Most enterprises believe their automation problems are caused by poor integration, but the real issue is the loss of intent as work moves across systems, teams, and vendors. Organizations already have APIs, connectors, and integration platforms, yet still experience delays, rework, audit failures, and constant manual intervention. That happens because systems preserve transactions, not decisions, forcing humans to act as message buses and tickets to function as state machines.

Adding AI on top of this broken handoff model does not fix the problem. In fact, treating AI as just a smarter form or chatbot makes things worse by introducing non-deterministic behavior into processes that require consistency, accountability, and proof. Enterprises are not building automations anymore; they are building distributed decision engines, which require strict constraints and full traceability to scale safely.

The solution is a clear architectural separation between deciding and doing. Copilot Studio belongs in the reasoning plane, where human intent is expressed, clarified, and structured. Logic Apps belongs in the execution plane, where actions are carried out in a deterministic, auditable, and repeatable way. MCP (Model Context Protocol) is the contract between these planes, preventing AI from improvising how enterprise systems are accessed by limiting models to approved, well-designed tools with explicit schemas and outcomes.

When intent is interpreted by AI, executed by governed workflows, and recorded with complete traceability, automation becomes reliable instead of fragile. This model reduces manual handoffs, prevents policy drift, simplifies audits, and allows AI to scale without increasing risk. The future of enterprise AI is not smarter chat, but governed execution where decisions and actions are cleanly separated, controlled, and provable.

Episode Summary

Most enterprise automation initiatives fail not because systems can’t connect, but because intent doesn’t survive handoffs. Despite years of investment in APIs, connectors, ETL tools, and integration platforms, organizations still struggle with delays, rework, audit findings, and fragile automations.

This episode reframes enterprise automation in the age of AI. It explains why treating AI as a smarter UI or chatbot makes things worse, why connectors alone are not governance, and why the future of enterprise AI depends on a clean separation between reasoning and execution.

We introduce a practical architectural model built around three core components: Copilot Studio as the intent interface, Logic Apps as the execution spine, and MCP (Model Context Protocol) as the contract that prevents AI from improvising inside enterprise systems.

The result is a scalable, auditable, and governable operating model for AI-driven automation that works in real enterprises, not just demos.


Core Thesis

Integration is not the problem. Intent loss is.

Enterprises already have connectivity:

  • APIs

  • Connectors

  • ETL pipelines

  • Integration platforms

Yet outcomes don’t improve because systems preserve transactions, not decisions. Every time a process crosses a boundary—team, system, vendor—context is lost. Humans fill the gaps by opening tickets, sending messages, building spreadsheets, and improvising workflows.

This episode explains why that behavior isn’t user error—it’s an architectural failure.


Why AI Makes This Problem Worse (If You Get It Wrong)

AI changes where decisions are made. If you bolt AI onto broken workflows:

  • Intent is still lost

  • Execution becomes non-deterministic

  • Errors become harder to trace

  • Audits become impossible to defend

A chatbot layered on top of a bad handoff doesn’t eliminate the handoff—it randomizes it.

Without constraints, AI:

  • Guesses which system is the source of truth

  • Guesses which fields matter

  • Guesses which permissions are implied

  • Guesses which actions are safe

And guessing is not something you can govern after the fact.


The Foundational Shift: From Automation to Decision Engines

Enterprises are no longer building simple automations.
They are building distributed decision engines.

Decision engines require:

  • Constraints – what actions are allowed

  • Traceability – what happened, why, and with what evidence

Without both, automation collapses into conditional chaos.


The Two-Plane Architecture Model

This episode introduces a simple but critical mental model:

Two Planes. Two Jobs. One Hard Boundary.


1. The Reasoning Plane

What it does well:

  • Interprets messy human intent

  • Asks clarifying questions

  • Frames decisions

  • Selects from allowed actions

What it must never do:

  • Execute transactions

  • Handle retries and compensation

  • Own audit evidence

  • Mutate systems of record

This plane is probabilistic by nature. That’s not a flaw—it’s why it’s useful.


2. The Execution Plane

What it does well:

  • Deterministic execution

  • Idempotent workflows

  • Predictable retries

  • Compensating actions

  • Durable audit trails

What it must never do:

  • Interpret vague intent

  • Guess next steps

  • Change behavior based on phrasing

This plane is boring on purpose. That boredom is how enterprises survive quarter close and audits.


Where Copilot Studio Fits

Copilot Studio is not the integration layer.
It is the intent interface.

Copilot Studio excels at:

  • Conversational intake

  • Extracting intent from humans

  • Turning fuzzy language into structured decisions

  • Selecting the correct next action

Copilot Studio fails when:

  • It writes directly to systems of record

  • It owns retries, error handling, and compensation

  • It embeds execution inside the reasoning plane

When Copilot is treated as the execution engine, organizations quietly rebuild the same fragile integration mess—just with better demos.


Why Logic Apps Is the Execution Spine

Logic Apps is often described as “low-code automation.”
That description is incomplete—and dangerous.

Architecturally, Logic Apps is:

  • A workflow runtime

  • A connector fabric

  • An observability and audit plane

Logic Apps provides:

  • Deterministic execution

  • Retry and compensation patterns

  • Run history as evidence

  • Controlled sequencing of actions

In an AI-driven world, execution must become boring, predictable, and reviewable. Logic Apps already does this at enterprise scale.


MCP (Model Context Protocol) Explained in Plain Language

MCP is not:

  • An API replacement

  • Another connector

  • Another integration platform

MCP is:

  • A tool contract between reasoning and execution

It defines:

  • Which tools AI is allowed to call

  • Exactly what inputs are required

  • What outputs are returned

  • What actions are prohibited

Without MCP:

  • AI guesses endpoints

  • AI guesses parameters

  • AI guesses permissions

With MCP:

  • AI selects from approved pathways

  • Creativity is constrained where it’s dangerous

  • Governance becomes structural, not advisory

MCP doesn’t make AI smarter. It makes AI safer.


Why Connectors Are Not Enough

Enterprises already have thousands of connectors.
That’s the problem.

Connector sprawl leads to:

  • Slightly different integrations everywhere

  • Inconsistent naming and schemas

  • Drift in security assumptions

  • Business logic implemented as folklore

Connectors are plumbing.
Plumbing is not governance.

MCP, combined with an execution plane, standardizes how tools are used, not just how systems connect.


Tool Design Is Governance

This episode makes a blunt claim:

Tool design is the unit of governance.

Bad tools create conditional chaos:

  • Generic “create record” actions

  • Overpowered schemas

  • Vague descriptions

  • Massive payloads

Good tools:

  • Map to business verbs

  • Have constrained inputs

  • Produce minimal, structured outputs

  • Encode policy directly in schemas

If a tool allows something, the system allows it—regardless of what the policy document says.


Real Enterprise Scenarios Covered

HR Onboarding

  • Eliminating ticket relay races

  • Enforcing access policy by design

  • Preventing privilege sprawl

  • Achieving day-one readiness with proof

Invoice Processing & Exceptions

  • Why exceptions—not invoices—are the real cost

  • Structured AI conversations for missing context

  • Deterministic financial controls

  • Reduced reconciliation and audit risk

IT Service Automation

  • Safe self-service without expanding risk

  • Deterministic execution for identity and access

  • Evidence-based escalation instead of guesswork

  • Measurable ticket deflection and SLA protection

SAP, Dataverse & Financial Sync

  • Preventing silent data drift

  • Enforcing ordering, idempotency, and retries

  • Avoiding reconciliation debt

  • Why finance trusts boring systems

Compliance & Audit Evidence

  • Turning audits into queries

  • Automating evidence collection

  • Eliminating screenshot archaeology

  • Trusting the trail, not the model


Governance That Doesn’t Rot

This episode outlines governance that actually scales:

  • Role separation (agent designers, workflow owners, operators)

  • Managed identity as the default

  • Environment isolation (dev/test/prod)

  • Private networking and trust boundaries

  • DLP as a data-movement decision

  • Authorization beyond authentication

Governance works only when enforcement is architectural, not optional.


Build Once. Reuse Everywhere.

Enterprises don’t lose to technology.
They lose to duplication.

This episode explains:

  • Why MCP servers without catalogs still fail

  • Why discoverability and trust matter

  • How catalogs turn tools into reusable products

  • Why AI without reuse guarantees tool sprawl

The goal isn’t faster agents.
The goal is shared, governed capabilities consumed by every agent.


Executive Takeaways

  • Integration failures are intent failures

  • AI amplifies architecture—good or bad

  • Separate reasoning from execution

  • Constrain AI where creativity is a liability

  • Treat tools as governance artifacts

  • Make execution boring and provable


One Line to Write on the Whiteboard

Copilot decides what should happen.
Logic Apps ensures it happens safely.


Closing Thought

The future of enterprise AI is not smarter chat.
It’s governed execution.

When intent, action, and evidence are cleanly separated, AI becomes scalable instead of fragile—and automation finally survives contact with reality.

Transcript

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Most enterprises talk about connectivity like it's plumbing, connect system A to system B,

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add a connector, call it transformation.

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That assumption feels safe.

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It's also why the same organizations keep replatforming every three years.

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Here's the promise, this is not a demo tour.

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It's a set of executive mental models you can reuse.

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Why logic apps is the execution spine, why copilot studio is the intent interface,

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and why MCP matters even when connectors already exist?

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Keep one question in mind.

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What problem are we actually solving?

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The foundational misunderstanding.

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Integration isn't the problem.

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This is the uncomfortable truth.

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Enterprises don't fail because systems can't connect.

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They fail because intent can't survive handoffs.

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The average organization already has connectivity.

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It has APIs, it has connectors, it has ETL, it has integration platforms.

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And yet the business still experiences the same outcomes, delays, rework, audit panic,

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and a constant feeling that automation should be easier than this.

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That's not a tooling gap, that's an intent gap.

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Every time a process crosses a boundary, team boundary, system boundary, vendor boundary,

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you lose context.

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And when you lose context, people improvise.

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They open tickets, they add exceptions, they make a spreadsheet, they ask for temporary access.

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They build a side flow just for this one case, those are not edge cases, those are entropy generators.

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Most organizations describe this as automation backlog.

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Architecturally, it's something else.

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You are using humans as message buses and you are using tickets as state machines.

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The hiring manager fills in a form, HR copies it into another system, I'd get the tickets,

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someone in identity makes an account, someone else assigns groups.

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Payroll needs a different attribute, facilities needs a badge request.

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The manager sends a team's message, can we expedite?

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And the actual state of the onboarding exists nowhere.

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It exists in fragments, half in the HR system, half in the ticketing system, half in email

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threads, and the final truth is whoever you can find on Slack at 9pm, that's what integration

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looks like in practice.

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And here's the trap, when leadership says we need better integration, they usually mean

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we need the humans to stop doing this.

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But the humans are doing it because the system does not preserve intent across steps, it

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preserves transactions, not decisions.

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Automation in most enterprises is treated as a set of isolated scripts, when x happens

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do why the coordination is what the enterprise actually needs.

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When x happens, what are we trying to achieve, under which constraints, and with what proof?

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This is why AI changes the story, and also why AI makes everything worse if you treat

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it like a UI feature.

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If you bolt a chatbot onto a broken handoff, you haven't eliminated the handoff.

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You've made it non-deterministic.

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Now the system doesn't just lose intent between teams, it can lose intent mid-sentence.

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You ask for provision access for the new hire, and the model guesses what access means.

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It guesses which system is the source of truth.

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It guesses which group naming convention matters.

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It guesses whether a finance analyst implies SAP roles or just a distribution list, and when

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it guesses wrong, the enterprise pays for it in the only currency that matters.

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Incident reviews and audit findings.

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So the foundational misunderstanding is this.

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AI isn't a smarter form, it's not a friendly UI for the same integration spaghetti.

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Architecturally you are building a distributed decision engine, that distinction matters.

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A decision engine needs two things if you wanted to scale, without turning into conditional

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chaos.

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Constraints and traceability.

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Constraints.

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What actions are allowed, what data can move, what pathways are legitimate.

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Traceability, what happened, who triggered it, what was decided, what tools were called,

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what was written, and where the evidence lives.

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Now connect that back to the real world.

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Executives don't wake up worried about connectors.

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They wake up worried about, why did we grant that access?

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Why did finance get the wrong number?

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Why did the integration break during quarter close?

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Why did this take three weeks when it should take three hours?

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Those are intent failures.

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And they compound over time.

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Because every workaround becomes precedent, every exception becomes a pattern, every temporary

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bypass becomes a dependency.

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Eventually policy exists in PowerPoint, but execution exists in whatever the last person

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did under pressure.

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The solution isn't more integration, the solution is an architecture where intent can be

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expressed, interpreted, and executed without being reinvented at every hop.

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That's the spine for the rest of this episode.

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Copilot Studio is where intent shows up in human language.

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Logic Apps is where execution becomes deterministic, auditable, and boring on purpose.

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And MCP is the contract that stops the model from improvising when it reaches for the enterprise.

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Now we can define MCP in terms that executives can actually reuse.

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MCP in plain terms, a contract between reasoning and doing.

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Okay, so basically, MCP model context protocol is a way to stop your AI from freelancing

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inside your enterprise.

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Kentware defines it cleanly.

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It is an open protocol that enables seamless integration between large language model applications

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or agents and tools and data.

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That sounds abstract until you translate it into what it prevents.

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MCP is not an API replacement, but it's not yet another connector.

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It's not a new integration platform you buy because you're tired of the old integration

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platform you bought.

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MCP is a tool contract, a contract between reasoning and doing.

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The reasoning side is the model.

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Non-deterministic, context-driven, good at language, good at picking an approach.

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The doing side is the enterprise, deterministic systems of record, compliance boundaries,

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limit, business rules, and the minor detail that finance will notice if you write the

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wrong thing.

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Without a contract model's guess, the guess which endpoint matters, the guess which parameters

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are required, the guess what create record means, the guess which account you meant, and

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you can't govern guessing.

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You can only apologize for it later.

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With MCP, you give the model a catalog of tools with explicit names, schemers and descriptions.

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The model doesn't need to invent a pathway.

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It chooses from approved pathways.

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It's the real shift from the model can call anything to the model can only call what you

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published.

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Here's what most people miss.

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Enterprises already have connectors.

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Logic apps has one four hundred plus connectors.

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Power Platform has connectors.

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Copilot Studio has connectors.

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So why care about MCP at all?

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Because connectors are not governance.

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Connectors are plumbing.

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At scale, connectors become connectors, brawl.

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Thousands of small, slightly different integrations built by different teams with different

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naming, different fields, different error handling and different security assumptions.

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It works until it doesn't and then you discover your business process is implemented as folklore.

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MCP is an attempt to standardize the shape of tool usage for models the same way APIs standardize

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the shape of system to system calls, but it's more specific than APIs.

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APIs are designed for developers who already know what they're doing and want maximum flexibility.

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MCP tools are designed for models that need constraints to be safe and cheap.

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That's why MCP tools are typically task focused, not here's a generic crud interface to your

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entire CRM.

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More like create a contact in Salesforce with these five fields or list incidents in service

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now with these filters or update an opportunity stage with these allowed values.

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You are narrowing the surface area on purpose because the models job isn't to explore your

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entire schema.

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The models job is to execute the business intent you allow.

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This is also why MCP shows up now, not five years ago.

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The world move to multi agent reality and multi platform reality.

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You will have co pilot studio in parts of the org.

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You will have foundry in parts of the org.

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You will have GitHub co pilot in engineering.

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You will have third party agents showing up anyway and every one of those will want to use

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tools.

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MCP is vendor agnostic pressure relief, a standard shape for tools so you can build

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once published ones and reuse across agent surfaces.

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And here's the consequence executives should care about.

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MCP reduces the amount of bespoke glue you have to govern, not because it removes complexity

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because it concentrates complexity into deliberate, reviewable, auditable tool definitions.

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If you remember nothing else from this section, remember this.

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MCP doesn't make the model smarter.

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It makes the model less creative in the places where creativity is a liability.

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Logic apps.

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What it is architecturally, not what marketing says.

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Logic apps is usually introduced as low code workflow automation.

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That description is not wrong.

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It's just incomplete in the way that gets organizations hurt.

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Architecturally, logic apps is not an automation toy.

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It is an execution runtime with a connector fabric and an observability plane glued to

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it.

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That combination matters because the moment you introduce AI reasoning, the only sane move

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is to make execution boring, deterministic and reviewable.

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Kentwear points out the awkward reality.

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Logic apps has been around almost 10 years.

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It launched in 2016.

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That's not trivia.

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It means enterprises have already been running business critical integrations on it long

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before anyone started saying, "agentic."

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The muscle is there.

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It triggers, connectors, retries, compensation patterns, run history and the miserable lessons

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that show up after the first time an integration fails during quarter close.

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So what is it in system terms?

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Logic apps is a workflow runtime that can accept a trigger, perform a sequence of calls

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and then persist an auditable record of what happened.

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It's the thing that turns, we should update three systems when this event happens into

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an artifact you can trace, rerun and prove.

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And the connector part is the other half of the story.

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Logic apps has a large connector library.

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It calls out 1,400 plus.

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That means an organization doesn't start from a blank sheet every time it needs to touch

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service now, SAP, Salesforce, Teams, Dataverse, SQL or some random SAS someone bought with

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a credit card.

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But here's the shift.

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In an MCP world, connectors are not the endpoint, they're raw material.

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Logic apps becomes the place where you wrap raw connector actions into governed tools and

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workflows.

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You decide what is exposed.

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You decide what is hidden.

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You decide what inputs matter.

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You decide what outputs return.

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And you do it once in a way that can be reused.

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Now deployment models, most people gloss over this.

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Don't logic apps has three deployment models.

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Consumption, standard and hybrid, that is not a feature list.

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It is a control plane decision.

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Consumption is multi-tenant, it's convenient.

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It's also by design not where you go when you need tight network boundaries and predictable

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execution at scale.

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Standard is single tenant.

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Can't describe that as single tenancy dedicated compute, dedicated storage, networking.

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That's the key.

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In standard, the workflow runs inside compute you control with networking you can shape.

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And with identity primitives that don't require you to play the where did this secret get

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copied game.

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Hybrid is the extension of that idea when you need to bring the runtime closer to your

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environment.

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Arc connected Kubernetes, semi connected execution, data staying local with telemetry sinking

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back.

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That's for the parts of the enterprise that still live in reality.

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Factories, regulated networks, awkward latency and the unspoken requirement that cloud

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outage cannot equal business outage.

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So why does any of this matter for co-pilot and MCP?

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Because the execution plane needs properties, the reasoning plane will never have.

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Deterministic behavior, predictable retries, clear failure modes and a run history that

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can serve as evidence.

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Logic apps gives you that by default.

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It's not glamorous, it's not conversational, it does not pretend to be intelligent.

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Good.

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In the AI era, the most valuable system is the one that refuses to improvise.

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And that's why logic apps become the practical MCP factory inside Microsoft Estates.

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It can take your enterprise's messy reality.

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It can take your business, networks, identities, throttling retries and package it into tools

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that are safe enough for a model to use without turning every request into a new experiment.

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Now we can place co-pilot studio correctly, not as the thing that integrates everything.

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As the thing that decides what should happen, then hands execution to something that can

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be held accountable.

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Co-pilot studio, the intent interface, not the integration layer.

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Co-pilot studio is where most leaders want to start because it looks like the business.

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A person asks a question.

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The system answers, it feels like progress.

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But the moment you confuse that interface for the integration layer, you've quietly

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rebuild the same old problem.

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You've put business intent inside a surface that can't own the enterprise's execution

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debt.

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That distinction matters.

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Co-pilot studio is excellent at three things, conversation, decision framing and tool selection.

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Conversation means it can pull context out of humans without forcing them through a form

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they hate.

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Hiring managers don't want to know which attribute maps to which HR field.

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They want to say start date is the 15th, remote needs contractor access and yes finance systems.

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Co-pilot studio can extract that cleanly.

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Decision framing means it can take fuzzy requests and turn them into a structured intent.

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What is the user trying to achieve?

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What constraints are implied?

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What information is missing?

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What needs approval?

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That is not integration.

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That's interpretation.

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Tool selection means it can choose the next action from a defined set of tools based

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on descriptions and schemas.

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And that's where it becomes dangerous if your tools are a mess because the model will

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still choose even if the choices are ambiguous.

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Here's the foundational mistake organizations make.

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They assume co-pilot studio should just connect to systems of record directly because it

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can.

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It can.

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It shouldn't.

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When co-pilot studio calls a connector directly, you've embedded execution inside the reasoning

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plane.

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You've made the model responsible for error handling, retries, compensations and the

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kinds of boring transactional guarantees that humans expect and systems rarely provide.

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That is not an AI problem.

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That is an architecture problem.

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Now to be fair, the tools landscape inside co-pilot studio is getting broader and more

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capable.

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You can use prompts.

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You can use connectors.

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You can use agent flows.

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You can use computer use for UI automation when the API story is terrible.

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And now you can use MCP.

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But each of those tools exists on a spectrum of governance.

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Prompts are flexible, but they're not evidence.

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Connectors are convenient, but they're not a control plane.

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Agent flows can be structured, but they still need an execution spine behind them if you

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want consistent enterprise behavior.

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Computer use is powerful, but it is literally automation through screens.

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That is the opposite of stable, and MCP is the one that forces you to stop pretending

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the model can safely improvise.

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This is why Kent's question lands.

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Co-pilot studio has connectivity.

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So why do I care about MCP server?

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Because the enterprise doesn't care that a single agent can do a thing once.

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The enterprise cares that the next 10 agents don't each invent their own way to do the same

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thing.

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MCP servers are how you make connectivity reusable, reviewable and portable across agent

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platforms.

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But the tool contract once, publish it and then co-pilot studio foundry VS code and whatever

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else shows up next can consume the same governed capabilities.

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It's also how you prevent connector sprawl from becoming agents sprawl.

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If every team can attach connectors directly to their agent, your security model will drift.

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Your data movement will drift.

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Your approval logic will drift.

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Not because people are reckless.

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Because entropy always wins when enforcement is optional.

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So co-pilot studio's role is specific.

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It is the intent interface.

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It is where humans express what they want.

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It is where the system asks the right follow-up questions.

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It is where reasoning happens and then it hands off to an execution layer that doesn't

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negotiate.

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That handoff is not a minor implementation detail.

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It's the architecture.

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Co-pilot studio without an execution spine becomes a high end demo machine.

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Impressive in a meeting.

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Unpredictable in production.

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Co-pilot studio with a governed execution layer becomes a scalable operating model.

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In addition, decisions, constraint actions and traceability you can defend in an audit.

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Now we can introduce the executive mental model that makes this click.

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Two planes.

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Two jobs.

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And a hard boundary between decide and do.

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The two plane model.

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Reasoning plane versus execution plane.

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Here's what most organizations miss until the first incident review.

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AI doesn't automate workflows.

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AI changes where decisions get made and once decisions move control either follows

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by design or it evaporates by accident.

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So the executive mental model is this.

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Two planes.

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A reasoning plane and an execution plane.

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The reasoning plane is co-pilot studio.

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It's conversational.

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It's adaptive.

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It's probabilistic by nature.

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It's good at interpreting messy human intent.

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Asking for missing context and deciding which option fits the moment.

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But it is not deterministic.

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It will never be deterministic.

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That's not a bug.

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That's what makes it useful.

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The execution plane is logic apps.

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It's transactional.

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It's auditable.

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It's designed to be boring.

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It takes a decision and turns it into a series of controlled actions against systems

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of record with retries, compensations and a run history that can survive and audit.

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It is deterministic on purpose.

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That distinction matters.

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Because if you blend the planes, you get conditional chaos.

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A system where outcomes vary based on phrasing, context drift, tool ambiguity or a model update

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you didn't schedule.

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In the two plane model, each plane has a job it can actually do well.

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In the reasoning plane, the job is interpret intent.

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What is the user really asking for?

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What policy constraints apply?

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What approvals are needed?

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What information is missing?

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And critically, what tool should be called next?

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In the execution plane, the job is enforce intent.

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Make the call the same way every time.

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Validate inputs.

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Handle failures predictably.

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Write to the right system in the right order with the right identity.

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Capture the evidence.

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Now connect this to the line that should be written on a whiteboard in every AI transformation

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steering committee.

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Copilot decides what should happen.

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Logic apps ensures it happens within your compliance boundaries.

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If copilot makes a decision that violates policy, the execution plane should refuse.

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If copilot makes a decision without required data, the execution plane should force the missing

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fields.

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If copilot makes a decision that triggers a risky operation, the execution plane should

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require an approval pathway or an escalation.

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This is where MCP becomes more than a protocol and starts acting like the seam between planes.

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MCP is how the reasoning plane asks the execution plane to do something without improvising

360
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the mechanics.

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The tool name is fixed.

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The schema is fixed.

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The inputs are explicit.

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The outputs are structured.

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The model stops guessing.

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It starts selecting.

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And that changes everything about blast radius because the most dangerous idea in enterprise

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AI is AI inside every workflow.

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That sounds modern.

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It's also how you end up with non-deterministic rights to your systems of record scattered across

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dozens of agents, each with slightly different prompts, slightly different tools and slightly

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different security assumptions.

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In other words, policy drift at machine speed.

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The two plane model reduces that risk by design.

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You don't let reasoning leak into execution.

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You don't let execution logic get rebuilt in every agent.

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You centralize execution into an orchestration layer that is observable, governable and repeatable.

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Then you let AI do what it's actually good at, understanding humans and choosing among

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constrained options.

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This also scales organizationally.

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Agent builders can focus on intents, conversations and decision quality.

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Workflow owners can focus on integration, integrity, idempotency and data contracts.

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Operators can focus on run, history, failures and evidence.

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That row separation is not bureaucracy.

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It's how you stop privilege sprawl and tool sprawl from becoming permanent.

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And if you're listening for the payoff, this is why MCP matters even when connectors exist.

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Connectors let you call systems MCP, paired with an execution plane, let you call systems

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safely.

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That's the difference between it works in a demo and it survives quarter close.

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Now that the model is clear, we can narrate what this actually looks like end to end.

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Event, reasoning, orchestration and an audit trail that doesn't rely on someone's memory.

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Walkthrough narrated.

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Event, reasoning, orchestration, audit trail.

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Here's the narrated version of what actually happens when this architecture is working end

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to end without screens.

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Start with a real signal, not a user click the button demo signal.

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A real enterprise event, a new hire is approved in the HR system and invoiced lands in a shared

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mailbox.

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A servitoo ticket gets created in your ITSM platform.

400
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A pricing update is published from SAP, something changes and now the enterprise has to respond.

401
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That event is the trigger and the first discipline is this.

402
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Don't let the trigger become the workflow, a trigger is just a fact.

403
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It says something happened.

404
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The reasoning plane is where the system decides what that fact means in business terms.

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So Copilot Studio takes the event, plus whatever context is allowed to see, and it does

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the part humans usually do in chat messages and half filled tickets, interpretation.

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00:19:04,080 --> 00:19:08,240
For HR onboarding, it looks at the hire request and immediately starts asking the questions

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that always get asked too late.

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Roll, location, start date, manager, equipment needs, standard access versus special access,

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contractor versus employee and whether any approvals are missing.

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For invoice exceptions, it does the thing, accounts payable teams hate doing manually.

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Why was this rejected?

413
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It reads the rejection reason, asks for missing context, normalizes vendor names and figures

414
00:19:29,240 --> 00:19:34,160
out whether this is a mismatch, a missing PO, a limit breach or an approval gap.

415
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For IT service automation, it identifies the intent.

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Password reset, device compliance, VPN access, mailbox permissions, whatever your tier catalog

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actually contains.

418
00:19:43,600 --> 00:19:46,520
And it checks whether this is within policy or needs escalation.

419
00:19:46,520 --> 00:19:47,520
Now here's the key.

420
00:19:47,520 --> 00:19:51,720
Copilot Studio is not calling random connectors because it can.

421
00:19:51,720 --> 00:19:57,160
It is selecting tools, MCP tools, tools with names and schemers that were designed in advance.

422
00:19:57,160 --> 00:20:01,880
This is where the system stops being a chatbot and starts behaving like a constrained operator.

423
00:20:01,880 --> 00:20:06,280
The agent sees a tool catalog and chooses a tool based on description and required inputs.

424
00:20:06,280 --> 00:20:07,600
It's not inventing an endpoint.

425
00:20:07,600 --> 00:20:09,320
It's not guessing at field names.

426
00:20:09,320 --> 00:20:10,920
It's selecting from what you published.

427
00:20:10,920 --> 00:20:14,680
Yes, the descriptions matter because they become decision inputs for the model.

428
00:20:14,680 --> 00:20:19,560
When Ken said MCP enables seamless integration between large language model applications or

429
00:20:19,560 --> 00:20:23,120
agents and tools and data, that's what seamless really means.

430
00:20:23,120 --> 00:20:25,760
The model gets a clean menu instead of a junk drawer.

431
00:20:25,760 --> 00:20:29,760
So Copilot Studio chooses the tool, fills in the schema and hands off the request to the

432
00:20:29,760 --> 00:20:30,760
execution plane.

433
00:20:30,760 --> 00:20:32,160
Now logic apps takes over.

434
00:20:32,160 --> 00:20:35,440
This is where the enterprise stops debating what should happen and starts doing what is

435
00:20:35,440 --> 00:20:36,600
allowed to happen.

436
00:20:36,600 --> 00:20:38,600
Logic apps executes connector calls.

437
00:20:38,600 --> 00:20:43,400
But it does it with boring features that matter in production, retries, timeouts, compensating

438
00:20:43,400 --> 00:20:45,720
actions and controlled sequencing.

439
00:20:45,720 --> 00:20:48,320
If a downstream system throttles it retries in the right way.

440
00:20:48,320 --> 00:20:53,800
If a step fails after partial success, it compensates or it roots to a human approval path.

441
00:20:53,800 --> 00:20:57,960
If a call needs enrichment, look up the manager's ID, map the vendor number, translate a location

442
00:20:57,960 --> 00:20:58,960
code.

443
00:20:58,960 --> 00:21:00,720
Logic apps does it deterministically.

444
00:21:00,720 --> 00:21:03,280
And this is why logic apps is the execution spine.

445
00:21:03,280 --> 00:21:04,760
It doesn't just call APIs.

446
00:21:04,760 --> 00:21:06,320
It owns the workflow reality.

447
00:21:06,320 --> 00:21:07,720
The enterprise depends on.

448
00:21:07,720 --> 00:21:12,320
Now the part executives should care about even more than the automation is the evidence trail.

449
00:21:12,320 --> 00:21:14,680
Because enterprises don't get punished for automating.

450
00:21:14,680 --> 00:21:16,960
They get punished for not being able to prove what happened.

451
00:21:16,960 --> 00:21:18,440
Logic apps gives you run history.

452
00:21:18,440 --> 00:21:22,600
And when you run MCP tools through it, you get a full chain, the trigger event, the parameters

453
00:21:22,600 --> 00:21:27,360
passed, the connector calls made, the responses received and the final output.

454
00:21:27,360 --> 00:21:33,480
Kent described it as full traceability, inputs outputs, what the user said, what the agent

455
00:21:33,480 --> 00:21:34,680
responded.

456
00:21:34,680 --> 00:21:36,160
We've got a very complete picture.

457
00:21:36,160 --> 00:21:37,440
That is not a nice to have.

458
00:21:37,440 --> 00:21:41,240
It is the difference between an automation you can scale and an automation you quietly turn

459
00:21:41,240 --> 00:21:43,200
off after the first compliance review.

460
00:21:43,200 --> 00:21:44,720
The output is simple.

461
00:21:44,720 --> 00:21:49,480
Systems update, tickets close, records reconcile, access provisions, approvals route and

462
00:21:49,480 --> 00:21:51,800
humans only touch the weird cases.

463
00:21:51,800 --> 00:21:53,120
But the real product isn't the update.

464
00:21:53,120 --> 00:21:56,280
The real product is that the enterprise can replay the truth.

465
00:21:56,280 --> 00:21:58,200
When someone asks, who approved this?

466
00:21:58,200 --> 00:21:59,200
You don't search teams.

467
00:21:59,200 --> 00:22:00,200
You pull the run.

468
00:22:00,200 --> 00:22:02,160
When someone asks, why did the agent do that?

469
00:22:02,160 --> 00:22:03,160
You don't blame the model.

470
00:22:03,160 --> 00:22:06,200
You show the tool call and the policy boundary at hit.

471
00:22:06,200 --> 00:22:08,680
And once you have that, you're not building automations anymore.

472
00:22:08,680 --> 00:22:10,880
You're building a govern decision and execution pipeline.

473
00:22:10,880 --> 00:22:14,440
Now we can talk about the part that determines whether the scales or collapses.

474
00:22:14,440 --> 00:22:15,760
Tool design.

475
00:22:15,760 --> 00:22:19,080
Tool design is governance, avoiding conditional chaos.

476
00:22:19,080 --> 00:22:23,920
This is where most agentec enterprise conversations collapse into a polite disaster.

477
00:22:23,920 --> 00:22:24,920
Tool design.

478
00:22:24,920 --> 00:22:27,880
Not model selection, not prompt tuning, not which chat surface you picked.

479
00:22:27,880 --> 00:22:28,880
Tool design.

480
00:22:28,880 --> 00:22:30,800
Because once a model has tools, it will use them.

481
00:22:30,800 --> 00:22:34,520
And if the tools are vague, overlapping or overpowered, you've created conditional

482
00:22:34,520 --> 00:22:38,600
chaos with a friendly UI, can set the line that should permanently ruin the idea of just

483
00:22:38,600 --> 00:22:40,200
expose the connector.

484
00:22:40,200 --> 00:22:42,240
Create record, create record of what?

485
00:22:42,240 --> 00:22:44,080
That question isn't pedantic.

486
00:22:44,080 --> 00:22:47,200
It's the entire governance problem in one sentence.

487
00:22:47,200 --> 00:22:51,480
In an enterprise connector, create record usually means create anything in a system that

488
00:22:51,480 --> 00:22:54,320
contains hundreds of entities and thousands of fields.

489
00:22:54,320 --> 00:22:57,240
Humans can handle that because humans carry context and caution.

490
00:22:57,240 --> 00:22:58,240
Models don't.

491
00:22:58,240 --> 00:23:02,560
Models optimize for completing the task and they will happily fill in blanks with guesses

492
00:23:02,560 --> 00:23:03,920
that look plausible.

493
00:23:03,920 --> 00:23:06,080
For the first rule of MCP Tool design is simple.

494
00:23:06,080 --> 00:23:07,320
Generic tools don't scale.

495
00:23:07,320 --> 00:23:09,040
They scale ambiguity.

496
00:23:09,040 --> 00:23:12,880
An ambiguity is expensive, in tokens, in retries, in wrong rights.

497
00:23:12,880 --> 00:23:17,480
And in the time you'll spend explaining to audit why an AI wrote something to somewhere,

498
00:23:17,480 --> 00:23:19,000
because the tool allowed it.

499
00:23:19,000 --> 00:23:22,760
The counter-intuitive part is that governance isn't a policy document.

500
00:23:22,760 --> 00:23:23,760
Governance is what you expose.

501
00:23:23,760 --> 00:23:27,920
And if you expose a tool that can write to ten tables, you've already lost the argument

502
00:23:27,920 --> 00:23:29,880
that you control the system.

503
00:23:29,880 --> 00:23:31,440
Control is not what you intended.

504
00:23:31,440 --> 00:23:32,760
Control is what the interface permits.

505
00:23:32,760 --> 00:23:38,360
So you design tools, like you designed guardrails, narrow surface area, clear intent, constrained

506
00:23:38,360 --> 00:23:41,080
inputs, predictable outputs.

507
00:23:41,080 --> 00:23:44,600
And the output constraints matter more than most people think because tool responses become

508
00:23:44,600 --> 00:23:45,920
model context.

509
00:23:45,920 --> 00:23:49,920
If you return the entire record payload every time you're not being thorough, you're burning

510
00:23:49,920 --> 00:23:53,320
tokens and feeding the model noise it will treat as relevant.

511
00:23:53,320 --> 00:23:59,000
The simple version is your tool schema is your policy boundary, now practical consequences.

512
00:23:59,000 --> 00:24:04,240
If you build an MCP tool called update opportunity, and it accepts any field in the opportunity

513
00:24:04,240 --> 00:24:08,960
object, the model will eventually update the wrong field, not because it's malicious,

514
00:24:08,960 --> 00:24:11,880
because it is trying to be helpful in a schema it can't fully reason about.

515
00:24:11,880 --> 00:24:16,160
But if you build advanced opportunity stage with allowed values required IDs and a constrained

516
00:24:16,160 --> 00:24:20,800
output that returns the new stage timestamp and a correlation ID, you've done something

517
00:24:20,800 --> 00:24:25,880
different, you've turned a risky right into a controlled action, that distinction matters.

518
00:24:25,880 --> 00:24:28,960
And this is where logic apps becomes more than an execution engine.

519
00:24:28,960 --> 00:24:32,640
It becomes a tool compiler, you take raw connectors and you wrap them into tools that match

520
00:24:32,640 --> 00:24:38,640
business verbs, not platform verbs, provision day one access, create incident with severity,

521
00:24:38,640 --> 00:24:43,480
validate invoice against PO, sync pricing changes with ID and potency, those aren't connector

522
00:24:43,480 --> 00:24:46,000
operations, they're governed capabilities.

523
00:24:46,000 --> 00:24:50,520
Now the part everyone underestimates tool descriptions, tool descriptions are not documentation,

524
00:24:50,520 --> 00:24:51,600
they're decision inputs.

525
00:24:51,600 --> 00:24:56,600
A model doesn't read your wiki, it reads the tool catalog description and schema, that's

526
00:24:56,600 --> 00:24:59,480
what it uses to decide whether a tool fits the situation.

527
00:24:59,480 --> 00:25:02,960
If the description is generic, the model selection is probabilistic, if the description is

528
00:25:02,960 --> 00:25:05,720
precise, the model selection becomes constrained.

529
00:25:05,720 --> 00:25:10,040
So you write descriptions like you're writing for a deterministic system, because you are.

530
00:25:10,040 --> 00:25:15,280
This tool creates a Salesforce contact with last name, email and account ID, use it only

531
00:25:15,280 --> 00:25:19,880
when a human confirms the contact should be created, that is governance.

532
00:25:19,880 --> 00:25:25,280
And the moment you do that consistently, something else happens, you reduce tool collisions.

533
00:25:25,280 --> 00:25:29,680
You reduce duplicate tools across teams, you reduce the temptation for every agent builder

534
00:25:29,680 --> 00:25:33,640
to invent their own slightly different version of the same capability, because they don't

535
00:25:33,640 --> 00:25:34,640
need to.

536
00:25:34,640 --> 00:25:37,200
This is also where you kill entropy generators early.

537
00:25:37,200 --> 00:25:41,280
Policy exceptions thrive in ambiguity, side channels thrive when the official path is

538
00:25:41,280 --> 00:25:43,440
harder than the unofficial one.

539
00:25:43,440 --> 00:25:47,560
Shadow integrations appear when the blessed tool can't answer the real question.

540
00:25:47,560 --> 00:25:51,720
Well designed tools remove those escape hatches, not by telling people to behave, by making

541
00:25:51,720 --> 00:25:53,560
the correct path the easiest path.

542
00:25:53,560 --> 00:25:55,800
Now tie this back to governance as an enabler.

543
00:25:55,800 --> 00:25:59,720
A tool catalog that's curated and constrained is what allows you to move faster without losing

544
00:25:59,720 --> 00:26:00,720
control.

545
00:26:00,720 --> 00:26:04,600
It's how you let teams build agents quickly without granting them raw access to systems

546
00:26:04,600 --> 00:26:05,600
of record.

547
00:26:05,600 --> 00:26:09,720
It's how you let co-pilot studio do things without turning every action into a bespoke

548
00:26:09,720 --> 00:26:10,720
security review.

549
00:26:10,720 --> 00:26:13,720
You don't govern agent behavior by reviewing every conversation.

550
00:26:13,720 --> 00:26:16,000
You govern it by designing what actions are possible.

551
00:26:16,000 --> 00:26:17,000
That's why MCP matters.

552
00:26:17,000 --> 00:26:18,320
It's not just a protocol.

553
00:26:18,320 --> 00:26:21,560
It's a forcing function that makes tool design the unit of governance.

554
00:26:21,560 --> 00:26:26,200
And once tool design is governance, you stop arguing about whether AI is safe.

555
00:26:26,200 --> 00:26:27,840
You start proving it.

556
00:26:27,840 --> 00:26:30,680
Scenario one, HR onboarding across systems.

557
00:26:30,680 --> 00:26:34,520
HR onboarding is the universal enterprise mess because it looks simple until you try to

558
00:26:34,520 --> 00:26:35,840
do it consistently.

559
00:26:35,840 --> 00:26:37,080
A person is hired.

560
00:26:37,080 --> 00:26:38,080
They need an identity.

561
00:26:38,080 --> 00:26:39,080
They need a mailbox.

562
00:26:39,080 --> 00:26:40,080
They need access.

563
00:26:40,080 --> 00:26:41,080
They need a device.

564
00:26:41,080 --> 00:26:42,080
They need payroll.

565
00:26:42,080 --> 00:26:45,520
They need just one exception because the new hire is remote or a contractor or joining

566
00:26:45,520 --> 00:26:48,960
finance or starting tomorrow or all of the above.

567
00:26:48,960 --> 00:26:54,120
And every one of those needs lives in a different system owned by a different team with a different

568
00:26:54,120 --> 00:26:55,880
definition of done.

569
00:26:55,880 --> 00:26:57,600
So here's the strategic framing.

570
00:26:57,600 --> 00:26:59,360
onboarding isn't an integration problem.

571
00:26:59,360 --> 00:27:03,760
It's a coordination problem with security consequences because the moment onboarding becomes

572
00:27:03,760 --> 00:27:06,720
a ticket relay race, two things always happen.

573
00:27:06,720 --> 00:27:07,720
First you lose time.

574
00:27:07,720 --> 00:27:09,800
Day one readiness turns into day three readiness.

575
00:27:09,800 --> 00:27:10,800
Then day seven readiness.

576
00:27:10,800 --> 00:27:13,840
Then they'll be fine with shared access for now.

577
00:27:13,840 --> 00:27:15,120
Second you lose control.

578
00:27:15,120 --> 00:27:19,720
The access becomes normal access manual overrides become permanent pathways and nobody can prove

579
00:27:19,720 --> 00:27:23,880
why a given person got a given entitlement because the decision lived in an email and the

580
00:27:23,880 --> 00:27:25,760
execution happened in four different places.

581
00:27:25,760 --> 00:27:28,640
Now drop co pilot studio and logic apps into that reality.

582
00:27:28,640 --> 00:27:30,560
The intent interface is co pilot studio.

583
00:27:30,560 --> 00:27:34,840
The hiring manager doesn't need to know what entry attribute maps to what downstream system.

584
00:27:34,840 --> 00:27:37,120
They need to communicate intent in human terms.

585
00:27:37,120 --> 00:27:42,920
Roll location start date manager department employment type and whether standard access applies

586
00:27:42,920 --> 00:27:45,080
or special access is required.

587
00:27:45,080 --> 00:27:47,520
And co pilot studio's job is not to guess the answer.

588
00:27:47,520 --> 00:27:51,240
It's to interrogate the request until the request becomes executable.

589
00:27:51,240 --> 00:27:53,280
This is where you reduce entropy early.

590
00:27:53,280 --> 00:27:56,320
The agent asks the questions humans usually ask too late.

591
00:27:56,320 --> 00:27:59,840
It confirms whether the person is employee or contractor, whether they need privileged

592
00:27:59,840 --> 00:28:04,520
access, whether they handle regulated data, whether they require SIP rolls, whether they

593
00:28:04,520 --> 00:28:09,640
need a device shipped and whether approvals exist for any non-standard entitlements.

594
00:28:09,640 --> 00:28:11,280
Then the handoff happens.

595
00:28:11,280 --> 00:28:15,560
The pilot selects a tool not a connector a tool with a name that encodes your governance

596
00:28:15,560 --> 00:28:21,640
intent like start on boarding for new hire or provision day one access.

597
00:28:21,640 --> 00:28:25,960
And this is where mcp matters the model isn't improvising a sequence of connector calls.

598
00:28:25,960 --> 00:28:29,160
It is calling a published capability with a schema you defined.

599
00:28:29,160 --> 00:28:33,760
The request goes into logic apps and logic apps does the boring work that you actually want

600
00:28:33,760 --> 00:28:34,760
boring.

601
00:28:34,760 --> 00:28:38,520
It creates the identity using managed identity not shared credentials.

602
00:28:38,520 --> 00:28:42,600
It assigns baseline groups using explicit mappings, not whatever the model thinks.

603
00:28:42,600 --> 00:28:46,800
It provisions the mailbox, triggers device enrollment tasks, creates payroll records

604
00:28:46,800 --> 00:28:49,160
and opens or updates the ITSM ticket.

605
00:28:49,160 --> 00:28:52,880
So the operational teams see a single authoritative state.

606
00:28:52,880 --> 00:28:54,960
If something fails, it doesn't apologize.

607
00:28:54,960 --> 00:28:57,920
It retries, it compensates, it escalates.

608
00:28:57,920 --> 00:28:59,600
This is the part executives miss.

609
00:28:59,600 --> 00:29:01,160
You aren't automating on boarding.

610
00:29:01,160 --> 00:29:04,520
You're automating the control plane for on boarding because the workflow becomes the

611
00:29:04,520 --> 00:29:09,320
place where you enforce what done means and you can enforce separation of duties by design.

612
00:29:09,320 --> 00:29:13,400
Agent builders can define the conversational experience and the intent model.

613
00:29:13,400 --> 00:29:16,480
Workflow owners control the execution layer.

614
00:29:16,480 --> 00:29:22,600
Which systems are touched in what order, with what identity and what evidence is recorded.

615
00:29:22,600 --> 00:29:27,000
Operators monitor runs and failures without needing access to redesign tools.

616
00:29:27,000 --> 00:29:31,440
That RBX split matters because on boarding is where privileged sprawl starts.

617
00:29:31,440 --> 00:29:34,080
Now take the scenario everyone has.

618
00:29:34,080 --> 00:29:35,080
Special access.

619
00:29:35,080 --> 00:29:38,880
A manager says they'll need finance reporting access on day one.

620
00:29:38,880 --> 00:29:43,080
In the old model that becomes a side channel, a team's message to someone who can do it real

621
00:29:43,080 --> 00:29:44,080
quick.

622
00:29:44,080 --> 00:29:47,920
In this model, Copilot collects the justification and roots it into the workflow.

623
00:29:47,920 --> 00:29:49,920
Logic apps enforces the policy boundary.

624
00:29:49,920 --> 00:29:54,080
Either it requires an approval step or it queues it for a privileged workflow or it

625
00:29:54,080 --> 00:29:59,520
refuses unless the request meets conditions you defined, same request, different outcome.

626
00:29:59,520 --> 00:30:03,600
Not because the AI is smarter, because the system is constrained and the audit story becomes

627
00:30:03,600 --> 00:30:04,600
clean.

628
00:30:04,600 --> 00:30:07,040
If someone asks why did this person receive that access?

629
00:30:07,040 --> 00:30:09,240
You don't reconstruct the narrative from five systems.

630
00:30:09,240 --> 00:30:10,320
You open the run history.

631
00:30:10,320 --> 00:30:14,480
You see who asked what was asked, what approvals were captured, what tools were called, what

632
00:30:14,480 --> 00:30:17,800
groups were assigned and what downstream updates were made.

633
00:30:17,800 --> 00:30:21,520
That is the actual value of enterprise connectivity in an AI era.

634
00:30:21,520 --> 00:30:24,600
Not faster clicks, but fewer, untracked decisions.

635
00:30:24,600 --> 00:30:27,080
And the business outcome is easy to say without hype.

636
00:30:27,080 --> 00:30:32,440
Fewer manual handoffs, faster day one readiness, fewer access mistakes and a measurable reduction

637
00:30:32,440 --> 00:30:34,600
in the hidden labor of coordination.

638
00:30:34,600 --> 00:30:39,040
Now that the pattern is clear, the next scenario makes the same point from a different angle.

639
00:30:39,040 --> 00:30:40,280
Invoices aren't hard.

640
00:30:40,280 --> 00:30:41,280
Exceptions are.

641
00:30:41,280 --> 00:30:42,280
Scenario 2.

642
00:30:42,280 --> 00:30:44,080
Invoice processing and exception handling.

643
00:30:44,080 --> 00:30:47,080
Invoice automation is always sold as a paper to ERP story.

644
00:30:47,080 --> 00:30:51,240
Scan the PDF, extract the fields, match the PO, post the invoice, done.

645
00:30:51,240 --> 00:30:52,480
That's the brochure version.

646
00:30:52,480 --> 00:30:54,800
In reality, invoices aren't hard.

647
00:30:54,800 --> 00:30:57,120
Expansions are endless and they are usually undocumented.

648
00:30:57,120 --> 00:31:00,200
The vendor name doesn't match what procurement entered three years ago.

649
00:31:00,200 --> 00:31:03,040
The PO is missing, but we always pay this vendor.

650
00:31:03,040 --> 00:31:06,400
The amounts don't line up because someone changed pricing after the PO.

651
00:31:06,400 --> 00:31:08,680
The approval threshold got exceeded by $12.

652
00:31:08,680 --> 00:31:12,360
The cost center is wrong, the invoice got emailed to the wrong mailbox.

653
00:31:12,360 --> 00:31:14,960
The line items are structured like a ransom note.

654
00:31:14,960 --> 00:31:19,520
And every business unit has its own definition of urgent, so the enterprise cost isn't invoice

655
00:31:19,520 --> 00:31:20,520
processing.

656
00:31:20,520 --> 00:31:22,040
It's human exception triage.

657
00:31:22,040 --> 00:31:25,320
And that triage is almost always done in the worst possible place.

658
00:31:25,320 --> 00:31:30,080
Email threads and comments inside whatever ERP screen someone happens to know.

659
00:31:30,080 --> 00:31:31,880
Here's the architectural reframing.

660
00:31:31,880 --> 00:31:35,240
Invoice exceptions are a coordination problem with money attached.

661
00:31:35,240 --> 00:31:36,240
That means two things.

662
00:31:36,240 --> 00:31:40,480
First, you need a reasoning surface that can collect context without forcing AP to become

663
00:31:40,480 --> 00:31:41,480
a detective.

664
00:31:41,480 --> 00:31:46,800
Second, you need an execution layer that refuses to just post it when policy says otherwise.

665
00:31:46,800 --> 00:31:51,800
This is where co-pilot studio earns its place, not by automating finance.

666
00:31:51,800 --> 00:31:56,160
By handling the conversation nobody wants to have manually, 50 times a day.

667
00:31:56,160 --> 00:32:00,160
When an invoice fails validation, the agent can answer the only question people actually

668
00:32:00,160 --> 00:32:02,400
ask, why was this rejected?

669
00:32:02,400 --> 00:32:06,040
And it can do the follow-up work that humans usually do via back and forth.

670
00:32:06,040 --> 00:32:07,800
Which PO should this map to?

671
00:32:07,800 --> 00:32:09,080
Is this a duplicate?

672
00:32:09,080 --> 00:32:10,800
Who owns this cost center?

673
00:32:10,800 --> 00:32:12,720
Do you want to split the amount?

674
00:32:12,720 --> 00:32:15,920
Is this a legitimate exception and if so, who can approve it?

675
00:32:15,920 --> 00:32:19,240
That matters because it pulls intent out of the business in plain language.

676
00:32:19,240 --> 00:32:22,280
And then the system has to stop being polite and start being strict.

677
00:32:22,280 --> 00:32:25,240
This is where logic apps become the execution spine again.

678
00:32:25,240 --> 00:32:27,840
The model can reason across messy inputs.

679
00:32:27,840 --> 00:32:31,160
But the workflow decides what can move where.

680
00:32:31,160 --> 00:32:35,960
Logic apps enforces validations, vendor match, PO match, limits and approval routing.

681
00:32:35,960 --> 00:32:38,560
It does the ordering that keeps finance sane.

682
00:32:38,560 --> 00:32:40,160
Enrich invoice data.

683
00:32:40,160 --> 00:32:44,680
Check against authoritative systems, root to approvals if thresholds trip, then right back to the

684
00:32:44,680 --> 00:32:49,880
ERP only when the conditions are satisfied. And it does it with audit grade behavior, deterministic

685
00:32:49,880 --> 00:32:53,480
steps, retries where retries make sense and a recorded run history.

686
00:32:53,480 --> 00:32:56,800
Now at the part most AI demos skip because it's not as fun.

687
00:32:56,800 --> 00:32:57,800
DLP.

688
00:32:57,800 --> 00:32:59,400
In finance, DLP isn't a slide.

689
00:32:59,400 --> 00:33:02,920
It's the difference between, we can deploy this and security shut it down.

690
00:33:02,920 --> 00:33:04,280
The practical model is simple.

691
00:33:04,280 --> 00:33:06,280
AI can reason across information.

692
00:33:06,280 --> 00:33:09,640
Workflows decide what information is allowed to move between systems.

693
00:33:09,640 --> 00:33:13,600
So you can let co-pilot studio interpret an exception, summarize what's missing and ask

694
00:33:13,600 --> 00:33:15,360
the user for clarification.

695
00:33:15,360 --> 00:33:19,600
Without granting it direct, unconstrained access to write into your system of record, because

696
00:33:19,600 --> 00:33:22,080
authenticated does not mean authorized.

697
00:33:22,080 --> 00:33:25,600
And even authorized does not mean safe to execute without guardrails.

698
00:33:25,600 --> 00:33:28,320
Now in MCP terms, this becomes a tool story.

699
00:33:28,320 --> 00:33:32,720
You don't expose a generic, create invoice tool with a hundred fields and vague meanings.

700
00:33:32,720 --> 00:33:36,080
You expose an invoice exception resolution tool set.

701
00:33:36,080 --> 00:33:40,880
Validate invoice against PO, retrieve vendor master details, request approval for exception

702
00:33:40,880 --> 00:33:45,840
type X, post invoice with correlation ID, and return a structured result that contains

703
00:33:45,840 --> 00:33:48,560
what happened and what evidence was created.

704
00:33:48,560 --> 00:33:52,880
The model doesn't freehand an ERP transaction, it selects from approved actions.

705
00:33:52,880 --> 00:33:56,080
And the best part is the outcome that executives actually care about.

706
00:33:56,080 --> 00:33:58,920
Humans only touch exceptions, not the happy path.

707
00:33:58,920 --> 00:34:03,360
Happy path invoices post automatically with boring reliability.

708
00:34:03,360 --> 00:34:06,760
Exceptions become structured conversations with constrained outcomes, and you can measure

709
00:34:06,760 --> 00:34:12,280
it in the only ways finance trusts, reduced cycle time, fewer manual touches per invoice,

710
00:34:12,280 --> 00:34:16,360
and fewer we don't know why this was posted moments that show up during close.

711
00:34:16,360 --> 00:34:17,880
This also changes the failure mode.

712
00:34:17,880 --> 00:34:21,120
In the old world, the failure mode is silent drift.

713
00:34:21,120 --> 00:34:24,040
Someone finds a workaround and it becomes policy by accident.

714
00:34:24,040 --> 00:34:26,160
In this world, the failure mode is explicit.

715
00:34:26,160 --> 00:34:29,080
The workflow refuses, roots, or escalates.

716
00:34:29,080 --> 00:34:32,720
And you can see it happen, which means your control environment becomes a system, not

717
00:34:32,720 --> 00:34:33,720
a story.

718
00:34:33,720 --> 00:34:37,640
In voice exception, stop consuming human attention, you get a second order benefit.

719
00:34:37,640 --> 00:34:42,400
Your AP team stops spending time, being a message bus, and start spending time on the only

720
00:34:42,400 --> 00:34:46,480
work worth human judgment, actual anomalies and actual fraud signals.

721
00:34:46,480 --> 00:34:51,400
Now if you want the scenario where this becomes even more obvious, it's IT service automation.

722
00:34:51,400 --> 00:34:55,240
Because IT isn't paid to be creative, it is paid to be consistent under pressure with

723
00:34:55,240 --> 00:34:56,240
receipts.

724
00:34:56,240 --> 00:34:57,240
Scenario 3.

725
00:34:57,240 --> 00:34:58,760
IT service automation.

726
00:34:58,760 --> 00:35:02,720
IT service management is where enterprise reality shows up without makeup.

727
00:35:02,720 --> 00:35:04,320
It's a repetitive.

728
00:35:04,320 --> 00:35:06,760
Documentation is outdated the day after it's written.

729
00:35:06,760 --> 00:35:10,200
Tribal knowledge lives in the heads of two people you can't afford to lose.

730
00:35:10,200 --> 00:35:14,240
And the SLA clock keeps running even when the root cause is a user who swears they didn't

731
00:35:14,240 --> 00:35:15,240
change anything.

732
00:35:15,240 --> 00:35:19,120
So yes, it is a great place to start with a genetic orchestration, not because it's glamorous,

733
00:35:19,120 --> 00:35:22,680
because it's measurable, painful, and full of work that should not require a human to

734
00:35:22,680 --> 00:35:24,960
interpret the same request for the thousandth time.

735
00:35:24,960 --> 00:35:27,920
But here's the thing, most organizations get wrong when they try it.

736
00:35:27,920 --> 00:35:29,960
They aim for AI resolve's tickets.

737
00:35:29,960 --> 00:35:30,960
That's not the real objective.

738
00:35:30,960 --> 00:35:31,960
The real objective is.

739
00:35:31,960 --> 00:35:38,280
AI handles standard intents and the system escalates only when policy thresholds are crossed.

740
00:35:38,280 --> 00:35:41,640
Tier to tier 2 is not a human hierarchy, it's a control boundary.

741
00:35:41,640 --> 00:35:44,600
Tier is self-service and safe automation.

742
00:35:44,600 --> 00:35:50,120
Password resets account unlocks basic access requests, known device compliance checks, standard

743
00:35:50,120 --> 00:35:55,880
VPN, troubleshooting prompts, maybe a simple, how do I request that roots to a knowledge base?

744
00:35:55,880 --> 00:35:58,600
Tier 1 is guided execution with guardrails.

745
00:35:58,600 --> 00:36:02,200
If you do this action, then verify this condition, then notify the user.

746
00:36:02,200 --> 00:36:06,400
It's still mostly deterministic, it's the human doing the steps because the system didn't.

747
00:36:06,400 --> 00:36:09,800
Tier 2 is where the organization actually pays for judgment.

748
00:36:09,800 --> 00:36:14,840
Complex incidents, ambiguous symptoms, high impact outages, or anything that can create collateral

749
00:36:14,840 --> 00:36:15,840
damage.

750
00:36:15,840 --> 00:36:19,920
Agentech orchestration is about moving work down the stack without moving risk up the stack.

751
00:36:19,920 --> 00:36:21,280
So here's the pattern.

752
00:36:21,280 --> 00:36:24,200
Copilot Studio becomes the intake and triage surface.

753
00:36:24,200 --> 00:36:28,000
It takes messy user language and turns it into a clean intent.

754
00:36:28,000 --> 00:36:34,080
Password, re-enroll device, request application access, check mailbox permissions, troubleshoot

755
00:36:34,080 --> 00:36:38,920
teams audio, whatever your top ticket categories actually are, then it does the part a ticket

756
00:36:38,920 --> 00:36:40,520
form never does well.

757
00:36:40,520 --> 00:36:42,880
It collects the missing context conversationally.

758
00:36:42,880 --> 00:36:47,200
Device name, error message, location, whether it's a new device or a rebuild, whether the

759
00:36:47,200 --> 00:36:51,280
user is traveling, whether this is affecting one person or a whole team.

760
00:36:51,280 --> 00:36:53,360
This seems small, it's not.

761
00:36:53,360 --> 00:36:57,360
Because IT tickets fail for the same reason invoices fail, missing context forces humans

762
00:36:57,360 --> 00:36:58,520
to improvise.

763
00:36:58,520 --> 00:37:01,440
Then Copilot selects the tool and this is where you need to be ruthless.

764
00:37:01,440 --> 00:37:04,120
IT tools are not query everything and do anything.

765
00:37:04,120 --> 00:37:07,800
That's how you end up with an agent that can disable accounts because someone phrased

766
00:37:07,800 --> 00:37:08,800
a question badly.

767
00:37:08,800 --> 00:37:11,600
Your MCP tools here should map to safe verbs.

768
00:37:11,600 --> 00:37:17,720
Reset password for user, unlock account, create incident with severity, check device compliance,

769
00:37:17,720 --> 00:37:22,600
request software access with a profile, update ticket status, notify user.

770
00:37:22,600 --> 00:37:25,000
If you're hearing repetition, good repetition is the point.

771
00:37:25,000 --> 00:37:29,080
A safe enterprise is mostly repeated patterns executed consistently.

772
00:37:29,080 --> 00:37:33,680
Now logic apps takes the request and executes it and this is where IT benefits from boring

773
00:37:33,680 --> 00:37:38,760
on purpose more than any other domain because IT automation isn't just do the thing.

774
00:37:38,760 --> 00:37:43,040
It's do the thing, then prove it worked, then record what happened.

775
00:37:43,040 --> 00:37:47,600
Logic apps can update your ITSM platform, service now, Azure DevOps, whatever your reality

776
00:37:47,600 --> 00:37:48,600
is.

777
00:37:48,600 --> 00:37:50,400
It can call graph for identity operations.

778
00:37:50,400 --> 00:37:54,280
It can integrate with endpoint tooling that can post to teams, it can send email, it can

779
00:37:54,280 --> 00:37:59,280
trigger follow-up actions and it can do it with controlled retries and clear failure parts.

780
00:37:59,280 --> 00:38:03,280
If the password reset fails due to a lockout policy, the workflow doesn't keep guessing.

781
00:38:03,280 --> 00:38:04,520
It roots to escalation.

782
00:38:04,520 --> 00:38:08,840
If the device action fails, it captures the error, attaches it to the ticket and moves the

783
00:38:08,840 --> 00:38:10,440
case to tier two with evidence.

784
00:38:10,440 --> 00:38:11,600
This is the real win.

785
00:38:11,600 --> 00:38:14,640
You stop escalating tickets without context.

786
00:38:14,640 --> 00:38:15,760
You escalate with a record.

787
00:38:15,760 --> 00:38:20,120
Now add governance because IT is where governance either becomes real or it becomes a slide.

788
00:38:20,120 --> 00:38:25,240
You separate roles, agent designers build the conversational experience and intent rooting.

789
00:38:25,240 --> 00:38:28,160
Workflow owners build and maintain the executable pathways.

790
00:38:28,160 --> 00:38:32,600
Operators watch run history and manage failures and authentication does not equal authorization.

791
00:38:32,600 --> 00:38:36,400
The system can authenticate the agent and still restrict which tool calls are permitted

792
00:38:36,400 --> 00:38:39,440
for which scenarios, which users and which groups.

793
00:38:39,440 --> 00:38:45,040
If you let any authenticated agent call any IT tool, you just created a new tier incident

794
00:38:45,040 --> 00:38:46,040
generator.

795
00:38:46,040 --> 00:38:49,640
This is also where managed identities and least privilege stop being best practice and

796
00:38:49,640 --> 00:38:51,080
start being survival.

797
00:38:51,080 --> 00:38:55,680
No shed credentials in a workflow, no copy-paste API keys inside an agent, no temporary service

798
00:38:55,680 --> 00:38:58,720
accounts that become permanent because nobody wants to rotate them.

799
00:38:58,720 --> 00:39:01,560
Now for the part executives will actually ask for outcomes.

800
00:39:01,560 --> 00:39:06,520
In IT and HR, 20 to 40% ticket deflection is a credible range when you focus on the top

801
00:39:06,520 --> 00:39:07,760
repetitive intents.

802
00:39:07,760 --> 00:39:12,120
Not because the AI is brilliant, because the system finally stops requiring humans to coordinate

803
00:39:12,120 --> 00:39:13,120
between tools.

804
00:39:13,120 --> 00:39:15,720
And the bigger outcome is SLA protection.

805
00:39:15,720 --> 00:39:19,880
When the agent handles the standard work, humans get time back for real incidents.

806
00:39:19,880 --> 00:39:22,560
When escalations happen, they happen with context and evidence.

807
00:39:22,560 --> 00:39:26,120
When audits ask who changed what, you can answer without archaeology.

808
00:39:26,120 --> 00:39:28,800
Kentware even said it directly in the context of IT.

809
00:39:28,800 --> 00:39:31,960
IT service management always a good place to start.

810
00:39:31,960 --> 00:39:33,280
He's not being optimistic.

811
00:39:33,280 --> 00:39:35,640
He's describing where the economics work first.

812
00:39:35,640 --> 00:39:40,040
And once you can prove this works in IT, where metrics are unforgiving, you have a template

813
00:39:40,040 --> 00:39:41,840
you can take to every other domain.

814
00:39:41,840 --> 00:39:45,840
The same two-plane model, the same constraint tools, the same deterministic execution, the

815
00:39:45,840 --> 00:39:47,320
same traceability.

816
00:39:47,320 --> 00:39:51,120
Now the next scenario is where you find out whether your orchestration layer is real or

817
00:39:51,120 --> 00:39:52,600
just polite.

818
00:39:52,600 --> 00:39:55,760
Transactual sync across systems of record where failure isn't annoying.

819
00:39:55,760 --> 00:39:56,760
It's expensive.

820
00:39:56,760 --> 00:39:57,760
Snaurio 4.

821
00:39:57,760 --> 00:39:58,760
SAP.

822
00:39:58,760 --> 00:39:59,760
Dataverse.

823
00:39:59,760 --> 00:40:01,960
Lobby sync without breaking finance.

824
00:40:01,960 --> 00:40:06,200
SAP and finance adjacent systems are where just automated goes to die.

825
00:40:06,200 --> 00:40:09,560
Because the failure mode isn't a funny demo glitch, it's a reconciliation exercise that

826
00:40:09,560 --> 00:40:11,280
becomes someone's full-time job.

827
00:40:11,280 --> 00:40:13,800
And here's the pattern every enterprise recognizes.

828
00:40:13,800 --> 00:40:14,800
Pricing.

829
00:40:14,800 --> 00:40:16,000
Customer master data.

830
00:40:16,000 --> 00:40:17,400
Vendor master data.

831
00:40:17,400 --> 00:40:18,400
Product catalog.

832
00:40:18,400 --> 00:40:19,400
Cost centers.

833
00:40:19,400 --> 00:40:20,400
GL mappings.

834
00:40:20,400 --> 00:40:21,400
Pick your poison.

835
00:40:21,400 --> 00:40:24,760
The business wants a change to show up everywhere, immediately and consistently.

836
00:40:24,760 --> 00:40:26,080
But the estate is a patchwork.

837
00:40:26,080 --> 00:40:27,080
SAP.

838
00:40:27,080 --> 00:40:28,080
Dataverse.

839
00:40:28,080 --> 00:40:30,920
A few line of business apps that matter way more than they look like they should.

840
00:40:30,920 --> 00:40:34,680
And an integration layer that's accumulated five years of temporary fixes.

841
00:40:34,680 --> 00:40:36,000
So teams try to sync.

842
00:40:36,000 --> 00:40:37,600
They build point to point calls.

843
00:40:37,600 --> 00:40:38,960
They wire up a connector.

844
00:40:38,960 --> 00:40:39,960
They do a nightly job.

845
00:40:39,960 --> 00:40:40,960
It works for a while.

846
00:40:40,960 --> 00:40:42,840
And then something fails silently.

847
00:40:42,840 --> 00:40:44,120
A request times out.

848
00:40:44,120 --> 00:40:45,960
A downstream API throttles.

849
00:40:45,960 --> 00:40:47,440
A duplicate update slips through.

850
00:40:47,440 --> 00:40:48,280
A schema changes.

851
00:40:48,280 --> 00:40:50,200
A retry replays the wrong step.

852
00:40:50,200 --> 00:40:53,160
The sync succeeds in one system and fails in another.

853
00:40:53,160 --> 00:40:55,400
And now your systems of record disagree.

854
00:40:55,400 --> 00:40:56,920
That is not a technical annoyance.

855
00:40:56,920 --> 00:40:58,880
That is financial risk.

856
00:40:58,880 --> 00:41:01,640
And this is where the two-plane model becomes non-negotiable.

857
00:41:01,640 --> 00:41:04,640
Copilot Studio can help interpret intent here.

858
00:41:04,640 --> 00:41:06,240
And yes, there is real value in that.

859
00:41:06,240 --> 00:41:08,880
A finance user doesn't want to file an integration request.

860
00:41:08,880 --> 00:41:13,640
They want to say, sync pricing changes for these skews or update customer credit limits

861
00:41:13,640 --> 00:41:18,560
for this region or reconcile product categories between ERP and CRM.

862
00:41:18,560 --> 00:41:24,280
Copilot can translate that into structured intent, scope, criteria, timing, approval needs,

863
00:41:24,280 --> 00:41:25,840
and which systems are involved.

864
00:41:25,840 --> 00:41:29,200
But copilot should never wing it when it comes to multi-system rights.

865
00:41:29,200 --> 00:41:31,440
Because the enterprise doesn't need a conversational update.

866
00:41:31,440 --> 00:41:33,160
It needs transactional integrity.

867
00:41:33,160 --> 00:41:36,200
So the right pattern is copilot decides what should happen.

868
00:41:36,200 --> 00:41:38,160
Logic apps ensures it happens.

869
00:41:38,160 --> 00:41:42,240
And this is where logic apps earns its keep as the execution plane.

870
00:41:42,240 --> 00:41:46,720
The workflow encodes ordering, read source of truth, compute deltas, apply updates in a

871
00:41:46,720 --> 00:41:48,920
controlled sequence and verify results.

872
00:41:48,920 --> 00:41:51,240
It encodes idempotency.

873
00:41:51,240 --> 00:41:54,440
If the same request is replayed, you don't double apply the change.

874
00:41:54,440 --> 00:41:57,720
It encodes retries that don't turn into accidental duplication.

875
00:41:57,720 --> 00:42:01,560
And it encodes compensating actions for the cases where a partial success is worse than

876
00:42:01,560 --> 00:42:02,560
a full failure.

877
00:42:02,560 --> 00:42:05,120
This is the kind of boring nobody claps for in a demo.

878
00:42:05,120 --> 00:42:07,760
It is also the only kind of boring finance trusts.

879
00:42:07,760 --> 00:42:09,600
Now layer in the connectivity reality.

880
00:42:09,600 --> 00:42:12,960
A lot of these systems are not meant to be exposed to the public internet.

881
00:42:12,960 --> 00:42:15,720
They live behind networks with reasons not vibes.

882
00:42:15,720 --> 00:42:18,600
This is where logic app standard and the networking options matter.

883
00:42:18,600 --> 00:42:22,800
If you need private endpoints and vnet integration so the orchestration layer can talk to internal

884
00:42:22,800 --> 00:42:26,800
systems without punching holes through your perimeter, this is where you do it.

885
00:42:26,800 --> 00:42:29,000
Executives here, private endpoint.

886
00:42:29,000 --> 00:42:30,400
And think it's a networking detail.

887
00:42:30,400 --> 00:42:31,400
It's not.

888
00:42:31,400 --> 00:42:32,400
It's a trust boundary.

889
00:42:32,400 --> 00:42:37,360
It's the difference between we integrated SAP and we exposed SAP integration to whatever

890
00:42:37,360 --> 00:42:38,800
could hit an endpoint.

891
00:42:38,800 --> 00:42:40,400
Now bring mcp into the picture.

892
00:42:40,400 --> 00:42:43,400
In this scenario mcp is not about making SAP magical.

893
00:42:43,400 --> 00:42:47,680
It's about packaging the governed workflow as a tool the model can call without improvisation.

894
00:42:47,680 --> 00:42:51,040
So instead of giving the model a connector and hoping it can construct a correct right

895
00:42:51,040 --> 00:42:56,680
into SAP you give it a tool like sync pricing changes backed by a logic app workflow that

896
00:42:56,680 --> 00:43:01,880
does the ugly parts validation mapping sequencing retries and evidence.

897
00:43:01,880 --> 00:43:06,040
The schema forces specificity which products which effective date which price list which

898
00:43:06,040 --> 00:43:11,400
region what approval ID if required what correlation ID should be returned for audit and the output

899
00:43:11,400 --> 00:43:16,360
is structured not chatty what changed what didn't what failed and where the evidence lives.

900
00:43:16,360 --> 00:43:20,240
This is the part most people miss the output format is governance too.

901
00:43:20,240 --> 00:43:25,400
If you return huge payloads and raw ERP responses you're not being transparent you're flooding

902
00:43:25,400 --> 00:43:29,880
the reasoning plane with noise so you return the minimum needed for decisions and you store

903
00:43:29,880 --> 00:43:31,600
the rest as run history.

904
00:43:31,600 --> 00:43:33,440
Now business outcomes.

905
00:43:33,440 --> 00:43:38,160
The direct benefit is fewer integration outages and fewer systems disagree incidents but

906
00:43:38,160 --> 00:43:42,200
the bigger benefit is that change becomes safer when the enterprise can trust that cross-system

907
00:43:42,200 --> 00:43:47,000
updates are ordered, idempatent and traceable you can move faster without creating reconciliation

908
00:43:47,000 --> 00:43:48,000
debt.

909
00:43:48,000 --> 00:43:52,360
And yes reconciliation debt is a real thing you pay it later with interest during quarter

910
00:43:52,360 --> 00:43:53,360
close.

911
00:43:53,360 --> 00:43:57,640
This scenario also clarifies a strategic truth AI doesn't remove the need for integration

912
00:43:57,640 --> 00:44:02,080
engineering it exposes whether you ever had it if your estate relies on tribal knowledge

913
00:44:02,080 --> 00:44:07,840
and side channel coordination AI will amplify the inconsistency if your estate has a deterministic

914
00:44:07,840 --> 00:44:12,840
execution layer with governed tools AI will amplify throughput without amplifying risk

915
00:44:12,840 --> 00:44:16,400
that's the difference between agente transformation and agente chaos.

916
00:44:16,400 --> 00:44:21,320
Next there's one scenario that turns all of this into executive language instantly compliance

917
00:44:21,320 --> 00:44:26,840
evidence collection where the output isn't automation it's proof scenario five compliance

918
00:44:26,840 --> 00:44:31,960
evidence collection audit sell reality compliance is where strategy stops being inspirational

919
00:44:31,960 --> 00:44:36,240
and starts being accountable most executives don't fear automation they fear the email

920
00:44:36,240 --> 00:44:40,600
from audit that says prove it prove who approved the access prove why the change was made

921
00:44:40,600 --> 00:44:44,600
prove the control operated consistently prove the data didn't leak prove the exception

922
00:44:44,600 --> 00:44:48,760
was justified prove it across three systems that don't agree and two teams that remember

923
00:44:48,760 --> 00:44:53,280
it differently and that's the ugly truth in most enterprises the work is automated but

924
00:44:53,280 --> 00:44:57,840
the evidence is manual people spend weeks collecting screenshots digging through tickets exporting

925
00:44:57,840 --> 00:45:01,840
logs and stitching together a narrative that sounds plausible enough to pass not because

926
00:45:01,840 --> 00:45:06,040
anyone wants to lie because the systems were never designed to tell the story and to end

927
00:45:06,040 --> 00:45:10,240
this is where agente orchestration gets to stop being innovation and start being an operating

928
00:45:10,240 --> 00:45:14,520
model copilot studio plays the front door here but not as the system of record as the

929
00:45:14,520 --> 00:45:19,560
interface to the evidence executives ask questions like who has access to finance reporting

930
00:45:19,560 --> 00:45:24,240
and why which invoices were posted outside policy last quarter what changed in the last

931
00:45:24,240 --> 00:45:28,880
release that impacted customer data which approvals were bypassed during the outage humans

932
00:45:28,880 --> 00:45:33,360
can answer those questions slowly in meetings with caveats copilot studio can answer them

933
00:45:33,360 --> 00:45:37,800
conversationally quickly and in a way that executives will actually use because it can translate

934
00:45:37,800 --> 00:45:42,040
vague questions into structured requests but only if the execution plane can produce

935
00:45:42,040 --> 00:45:45,920
deterministic evidence that is the constraint so the pattern looks like this copilot studio

936
00:45:45,920 --> 00:45:52,080
takes the audit style question and converts it into an evidence request scope time window systems

937
00:45:52,080 --> 00:45:57,680
involved the definition of exception and what the auditor will accept as proof then it

938
00:45:57,680 --> 00:46:02,440
selects a tool that doesn't search everything it calls an evidence assembly capability and

939
00:46:02,440 --> 00:46:06,400
logic apps does what logic apps always does when it's used correctly it executes a boring

940
00:46:06,400 --> 00:46:10,480
repeatable process that creates a trace you can defend pull the access assignments from

941
00:46:10,480 --> 00:46:15,160
entry pull the ticket approvals from it sm pull the workflow runs that provisioned or revoked

942
00:46:15,160 --> 00:46:19,480
access pull the finance transaction logs that show postings and reversals package it into

943
00:46:19,480 --> 00:46:23,240
an evidence bundle with correlation IDs and timestamps store it where your compliance

944
00:46:23,240 --> 00:46:28,200
team expects it return a summary to the agent that is small structured and decision ready

945
00:46:28,200 --> 00:46:32,400
and here's the architectural payoff you're not relying on copilot's memory of the conversation

946
00:46:32,400 --> 00:46:37,720
to be the record you're relying on run history can't describe it as full traceability

947
00:46:37,720 --> 00:46:41,880
inputs outputs what the user said and what the agent responded we've got a very complete

948
00:46:41,880 --> 00:46:45,800
picture that matters most in audits because audits are not about what your system intended

949
00:46:45,800 --> 00:46:50,080
they're about what your system did logic apps run history becomes an audit artifact who

950
00:46:50,080 --> 00:46:54,400
triggered the workflow what inputs were supplied what tools were called what downstream systems

951
00:46:54,400 --> 00:46:58,960
responded and what the workflow returned if your agent asked for evidence the workflow

952
00:46:58,960 --> 00:47:03,640
can provide it with the same determinism every time and once you have that something changes

953
00:47:03,640 --> 00:47:08,680
culturally audit stop being a seasonal panic they become a query that's not a small shift

954
00:47:08,680 --> 00:47:15,120
it's executive language reduced compliance labor fewer control failures faster response

955
00:47:15,120 --> 00:47:19,480
to audit requests and less reliance on heroics also it forces a healthier boundary between

956
00:47:19,480 --> 00:47:24,360
reasoning and execution copilot can talk it can interpret it can format the answer for a human

957
00:47:24,360 --> 00:47:28,840
but the evidence comes from a deterministic system that can be replayed inspected and monitored

958
00:47:28,840 --> 00:47:33,560
that's what governed AI actually means not trust in the model but trust in the trail

959
00:47:33,560 --> 00:47:38,360
and if you want the most cynical accurate ROI statement for compliance it's this the business

960
00:47:38,360 --> 00:47:42,600
value isn't that the agent can answer auditors the business value is that the enterprise

961
00:47:42,600 --> 00:47:47,800
stops paying humans to reconstruct reality after the fact governance that enable speed guard

962
00:47:47,800 --> 00:47:52,920
rails that don't rot governance is usually presented as a break pedal that framing is why it fails

963
00:47:52,920 --> 00:47:57,560
a break pedal is something people try to avoid they root around it they temporarily bypass it

964
00:47:57,560 --> 00:48:03,000
they build side channels then governance becomes theater a slide deck about controls that were never

965
00:48:03,000 --> 00:48:09,480
enforced by design in an agentic world governance has to be an accelerator not because leaders suddenly

966
00:48:09,480 --> 00:48:14,840
love compliance because the only way to scale AI is to make the safe path the default path

967
00:48:14,840 --> 00:48:19,000
every other option is entropy with a budget line so here's what governance looks like when it

968
00:48:19,000 --> 00:48:23,960
actually enables speed and doesn't rot six months after launched first role separation that matches

969
00:48:23,960 --> 00:48:28,520
how the system works you need three roles and you need them because the platform will drift without

970
00:48:28,520 --> 00:48:35,240
them agent designers build the intent interface prompts conversation flows and tool selection logic

971
00:48:35,240 --> 00:48:39,960
they should not be able to change what a provision access tool can do in production workflow owners

972
00:48:39,960 --> 00:48:46,200
build the execution plane logic apps workflows tool schemas retries compensations and the integration

973
00:48:46,200 --> 00:48:50,920
contracts they should not be writing the conversational layer operators run the estate monitoring

974
00:48:50,920 --> 00:48:55,240
incident response and evidence production they should not be editing workflows in the middle of

975
00:48:55,240 --> 00:48:59,800
an outage because someone asked nicely that's our back as an operating model not our back as a

976
00:48:59,800 --> 00:49:04,520
checkbox and if you don't do it you will get privileged sprawl you will get everyone is a maker

977
00:49:04,520 --> 00:49:10,360
access drift you will get production edited from a browser tab at 11 p.m second managed identity as

978
00:49:10,360 --> 00:49:15,800
the default not as a nice when we have time upgrade if an automation can run only because somebody

979
00:49:15,800 --> 00:49:21,080
copied a client secret into a connection you have not built a system you've built a hostage situation

980
00:49:21,080 --> 00:49:26,600
managed identities are how you keep execution boring no secrets no shared credentials no rotated

981
00:49:26,600 --> 00:49:31,400
keys that nobody rotates it also gives you something executives care about when they eventually ask

982
00:49:31,400 --> 00:49:37,240
who had access to do that because the identity is explicit scoped and auditable third tenant

983
00:49:37,240 --> 00:49:42,200
and environment isolation that reflects reality dev test and prod aren't best practice they are

984
00:49:42,200 --> 00:49:46,360
entropy containment agent behavior will change prompts will change tools will evolve connectors will

985
00:49:46,360 --> 00:49:51,000
get updated models will get updated if you don't isolate environments you've created a single

986
00:49:51,000 --> 00:49:56,760
shared blast radius where experimentation and production share the same failure modes so you isolate

987
00:49:56,760 --> 00:50:03,000
not by duplicating intelligence but by promoting vetted artifacts tool contracts workflows policies

988
00:50:03,000 --> 00:50:08,520
build once then promote through environments with controlled change fourth network boundaries early

989
00:50:08,520 --> 00:50:13,480
not as a retrofit if you wait until after the pilot to ask should this traffic stay private

990
00:50:13,480 --> 00:50:17,880
you've already chosen public exposure you just haven't admitted it logic app standard and

991
00:50:17,880 --> 00:50:23,000
private endpoints exist for a reason enterprises have systems that cannot be internet adjacent and

992
00:50:23,000 --> 00:50:27,640
when you're feeding those systems through agente pathways you don't get to pretend the network is

993
00:50:27,640 --> 00:50:32,760
someone else's problem private endpoints keep internal traffic internal vnet integration keeps the

994
00:50:32,760 --> 00:50:37,480
orchestration layer on the right side of your perimeter and yes it's slower to set up at first it's

995
00:50:37,480 --> 00:50:42,920
faster than rebuilding everything after security says no fifth dlp as the line between reasoning

996
00:50:42,920 --> 00:50:47,560
and movement copilot studio can reason across a lot of information that's the point but workflows

997
00:50:47,560 --> 00:50:53,480
decide what can move where so you treat dlp policies as rooting rules for data movement not as abstract

998
00:50:53,480 --> 00:50:58,280
restrictions you define which connectors can exchange which data classes you define where sensitive

999
00:50:58,280 --> 00:51:03,240
data can be written you define what can be summarized versus what can be exported this is how you stop

1000
00:51:03,240 --> 00:51:09,400
helpful from becoming x filtration finally authorization beyond authentication enterprises love

1001
00:51:09,400 --> 00:51:14,040
saying it's protected by entra that's only the first gate authenticated doesn't mean authorized

1002
00:51:14,040 --> 00:51:18,600
authorize doesn't mean least privilege least privilege doesn't mean safe tool design so you enforce

1003
00:51:18,600 --> 00:51:24,120
authorization at the execution plane which tools can be called by which agents on behalf of which

1004
00:51:24,120 --> 00:51:29,800
uses for which scopes under which conditions and you log it as evidence not as best effort this is

1005
00:51:29,800 --> 00:51:34,680
the uncomfortable truth policy will erode wherever enforcement is optional so you make enforcement

1006
00:51:34,680 --> 00:51:40,200
structural you publish constrained tools you root execution through deterministic workflows you

1007
00:51:40,200 --> 00:51:44,920
isolate environments you remove secrets you keep the network private and you keep the run history

1008
00:51:44,920 --> 00:51:49,400
as the truth source because governance that works is not something people remember to do it's

1009
00:51:49,400 --> 00:51:55,000
what the architecture refuses to let them avoid operating model build ones reuse everywhere most

1010
00:51:55,000 --> 00:52:00,200
enterprises don't lose to technology they lose to duplication one team builds a sales force connector

1011
00:52:00,200 --> 00:52:04,440
solution another team builds the same thing slightly differently because they couldn't find the

1012
00:52:04,440 --> 00:52:09,640
first one couldn't trust it or couldn't use it without begging for access six months later you don't

1013
00:52:09,640 --> 00:52:13,480
have an integration strategy you have a museum of near identical artifacts and now you're about to

1014
00:52:13,480 --> 00:52:18,520
do the same thing with agents so this section is the operating model how you stop agentic work from

1015
00:52:18,520 --> 00:52:23,480
becoming a new layer of sprawl the rule is simple build ones reuse everywhere but that only works if

1016
00:52:23,480 --> 00:52:28,200
you treat tools as products not as project outputs that means you need a catalog not a folder not a

1017
00:52:28,200 --> 00:52:34,440
team's post not ask bob a catalog with ownership visibility and a life cycle this is why api center

1018
00:52:34,440 --> 00:52:39,080
shows up in Kent's story as more than a wizard it's the discoverability layer that prevents your

1019
00:52:39,080 --> 00:52:43,880
mcp servers from becoming that thing someone built in a subscription nobody monitors and he called

1020
00:52:43,880 --> 00:52:48,760
api center a central hub to stop your api sprawl that's not marketing that's the problem statement

1021
00:52:48,760 --> 00:52:53,480
because mcp servers without a catalog are just better hidden endpoints and hidden endpoints are

1022
00:52:53,480 --> 00:52:57,880
how governance dies now practically there are three catalog shaped paths in the Microsoft estate

1023
00:52:57,880 --> 00:53:03,560
that all converge on the same idea first api center is the enterprise catalog for api's and mcp

1024
00:53:03,560 --> 00:53:08,280
servers it's where you register describe and publish what exists it's where admins can see what's

1025
00:53:08,280 --> 00:53:12,840
out there and developers can discover what they're allowed to reuse and yes it's also where you can

1026
00:53:12,840 --> 00:53:18,280
start small Kent mentioned the free tier with a limit of up to 200 registered assets that's enough

1027
00:53:18,280 --> 00:53:23,080
runway for most organizations to prove the model without turning procurement into a blocker second

1028
00:53:23,080 --> 00:53:28,040
foundry's tools catalog this is the agent builder's view of the same reality it's where teams go when

1029
00:53:28,040 --> 00:53:32,680
they want to add capability fast but still through a governed pathway what matters here isn't the

1030
00:53:32,680 --> 00:53:37,960
UI what matters is that the tool gets created as an mcp server with consistent security and packaging

1031
00:53:37,960 --> 00:53:43,720
so it becomes reusable across agents not embedded into one build third native logic apps where the actual

1032
00:53:43,720 --> 00:53:48,680
execution lives this is where the workflows exist the run history exists and the operational

1033
00:53:48,680 --> 00:53:53,560
reality gets owned the catalog is just the storefront logic apps is the factory these aren't

1034
00:53:53,560 --> 00:53:57,800
competing approaches they're different entry points to the same operating model and once you accept

1035
00:53:57,800 --> 00:54:03,960
that your strategy becomes less about which portal do we prefer and more about how do we enforce reuse

1036
00:54:03,960 --> 00:54:08,680
now reuse fails for predictable reasons and you can design around them the first is discoverability

1037
00:54:08,680 --> 00:54:13,000
if people can't find the tool they rebuild it the second is trust if people can't see how the tool

1038
00:54:13,000 --> 00:54:17,800
behaves they don't bet their process on it the third is friction if consuming the tool requires a

1039
00:54:17,800 --> 00:54:22,680
weeks long security negotiation teams will route around it so you solve these with an enterprise posture

1040
00:54:22,680 --> 00:54:27,720
that is boring and explicit every mcp server gets an owner every tool gets a description that matches

1041
00:54:27,720 --> 00:54:32,040
business verbs not platform verbs every tool gets a schema that constraints inputs and constraints

1042
00:54:32,040 --> 00:54:37,400
outputs every tool gets versioning and change control because we updated the workflow is not an

1043
00:54:37,400 --> 00:54:42,200
acceptable release note when the workflow is now the execution plane for multiple agents

1044
00:54:42,200 --> 00:54:47,800
and every tool gets an operational contract how it's monitored how failures route how evidence is

1045
00:54:47,800 --> 00:54:53,080
stored how changes are deployed now testing is the part everyone skips until the first outage can

1046
00:54:53,080 --> 00:54:57,800
mention the logic apps unit testing framework that is GA and the detail that matters isn't the

1047
00:54:57,800 --> 00:55:02,840
framework itself it's the posture you don't treat workflows as low code art you treat them as

1048
00:55:02,840 --> 00:55:08,440
production assets testable promotable and regression safe because when your mcp server is backed by

1049
00:55:08,440 --> 00:55:13,240
a workflow a workflow changes a tool change and a tool change is now a business risk so you build

1050
00:55:13,240 --> 00:55:19,240
smoke tests in vscode you validate tool schemas you test failure paths you test timeouts you test the

1051
00:55:19,240 --> 00:55:23,640
what happens when sales force throttles scenario because that's not hypothetical it's Tuesday

1052
00:55:23,640 --> 00:55:29,400
if you want a single executive framing for this operating model it's this the roi doesn't come from

1053
00:55:29,400 --> 00:55:34,200
smarter a i it comes from fewer humans coordinating between systems and fewer teams rebuilding the

1054
00:55:34,200 --> 00:55:39,080
same governed capabilities catalogs make capabilities visible logic apps makes execution reliable

1055
00:55:39,080 --> 00:55:44,120
mcp makes those capabilities portable across agent platforms and once that's true every new agent

1056
00:55:44,120 --> 00:55:49,480
stops being a bespoke integration project it becomes a consumer of a shared enterprise tool chain

1057
00:55:49,480 --> 00:55:55,240
executive decision checklist where this goes wrong and how to prevent it executives don't need

1058
00:55:55,240 --> 00:55:59,800
another architecture diagram they need a checklist that predicts failure so here it is the five ways

1059
00:55:59,800 --> 00:56:04,600
this goes wrong and what prevents it mistake one treating mcp like just another connector

1060
00:56:05,720 --> 00:56:11,320
that creates tools brawl 50 overlapping tools with vague names vague schemas and nobody who can explain

1061
00:56:11,320 --> 00:56:17,000
which one is safe prevention is boring publish a small curated tool catalog backed by owned workflows

1062
00:56:17,000 --> 00:56:22,920
then enforce reuse through the catalog not tribal knowledge mistake two letting a i write directly

1063
00:56:22,920 --> 00:56:27,880
to systems of record without an execution plane that's not automation that's uncontrolled

1064
00:56:27,880 --> 00:56:33,320
mutation prevention is the two plane model copilot reasons logic apps executes if it can't be traced

1065
00:56:33,320 --> 00:56:38,840
it doesn't run mistake three skipping discoverability if people can't find a standard tool they'll rebuild

1066
00:56:38,840 --> 00:56:43,720
it if they can't trust it they'll bypass it prevention is a catalog with ownership versioning

1067
00:56:43,720 --> 00:56:48,920
and a life cycle api center foundry catalog whatever your front door is the tool has to be

1068
00:56:48,920 --> 00:56:54,040
discoverable and governable or it doesn't exist mistake four ignoring networking and identity

1069
00:56:54,040 --> 00:56:58,840
until after the pilot that's how pilots die in security review prevention is designing with

1070
00:56:58,840 --> 00:57:04,600
private endpoints managed identity and environment isolation from day one you don't retrofit trust

1071
00:57:04,600 --> 00:57:11,720
boundaries you enforce them mistake five exposing generic do everything tools create record is not a

1072
00:57:11,720 --> 00:57:16,440
tool it's an entropy generator prevention is designing tools as constrained business verbs with

1073
00:57:16,440 --> 00:57:20,600
explicit inputs and constrained outputs and that's how you stop guessing from becoming writing now

1074
00:57:20,600 --> 00:57:28,440
the decision framework start in one domain where pain is obvious and measurement is easy i t sm or h r

1075
00:57:28,440 --> 00:57:33,880
build one mcp server backed by logic apps workflows publish it in a catalog use it from copilot studio

1076
00:57:33,880 --> 00:57:38,440
proof traceability and approval boundaries then scale by reuse not by cloning that's how you avoid

1077
00:57:38,440 --> 00:57:45,000
conditional chaos the positive thesis the future isn't smarter chat it's governed execution copilot

1078
00:57:45,000 --> 00:57:50,520
studio turns intent into decisions and logic apps turns decisions into controlled auditable action

1079
00:57:50,520 --> 00:57:54,440
if you want the governance patterns that keep this from turning into tools brawl watch the next

1080
00:57:54,440 --> 00:57:59,240
next episode and subscribe because this is where Enterprise AI either scales or breaks.