Why Your Platform is Rotting from the Inside

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It’s O347 UTC. Most of the IT team is asleep, but somewhere in the cloud logs a pattern is forming.

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It starts small, three new SharePoint lists named “Test” created within four minutes.

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Then a sudden spike in permission changes without a ticket.

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Finally, a series of power automate flows fail concurrently.

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And the phone doesn’t ring. That’s the scary part. The CIO doesn’t get a call because the system isn’t technically down.

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The server lights are still green, but if you look closely at that pattern, what you’re seeing isn’t an outage. It’s entropy.

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Entropy. That gradual decline into disorder.

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It feels like we focus so much on the loud failures, the ransomware, the DDoS attacks,

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that we ignore this quiet rot. We’re talking about the death by a thousand cuts in the Microsoft 365 ecosystem today, aren’t we?

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Exactly. We are talking about how platform systems fail quietly long before they fail loudly

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and more importantly, how to stop that drift with discipline instead of heroics.

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Because right now most organizations are running on heroics.

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They have that one power platform guy who fixes the flow when it breaks at midnight.

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That’s not a strategy, that’s a liability.

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So let’s break down this entropy.

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The source material we’re looking at today describes it as a compounding instability.

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It starts with the substrate itself. SharePoint.

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Right, SharePoint. The Swiss Army knife that everyone tries to use as a hammer,

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a saw and a relational database all at once.

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The core problem is that SharePoint is a collaboration substrate.

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It is designed for documents and lists of data that humans read.

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But people try to treat it like SQL Server.

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I’ve seen this a hundred times.

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You get a request for a simple tracker.

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And suddenly you have a list with 50 columns, five different look-up chains,

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and a permission structure that requires a PhD to understand.

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And that’s where the rot starts.

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The document calls it schema discipline.

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It sounds boring, but it’s critical.

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For example, naming lists.

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You see lists named Genstrial Tracker or Project X-Temp.

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That’s fine for a sandbox, but in production?

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No.

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Name the list after the business noun.

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It’s an incident, not Genstacker.

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And technical debt accumulates in the column names too, right?

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You name a column status today, then change the display name to current state.

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But the API still sees status.

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Then you delete it and make status too.

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Status too. Status final. Status real.

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It’s a nightmare for anyone trying to build an app on top of it.

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The rule is simple.

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Internal names never change.

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Labels are for the user interface, not the API.

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If you don’t enforce this,

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you’re building a skyscraper on a swamp.

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And then there’s the issue of relationships.

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Oh, the dreaded look-up column?

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Look-ups are seductive.

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They feel like a relational join.

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But SharePoint isn’t a relational database.

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The guidance here is strict.

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One look-up per critical view.

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Maybe two if you’re lucky.

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If you are trying to do multi-hop relationships,

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like filtering a list based on a look-up that looks up another list,

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you need to stop.

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So where do you go?

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If SharePoint can’t handle that complexity,

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do you just give up?

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You move the data.

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That’s a dataverse conversation or a SQL conversation.

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If you need transactional integrity and complex joins,

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you’re abusing SharePoint.

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And the system will punish you for it.

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Not today, maybe not tomorrow,

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but eventually, a query will hit a threshold.

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Delegation will break and your app will show blank screens.

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Speaking of breaking things,

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let’s talk about permissions.

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This is a huge pain point.

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The item-level permission trap.

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It’s the classic I want only the creator to see their own items request.

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It sounds reasonable, but technically, it’s a treadmill.

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If you break inheritance on every single item in a list of 50,000 items,

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the server has to check the access control list

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for every single row every time a user queries it.

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It destroys performance.

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So the fix is to break inheritance at the site level,

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not the item-level.

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Always, if you need to secure rows differently,

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you need different lists or a different data source.

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And please use groups.

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Never assign permissions to an individual person.

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People leave, groups remain.

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It seems like the theme here is “Stop improvising”,

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which leads us perfectly into the second pillar, “Power Apps”.

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The text describes “Power Apps” as either “deterministic”

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or “KeyOS” with a “Save” button.

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That’s a pretty stark dichotomy.

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It is, but it’s accurate.

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A canvas app feels like a blank canvas.

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You can paint whatever you want.

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That’s the danger.

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A, “deterministic” app means “You the developer control the state”.

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You know exactly what data is loaded

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when it’s submitted and what happens if it fails.

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Versus the “KeyOS” approach,

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which I assume is just throwing controls on a screen

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and hoping the submit form may function works?

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Precisely.

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“KeyOS” is relying on implicit behaviors.

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It’s putting complex logic inside a button’s on-select property

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that patches three different data sources,

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sends an email,

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and navigates to a new screen,

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all without any error handling.

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If the internet blinks in the middle of that,

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your data is corrupted.

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So how do we make it deterministic?

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You centralize your reads and rights.

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Your controls shouldn’t be queering the database directly.

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They should be looking at local collections

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or variables where appropriate,

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and you need to treat submit form as an atomic operation.

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If you use patch,

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you have to handle concurrency.

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Concurrency is a big one.

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Two people editing the same record at the same time.

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If you don’t handle it explicitly,

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the last person to save wins

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and the other person’s work is overwritten without them knowing.

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That’s that quiet failure again.

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The system didn’t crash, but the data is wrong.

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The text also mentions operational discipline in apps,

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logging what the app did,

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not just what it hoped to do.

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That’s the difference between a toy and a tool.

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A professional app generates telemetry.

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User X navigated to screen Y.

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User Z attempted to submit form failed with error code 133.

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If you don’t have that logs,

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you’re debugging with guesses.

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Let’s shift gears to the engine room,

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power automate.

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The description here is vivid.

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Time bombs diffused with protocols.

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Flows are terrifying because they run in the background.

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You can’t see them failing unless you’re looking

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and they fail just like buildings burn.

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Quietly at first, then all at once.

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What’s the number one cause of that fire?

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A lack of defensive design, specifically triggers.

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If you have a flow that triggers on

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when an item is modified,

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and you don’t set a trigger condition,

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that flow runs every single time anyone touches that item,

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even if they just fix a typo.

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So you have thousands of unnecessary runs clogging up your API limits.

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Exactly. You need scope triggers.

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Only run this flow if the status changes to approved,

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that one change can reduce your load by 90%.

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And then there’s concurrency.

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Right.

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By default, power automate tries to run everything in parallel to be helpful.

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Which is a disaster.

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If you are trying to update the same list item or increment a counter,

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you get race conditions,

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you have to set concurrency limits.

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Sometimes you need to force it to run sequentially one at a time

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to ensure data integrity.

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And error handling?

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The try catch pattern isn’t native to the visual designer

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in the same way it is in code, isn’t it?

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You have to build it.

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You create a scope block for your main actions.

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That’s your try.

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And then a parallel block that only runs if the first one fails.

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That’s your catch.

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If you don’t have a catch block that alerts you,

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a flow can fail for weeks.

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And you’ll never know until a user asks,

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“Hey, where’s my approval?”

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That silence is the enemy.

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It seems like the goal of all these protocols is to turn quiet failures

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into loud-contained failures.

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Yes, I want the system to scream at me when something breaks

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so I can fix it immediately.

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I don’t want it to whisper while it corrupts the database for six months.

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Now we can’t talk about the future of this platform

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without talking about AI.

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Copylates, AI Builder.

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Everyone wants to turn them on.

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But the text warns,

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the spike didn’t start with code.

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It started with a PDF.

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AI is the ultimate accelerator.

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If your governance is bad, AI will make it bad faster.

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The danger with AI, specifically large language models or copylates,

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is hallucination and over-access.

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Librarian, not Oracle.

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I liked that line.

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It’s the perfect analogy.

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An Oracle Invents Truth.

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A librarian finds truth that already exists.

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We want our corporate AI to be a librarian.

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It should only answer based on whitelisted knowledge sources.

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If it can’t find the document, it should say,

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“I don’t know, not invent a policy.”

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And how do we enforce that technically?

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You need boundaries.

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For AI Builder processing documents,

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you need a human in the loop for low-confident scores.

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If the AI isn’t 90% sure that invoice is for $500,

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a human needs to review it.

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You don’t just let it write to the ERP.

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And for the chatbots, the copylates?

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Citations are mandatory.

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If the bot gives an answer, it must link to the source document.

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No citation, no output.

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And critically, no direct data mutation.

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You don’t let a chatbot directly edit your SQL database.

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The chatbot should trigger a strictly governed power automate flow

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to make the change.

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The flow is the gatekeeper.

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So the AI is just the interface.

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The governance logic still lives in the rigid,

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deterministic layers we discussed earlier.

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Exactly.

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The AI is the soft fuzzy front end.

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The back end must remain cold, hard, and logical.

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We’ve covered the pillars.

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SharePoint, Apps, Automate, AI.

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But none of this works without what the text calls the “governance spine.”

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The controls that don’t blink.

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This is the unsexy stuff that saves your job.

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DLP, DataLoss Prevention Policies, Environment Strategies.

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You cannot have people building production apps

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in the default environment.

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The default environment is the Wild West.

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It’s where governance goes to die.

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You need a dev test-prote separation.

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You need managed solutions.

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If you are moving raw zip files of unmanaged solutions

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into production, you are asking for trouble.

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And service principles.

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Stop running enterprise flows under Steve’s account.

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Because when Steve wins the lottery in quits,

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the entire accounts payable process shuts down.

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User service principle, a non-human identity.

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So the system relies on the architecture

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and not the employee roster.

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It all comes down to a choice, doesn’t it?

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The conclusion lays it out.

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Alignment or entropy.

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That’s the binary choice.

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There is no middle ground.

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You either enforce structure early,

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which feels restrictive and slows you down initially.

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Or you pay for reconstruction later.

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And reconstruction is always ten times more expensive.

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It’s interesting.

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We started by talking about technical settings.

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Indexed columns, concurrency limits.

255
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But this is really a philosophical stance

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on how technology should be managed.

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It is. It’s about respecting the tool.

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SharePoint, Power Platform, AI.

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These are incredibly powerful tools.

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But they are not magic ones.

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They require a schema.

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They require protocols.

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If you treat them with discipline, they scale.

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If you treat them as a playground,

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they will become a graveyard for your data.

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Everything else is entropy with a friendly UI.

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That’s a haunting thought.

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It should be.

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Because when you log off today, those flows are still running.

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The entropy is still pushing against your walls.

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The question is, did you build the walls strong enough?

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So for our listeners, the call to action is clear.

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Don’t wait for the outage.

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Look for the signals.

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Look for the test lists.

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The failed flows.

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The permission drifts.

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Go check your environments.

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Implement the DLP.

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Separate your dev and prod.

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And for the love of data,

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go index your SharePoint columns.

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Simple, actionable and absolutely critical.

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If you ignore it, well,

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if you ignore it, I’ll be back.

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But next time we won’t be talking about prevention.

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We’ll be talking about disaster recovery.

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On that cheerful note, thank you for listening.

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This has been a deep dive into the mechanics of platform governance.

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Stay disciplined.

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And we’ll catch you in the next episode.

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Goodbye.