(00:00:00) The Fragility of Power Apps
(00:00:04) The Hidden Dangers of Low-Code Development
(00:00:29) The Anatomy of App Failure
(00:01:09) The Silent Killers of App Performance
(00:02:35) The Cycle of Patching and Drift
(00:04:13) Mapping the App's Dependency Graph
(00:08:13) The Power of Local Truth and Guardrails
(00:13:42) Components and Contracts: Building Scalable Apps
(00:18:18) The Importance of Governance and Testing
(00:22:57) Implementing a Refactor Plan and Governance Template

Your Power App works—until it doesn’t. No error. No warning. Just silence.
Low-code wasn’t sold as “fragile,” but that’s exactly what you get when you copy-paste formulas, skip environments, and bury dependencies where no one can see them. In this episode, we expose why Power Apps fail without telling you, where the fractures hide, and the one local-scope pattern (With) that stops the bleed. By the end, you’ll know how to restructure your screens, components, and ALM so drift disappears and reliability becomes predictable. Section 1 — The Anatomy of Fragility: Why Your App Actually Fails Power Apps don’t break loudly—they degrade quietly. You only notice after users complain, “It just spins.” Common Failure Modes

• Formula Drift: Copy-pasted logic across screens evolves separately and silently diverges.
• No Environment Boundary: Studio “Play” ≠ testing. Dev changes leak into prod instantly.
• Hidden Dependencies: Collections, globals, and shadow connectors impersonating your identity.
• Token Thinking: “It worked once” becomes your QA strategy until a schema rename destroys everything.
• Identity Drift: Permissions become patchwork; app sharing turns into chaos.
• Delegation Traps: Search, In, StartsWith—harmless at 500 rows, catastrophic at 50,000.
• Latency Creep: Dataverse + SharePoint joins push work client-side and burn your performance budget.
• Silent Error Swallowing: Patch failures vanish into thin air; users double-submit and duplicate rows explode.

The Real Pattern Every Power Apps failure is a broken contract:
Screen → Control → Formula → Data → Permission.
When no contract exists, drift fills the vacuum. Section 2 — Forensics: Tracing the Access Paths & Failure Modes You can’t fix an app you can’t see. This section teaches you to run forensic discovery like an engineer—not a guesser. Forensic Steps

• Map critical flows (Submit, Approve, Report).
• Inventory every dependency: tables, connectors, roles, variables, component props.
• Surface invisible state: every Set, UpdateContext, Collect, and App.OnStart cache.
• Diff formulas: normalize and hash to reveal divergence across screens.
• Build the dependency graph: see where trust, data, and identity assumptions connect.
• Rehearse failure: throttle connectors, rename fields, expire tokens, break a flow connection.
• Define your health model: clear red/yellow/green thresholds for your top user paths.
• Instrument telemetry: correlation IDs, durations, outcomes, without PII.

This is where ghosts lose power—because you finally see them. Section 3 — The Fix Starts Local: With() as the Guardrail The turning point.
With() introduces local scope, single truth, named intent, and eliminates formula drift. Why With() Works

• Containment: No global side effects.
• Clarity: Input → Transform → Payload → Output.
• Predictability: One exit path, memoized work, no duplicated logic.
• Performance: Heavy calls cached once, not recalculated per row.
• Safety: Schema coercion and type normalization happen in one place.

Patterns You’ll Learn

• Build query models inside With() blocks
• Construct patch payloads with explicit types
• Route all success/failure through a single result object
• Memoize expensive...