Discussion on "No Board of Directors Will Ever Accept "The AI Hallucinated": The Blame Deficit in Software Engineering"

Tarek Mostafa · 2026-09-20T00:44:18.635Z

Picture this scenario: It's 9:15 AM on a Monday morning. The payment service collapsed over the weekend, resulting in 4 hours of dropped checkouts and an angry email from the VP of Product. The incide

One thing I'd separate out here: not every "AI hallucinated" incident is actually a blame-deficit problem. A chunk of them are just plain CI failures wearing an AI label — code that would have failed the existing test suite if anyone had run it before merging, agent-written or not. That's not a new accountability problem, it's the old "we skipped a step" problem with a new excuse attached. The genuinely new case is narrower: code that passes every existing check, looks completely reasonable on read, and is still wrong in a way that only shows up under load or in an edge case nobody wrote a test for. That's the one where "who approved this diff" actually matters, because there was nothing mechanical left to catch it. Worth splitting those two before deciding how much process to add — the fix for the first one is just enforcing what already exists.

This is a brilliant distinction, Mihai. "A plain CI failure wearing an AI label" is such a sharp diagnosis—and calling out that lazy excuse is half the battle in engineering hygiene today.

You nailed the exact core of the problem with that second case. When code is syntactically pristine, passes every automated CI gate, and looks completely plausible on read, the mechanical safeguards are exhausted.

At that point, automated pipelines have done all they can do. The only barrier left between that code and a production meltdown is human architectural context—someone who understands distributed state, concurrency bottlenecks, and the unwritten edge cases that lie outside the model's context window.

That second category is precisely where engineering liability and human review become irreplaceable.

Really appreciate you sharing this taxonomy—it makes the conversation much sharper!

Answering your closing question directly, since that's the useful part.

Our policy: the AI's involvement is recorded but never mitigating. Every commit an agent co-wrote carries a co-author trailer, so after an incident we can answer "was this AI-written?" from git rather than from memory. It's a data question, not an excuse.

What actually changed is where the accountability gate sits. It moved from "who wrote this line" to "who approved this diff, and what did they check". The postmortem question isn't "did the AI hallucinate", it's "what was the reviewer relying on when they approved it". Usually the honest answer is that the diff was 400 lines at 6pm - and that's a process failure with a human name on it.

Two things followed from that for us:

We cap what a single review can cover. If an agent produces something too large to actually read, that's the defect, before any of the code is examined.
Incident reviews ask for the verification, not the intention. "It was tested" isn't an answer; "here is the test, and here's why it didn't cover this case" is.

The blast-radius framing in your piece is the one I'd extend: AI-written code hasn't changed the blame chain at all. It's changed the volume of code arriving per reviewer per hour. Accountability was always human. What's newly scarce is review capacity, and most teams haven't priced that in.

This is an absolute masterclass in operational pragmatism, Mythex.

Your point about review capacity being the newly scarce asset hits the exact economic reality most engineering leaders are completely missing right now. When the cost of syntax generation collapses to zero, code volume explodes—but human cognitive bandwidth remains strictly finite. If teams don't price in that review tax, they're just trading cheap keystrokes for expensive 3:00 AM postmortems.

I especially love your rule: "If an agent produces something too large to actually read, that's the defect before any code is examined." That should genuinely be standard industry practice. Rejecting unreviewable synthetic dumps at the gate is how you protect your team's cognitive budget.

And treating AI involvement as an audit trail rather than a liability shield is the only sane policy. An algorithm can co-author a commit, but it can never co-sign operational accountability.

Really appreciate you breaking down these concrete, battle-tested rules—this is the exact kind of engineering rigor the industry needs right now!

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No Board of Directors Will Ever Accept "The AI Hallucinated": The Blame Deficit in Software Engineering

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