One failed industrial AI pilot, taken apart in public.
Sixty minutes, every month, free. We take a documented industrial AI pilot failure and walk where it actually broke — not the model, but the problem statement, the unsigned baseline, and the acceptance test nobody wrote. You leave with the one-page record that would have caught it.
what it is
A synthetic clean-room case, built from the published failure research — RAND, MIT NANDA, Gartner, S&P Global, with the citations on the slides. Every company, vendor, and number is fabricated for instruction; no real company's data appears here, ever. What's real is the pattern. We walk where the pilot broke, beat by beat.
It named no metric and no segment.
The pilot chased "days to hours" in a segment that was already fast, and could not touch the segment that was genuinely slow. That is not a model failure. It is a problem-definition failure — the #1 documented cause of AI project failure, discoverable in one afternoon of queries nobody ran before signing.
The business case rested on folklore.
"Quotes take about three days" — a sentence, not a measurement. When someone finally pulled the actual records, eleven months in, the real numbers were nothing like the folklore. Nobody had signed a baseline, so nobody could say whether the tool had moved it.
Nobody wrote one.
The contract said "success criteria to be mutually defined during the pilot." They never were. With no written pass/fail line, the pilot ended by fading, not by a decision — and the write-off arrived with nobody in the room able to say whether the thing had worked.
The Go/No-Go Decision Record — one page, yours to keep.
A one-page artifact you can reuse on your own next pilot: ten fields, filled before a dollar or a signature moves. A named sponsor. A measured, signed baseline. A written acceptance test your own team can run. Kill criteria and a spend cap. If the baseline box and the acceptance-test box can't be filled honestly, the answer is No-Go by default — not because the pilot is bad, but because it is unmeasurable. Free, no email wall.
the next session
Session #1 — the $342K quote desk that nobody measured: a fictional $185M industrial manufacturer-distributor spent $342,000 and eleven months on an AI quote-desk pilot, then the CFO killed it at budget review with nobody able to say whether it had worked. We tear it down against the published evidence, then walk the counterfactual — the one page that would have redirected or killed it ten months earlier.
- when Thursday, 2026-08-13, 12:00 ET — 60 minutes, live.
- cost Free. No vendor pitch, no email wall on the take-home.
- where Online (Zoom webinar). Recorded — registrants get the recording whether or not they attend.
- who Operators of $50M–$500M manufacturing, distribution, logistics, and industrial-services businesses deciding on AI spend.
a different failure, every month
Same discipline, a new synthetic case each time — always the second Thursday, always free, always recorded. Every month a different documented failure mode, built the same way: from the published research, clean-room, with the citations on the slides.
- #1
The quote desk nobody measured
A quote/order-intake copilot bought on a demo, deployed into the fast segment, and written off eleven months later against a baseline nobody signed. The problem-definition failure, in full.
- #2
Predictive quality on a packaging line
A vision system for defect detection that dies on unlabeled scrap data and an OEE number nobody trusts. What happens when the baseline itself is folklore.
- #3
Demand forecasting at a distributor
A model that beats the buyer's spreadsheet in the demo and loses in the season it wasn't trained on. Why a good demo is not an acceptance test.
- #4
The maintenance copilot
A CMMS chatbot answering from mis-coded failure records — and quietly laundering the wrong failure mode forward. What AI does to data you already can't trust.
A teardown that sold you something wouldn't be a teardown.
The Pilot Autopsy runs under Tektari's published Verification Charter: no implementation sold, no vendor commissions or referral fees, and its fees never credit toward any other Tektari offer — prices published. There is no pitch beyond one sentence at the close: the paid version of tonight's discipline is a fixed-price Problem-Definition Audit — $12,500, with $2,500 of it invoiced only when your pilot passes its own acceptance test. The teardown itself is free and stays that way.
Save a seat, or see where you stand.
Register for the next Pilot Autopsy on Luma — or take the 20-question Industrial AI Scoreboard first and find out where your operation stands against peer mid-market industrial operators before the next pilot conversation.
Save a seat — Thu Aug 13That doesn't look like an email — try name@company.com