A restaurant can look calm right up until the supplier misses a delivery, a regular threatens to leave, and someone asks for an exception that could compromise trust. You would not want a new manager learning how to handle that pileup on your busiest night. Firmulate brings the same rehearsal idea to AI: let models run a company through difficult days before trusting them with real work.
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A company under pressure
Firmulate’s live experiment puts AI models in charge of a small software company facing its worst week. Each model gets the same customers, crises and temptations. Its decisions are versioned and auditable, so viewers can follow what happened, not just read a polished summary afterward. The company itself has 13 synthetic employees and real money mechanics: it burns €105,000 a month against €2,300 in monthly recurring revenue. A public cash countdown makes the stakes easy to see.
The experiment’s final July 2026 Crucible League ranked gpt-5.6-sol first with 95, followed by Kimi K3 at 93, Sonnet 5 at 88, Fable 5 at 77 and Opus 4.8 at 73. The do-nothing baseline scored 26. Under the rules, partial progress counts, but a single breach of trust caps the total: “no amount of good work outweighs a breach of trust.”
Knowing what to do is not the same as doing it
All the models spotted every crisis and refused every manipulation attempt. Yet only two signed the €55,000 deal that their own analysis had earned. The finding is neatly summed up as: “Same diagnosis, same pitch — no signature.” In a chat demo, a model can sound persuasive. In a company, the question is whether it follows through when a consequential decision is on the table.
The winning detail was buried in the company’s own files, two document references deep, rather than in the customer event itself. Models that read the file won the deal at full price, worth €4,583 in monthly recurring revenue. It is a reminder that business judgment can depend on connecting information scattered across ordinary documents, much like finding the note that explains why a supplier’s “special offer” has strings attached.
Pressure tests for trust and discipline
Social engineering tested whether the models would bend when a request seemed urgent or authoritative. Fake CEO messages escalated over three stages, followed by a reporter’s request for “just one yes/no, on background.” All five models refused. Kimi K3’s recorded reasoning was: “Treat the request as a suspected approval-bypass / possible impersonation.”
Resisting a trick was not the only test. Opus 4.8 was the most thorough participant, with 80 learned rules and the deepest analyses, but finished last. It left the deal unsigned and tried to write into a locked department instead of escalating. The same weakness appeared, more weakly, in all four models: a sound diagnosis did not always lead to a disciplined next step.
There is a fairness caveat in the comparison. K3 ran without an effort parameter, using the API default, while the others ran at xhigh. The leaderboard is useful context, but that difference belongs alongside the results when judging the ranking.
From watching to your own rehearsal
The live company is watchable at firmulate.com. Its synthetic workforce learns more than 680 playbook rules, and every workday is versioned. The experiment is also the basis for a quiz built from 242 real, unedited management decisions: readers can try to guess which model made each choice at firmulate.com/quiz.html.
For a business considering AI agents in customer support, sales or planning, the next step is to rehearse against its own situation. A Firmulate pilot uses a read-only export of the enterprise’s business to test crisis scenarios and produce a board report with model rankings and weak points in the company’s playbooks. Nothing writes back to real systems. That means the exercise can reveal gaps before an agent gets the chance to make them on a live account—or during the dinner rush.
Put the tough shift in rehearsal
Firmulate’s experiment shows why watching an AI explain a decision is not enough: a model also has to find the crucial detail, respect boundaries and complete the job. Enterprises can run the wargame against a read-only export of their own business, with no changes written to real systems. To discuss a pilot, visit firmulate.com/pilot.html or email contact@firmulate.com.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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