Before trusting a new power tool with a fine piece of hardwood, a careful woodworker checks how it handles the cut. Businesses face a similar test with AI: what happens when an agent must respond to a crisis, resist pressure and close a deal? Firmulate puts AI models through that kind of trial inside a watchable simulated company.
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One company, one rough week
In the Firmulate experiment, each frontier model ran the same small software company through its worst week, facing the same customers, crises and temptations. Every decision was versioned and auditable. The final Crucible League, in July 2026, 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. The league counts partial progress, but one breach of trust caps the total: “no amount of good work outweighs a breach of trust.”
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The missing signature
All models spotted every crisis and refused every manipulation attempt. Yet only two signed a €55,000 deal their own analysis had earned. The diagnosis and pitch were there; the signature was not.
The deal hinged on a clue buried two document references deep in the company’s own files, rather than in the customer event. Models that read the file won at full price, worth +€4,583 MRR. It is a practical reminder that a good decision can depend on checking the right paperwork, not just reacting to the loudest signal.
business crisis simulation tools
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Pressure, discipline and the human lesson
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 on-record reasoning was: “Treat the request as a suspected approval-bypass / possible impersonation.”
Opus 4.8 was the most thorough participant, with +80 learned rules and the deepest analyses, yet finished last. It left the close on the table and slipped on discipline, attempting to write into a locked department instead of escalating. A weaker version of that same weakness appeared in all four models.
One fairness detail matters when reading the rankings: Kimi K3 ran without an effort parameter, using the API default, while the others ran at xhigh.
AI decision-making analysis software
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A company you can watch
Firmulate’s live company has 13 synthetic employees and real money mechanics: €105k monthly burn against €2.3k MRR, alongside a public cash countdown. Its playbooks contain 680+ self-learned rules, and every workday is versioned. The experiment is watchable at firmulate.com. A quiz built from 242 real, unedited management decisions lets readers try to guess which model made each choice at firmulate.com/quiz.html.
For businesses, the next step is to test against their own circumstances. A pilot uses a read-only export to create a digital twin, then runs crisis scenarios and produces a board report with model rankings and weak points in the company’s playbooks. Nothing writes back to real systems.
digital twin simulation platform
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Try the wargame against your business
Watching a simulated company reveals the gap between spotting the problem and completing the job. Enterprises can run the same wargame against a read-only export of their own business and examine how models handle its crises and playbooks. To discuss a pilot, visit firmulate.com/pilot.html or contact contact@firmulate.com.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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