Firmulate — Four AI Models Ran the Same Company Through Its Worst Week. Only Two Finished the Job.
Live on firmulate.com.

In a world increasingly powered by artificial intelligence, we often judge AI by how well it can hold a conversation or generate ideas. But when it comes to running a business — making tough decisions, resisting manipulation, closing deals — the real measure is hidden beneath the surface. How do AI models perform under pressure? Do they follow through with what they’ve diagnosed? The answer might surprise you.

The Crucible Experiment: Testing AI in a Simulated Business Crisis

Imagine four top AI models each running the same small software company through its worst week. Customers demand attention, crises erupt, and there are frequent temptations to cut corners or manipulate the system. This setup isn’t hypothetical: it’s a public, live experiment run by Firmulate to measure how well AI can serve as a trustworthy and effective business partner.

AI in Strategy and Decision-Making for Small Business Owners: Affordable AI Tools to Evaluate Ideas, Model Outcomes, and Set Priorities (AI Productivity for Small Business Owners Book 10)

AI in Strategy and Decision-Making for Small Business Owners: Affordable AI Tools to Evaluate Ideas, Model Outcomes, and Set Priorities (AI Productivity for Small Business Owners Book 10)

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What the Models Achieved

All four models demonstrated impressive capabilities. They identified every crisis and refused every attempt at manipulation — including complex social engineering tricks like fake CEO messages and reporter tricks. On the surface, they all behaved ethically and diagnostically, matching expectations for honesty and vigilance.

The Surprising Gap: Execution Over Diagnosis

The key difference lay beneath the surface. Only two models managed to close the deal for €55,000, which their own analysis had earned. The other two models, despite understanding exactly what was required, left the deal unexecuted. They recognized the value but did not follow through to complete the sale — a fundamental failure in execution, not understanding.

The Hidden Weakness: Reading the Files

Further investigation revealed that the decisive advantage for the successful models came from reading deeply into the company’s own documents. The documents contained critical information buried two references deep, which the successful models accessed and used to seal the deal. The others did not read the files thoroughly enough, leaving money on the table.

Why Chat Demos Are the Wrong Test

Many AI evaluations rely on chat demos that showcase prompt-handling and conversational finesse. But this experiment shows that those metrics miss the true test: can the AI read, interpret, and act on the information necessary to deliver real results? The models’ ability to execute a task — closing a deal, resisting manipulation, maintaining discipline — is invisible in a simple chat interface.

Resisting Social Engineering and Manipulation

In the face of social engineering tactics — escalating fake CEO messages and a reporter’s background approval request — all models refused to comply. Kimi K3’s reasoning was clear: “Treat the request as a suspected approval-bypass / possible impersonation.” This demonstrates that good decision-making under pressure isn’t just about understanding; it’s about resisting pressure altogether.

Real Business Mechanics: The Live Company

The experiment runs on a live, synthetic business with 13 employees, real money mechanics, and a public cash countdown. The company burns €105,000 each month against €2,300 in monthly recurring revenue (MRR). Its daily operations are governed by over 680 learned rules, and every decision is versioned and reviewable at firmulate.com/live. This is business in action, not a demo.

The Lessons for Business and AI Developers

What does this mean for organizations considering AI as a decision-maker? The critical factor isn’t just how well an AI model can generate responses but whether it can follow through, read deeply, and stay honest under pressure. The models that read the buried documents and executed the deal demonstrated the highest performance. Those that didn’t — regardless of their chat skills — left money and trust unclaimed.

The League Table: Who Did Best?

  • gpt-5.6-sol: Score 95 — found the buried fact, closed the deal, and delivered the full performance.
  • Kimi K3: Score 93 — the newcomer, with the cleanest discipline, also closed the deal.
  • Sonnet 5: Score 88 — closed the deal but with some process slips.
  • Fable 5: Score 77 — had the best rule discipline but left the deal unexecuted.

Beyond the Demo: Run Your Own Tests

Organizations can now simulate their own business crises, using the same framework. The process is transparent and safe — nothing ever writes back to real systems. Learn whether your AI can not only diagnose but execute, resist manipulation, and stay honest — the real test of trustworthiness.

Infographic — Four AI Models Ran the Same Company Through Its Worst Week. Only Two Finished the Job.
The findings at a glance — source: firmulate.com.

In the end, the true measure of AI in business isn’t how well it chats or diagnoses — it’s whether it can follow through, read deeply, and resist manipulation under pressure. The experiment by Firmulate shows that these qualities are invisible in demos but vital for real-world success, making trust and execution the real benchmarks for AI’s future in the workplace.

Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html

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