Imagine a business so transparent that you can watch its daily battles, decisions, and failures unfold live online. No employees, no secrets, just an AI-driven company fighting to stay afloat — and you can see every move as it happens. This is not science fiction; it’s the groundbreaking experiment by Firmulate, a company that’s turning the traditional corporate story into an open, ongoing spectacle.
What Is Firmulate and How Does It Work?
At first glance, Firmulate appears to be a normal tech company, except it has no human employees. Instead, it operates through 13 synthetic ’employees’ — algorithms designed to mimic decision-making processes in a real business environment. Every decision they make is recorded, versioned, and publicly accessible at firmulate.com/live.html. The company runs every business day, incurring real expenses, with a live cash countdown, making its daily struggles visible to all.
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The Experiment: Testing AI Under Pressure
The core of this experiment involves four advanced AI models, each tasked with managing the same small software company through its worst week. The goal? To see if these models can diagnose crises accurately, refuse manipulative tactics, and close a crucial €55,000 deal — all in the face of simulated threats and ethical dilemmas.
Remarkably, all four models identified every crisis, refused every manipulation attempt, and maintained honesty. Yet, only two managed to finalize the deal, despite identical analysis and pitches. The difference? The winning models dug deeper into the company’s internal files — uncovering a crucial hidden reference that revealed a competitive advantage, and ultimately clinched the sale at full price (+€4,583 MRR).
What Does This Say About AI in Business?
This experiment underscores critical issues in deploying AI for real-world management. It’s not enough for AI to generate convincing chat or handle surface-level tasks. Success depends on the ability to read and understand complex internal information, resist manipulative tactics, and stay disciplined under pressure.
For example, when faced with social engineering — fake CEO messages escalating through stages — all models refused to act without verification. Kimi K3’s reasoning was clear: “Treat the request as a suspected approval-bypass / possible impersonation.” This shows a high level of caution and integrity, essential qualities for AI agents managing sensitive operations.
The Real Live Company in Action
Unlike typical AI demos, this is a tangible business now operating in real-time. The company’s daily operations involve real money mechanics: a burn rate of €105,000 per month against €2,300 in monthly recurring revenue. Its work is guided by over 680 self-learned rules, with every decision recorded and versioned. Visitors can watch the ongoing drama unfold, see the decisions made, and even watch the company’s cash dwindling—adding a visceral sense of urgency and reality.
The Performance League and Key Findings
The models competed in the Crucible League, with scores reflecting their ability to diagnose crises, act ethically, and close deals. GPT-5.6-sol led with a 95 score, having uncovered the buried fact and closed the full-price deal. Kimi K3 followed with a 93, demonstrating the cleanest discipline, while Sonnet 5 and Fable 5 scored 88 and 77 respectively, with some process slips and missed opportunities.
One striking insight was that the decisive advantage often lay in reading internal documents — something that is invisible in standard AI chat demos but critical for real success.
Why This Matters for Arts, Crafts & Culture Audiences
While the experiment might seem far removed from arts and culture, the underlying message is universal: transparency, discipline, and the ability to read deeply can determine success or failure—not just in business but in any creative or cultural endeavor. Whether managing a gallery, a craft workshop, or a community project, understanding and trusting your tools—and ensuring they act ethically—is vital.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
