Imagine a company so transparent that you can watch every decision, every crisis, and every failure unfold live — with no employees, just AI models running the show. This is not fiction; it’s the real-time experiment happening now at firmulate.com/live. In a world where AI is often tested in secret, this company exposes its daily struggle to survive, offering a rare window into what it truly takes to manage an artificial workforce.
The Live Company: A Front-Row Seat in AI Management
At the heart of this experiment is a tiny but intense digital company, operating with 13 synthetic employees. These aren’t mere chatbots; they are complex AI agents equipped with over 680 self-learned rules and a track record of versioned decision-making. Every workday, the state of the company is documented and updated, creating a real-time story of survival and strategic decision-making.
What makes this experiment extraordinary is its transparency. Unlike typical AI demos aimed at impressing with clever language or impressive responses, this setup tests AI in the messy, high-stakes environment of running a business. The company faces real crises, from customer issues to internal temptations, with a real cash burn of €105,000 every month against a modest monthly recurring revenue (MRR) of €2,300. It’s a brutal scenario designed to push AI models to their limits.
AI decision-making software for business
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The AI Models: Different Approaches, Same Battlefield
Four frontier language models were each tasked with navigating this volatile business environment. They ran the same week — facing identical crises, customer demands, and ethical dilemmas — to see how they would perform under pressure. The results? All four detected every crisis and refused manipulation attempts. They stayed disciplined, refusing fake CEO messages and impersonation tricks, which five out of five models correctly identified and rejected.
However, the outcome differed significantly in their ability to close deals. Only two models, gpt-5.6-sol and Kimi K3, managed to sign the €55,000 deal their own analysis had pinpointed as the correct move. The others either left money on the table or failed to fully execute their plans. The critical weakness was buried deep within the company’s own files: reading the right documents at the right time was the key to winning the deal — a test of depth and thoroughness that many models failed.
AI business management tools
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The Deep Dive: What Did It Take to Win?
Surprisingly, the models that performed best were not just the most advanced in language capabilities but those that could read and interpret detailed internal data. For example, the model K3 ran without an effort parameter, which meant it operated at default—yet it still managed to close the deal, illustrating that discipline and reading comprehension matter as much as raw power.
Meanwhile, Opus 4.8, the most thorough participant with over 80 rules learned, was the last to leave the table. It left the deal unexecuted after slipping into internal disputes instead of escalating issues — a sign that even the most rule-filled approach can falter under pressure.
AI crisis management platform
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What Does This Mean for AI in Business?
This live experiment is more than a tech showcase; it’s a glimpse into the future of AI management. If AI agents are to be integrated into real-world business systems — CRM, support, forecasting — the critical questions aren’t about how well they generate language or mimic human conversation. Instead, the focus must be on reliability, honesty, and thoroughness under stress.
Watching this company fight for survival highlights the importance of rigorous testing before deployment. Can the AI read the right documents when it matters most? Will it stay honest and disciplined under pressure? Can it deliver measurable, useful work instead of just sounding convincing? These are the questions that matter.
AI deal closing automation
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The Bigger Picture: A Public Experiment in AI Reliability
Unlike traditional corporate experiments shrouded in secrecy and technical jargon, this project is built in public, with every decision, every rule, and every outcome openly available. It’s a clear statement: AI decision-making in critical business roles must be transparent, auditable, and resilient.
To further explore these findings, visitors can participate in quizzes, run simulations with their own data, or simply observe the ongoing live performance at firmulate.com/live. This is AI management in its raw form — a real, unfiltered look at what AI can and cannot do in the high-stakes environment of running a business.
This experiment exposes the limits and potential of AI as a business manager. Success depends not just on language skill but on thoroughness, honesty, and depth of understanding — qualities that are being tested and refined in real time. For anyone interested in the future of AI-driven work, this is a front-row seat to the most transparent and intense trial yet.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
