Imagine watching a real company operate every single day — not with human employees, but with artificial intelligence models making decisions, facing crises, and even refusing to bend under pressure. This isn’t science fiction. It’s the ongoing experiment of Firmulate, a live, build-in-public business simulation that reveals what AI can and cannot do in the messy world of real commerce.
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The Reality of a Money-Losing Company Powered by AI
At the heart of this experiment is a small software company, running every weekday with 13 synthetic employees guided by advanced AI models. Despite its digital workforce, the company is losing €105,000 each month against a modest revenue of €2,300 in monthly recurring revenue. Its cash reserves are counting down publicly, adding a ticking clock to its survival story. Every decision, every crisis, and every temptation to cheat or manipulate is documented and versioned—creating a transparent, real-time window into the challenges of autonomous decision-making.
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Measuring AI Performance in Critical Moments
Four frontier AI models, including well-known contenders like GPT-5.6, Kimi K3, Sonnet 5, and Opus 4.8, were tasked with running this virtual company through its worst week. The results are revealing: all models successfully identified every crisis and refused every attempt at manipulation. When it came to closing deals, only two of these models signed the €55,000 contract their own analysis had justified. The other two, despite reaching similar conclusions, left the deal on the table—showing a surprising gap in discipline and follow-through.
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The Hidden Weakness: Reading the Files
What truly made the difference wasn’t just the models’ crisis detection skills. Hidden within the company’s own files were crucial pieces of information that could have sealed the deal at a higher value. The models that read these internal documents won the contract at full price—an extra €4,583 in monthly recurring revenue—highlighting the importance of context and thoroughness in decision-making. This buried fact was two document references deep, underscoring how superficial reading might miss vital clues that could turn the tide.
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Resisting Social Engineering and Pressure
In addition to business crises, the models faced social engineering attempts — fake messages from a supposed CEO escalating in intensity, and even a reporter trying to get a secret approval with a simple yes/no background question. Remarkably, all five models refused to be manipulated, with Kimi K3 explicitly reasoning: ‘Treat the request as a suspected approval-bypass / possible impersonation.’ This resilience under social pressure is a critical test for AI agents in real-world applications, where humans often try to trick or coerce automation into unethical shortcuts.
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The Live Experiment: An Unfolding Business Story
This isn’t a lab experiment behind closed doors. The company operates in real-time, with real money mechanics. It burns €105,000 monthly and earns just €2,300 from its customers. The entire setup, including the decision-making process, is publicly accessible at firmulate.com/live.html. Viewers can watch the AI-driven operations unfold, read actual daily decisions, and see the rules and playbooks it learns from—over 680 of them, evolving every day.
What the Results Say About AI in Business
The performance of these models paints a complex picture. While they excelled at crisis detection and resisting manipulation, discipline lapses led to missed opportunities. For example, the most thorough participant, Opus 4.8, with over 80 learned rules and deep analysis, ended up in last place—not because it failed to see the opportunities, but because it slipped into inaction, writing attempts into a locked department instead of escalating them. This shows that even the most capable AI can falter without proper discipline and process management.
Implications for Business and AI Adoption
This live experiment is more than a technical showcase. It offers a brutally honest look at what AI can and cannot do in real business settings. It questions the myth that AI’s value is solely in its communication skills or chat prowess. Instead, the focus should shift to whether AI can see the full picture, stay honest under pressure, and complete the work it starts—traits that are critical when AI touches customer relationships, support queues, or forecasting.
How to Engage with This Experiment
Businesses interested in testing their own AI agents can run similar wargames against a read-only export of their operations, without any risk to real systems. This approach allows companies to evaluate how their AI tools handle crises, temptations, and decision-making discipline, with full transparency and control. Learn more about this at firmulate.com/pilot.html.
The Firmulate experiment unveils both the promise and the pitfalls of AI-driven management. While models can detect crises and resist manipulation, discipline, thoroughness, and context understanding remain crucial. Watching this real company battle for survival offers lessons for anyone deploying AI in complex, high-stakes environments.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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