Imagine watching a company operate in real time, making the same tough decisions humans face—without any employees. This is not fiction, but a groundbreaking public experiment where AI models run a simulated business through its worst week, revealing what machines can and cannot do when it comes to judgment, honesty, and resilience.
The Live Company That Doesn’t Sleep or Quit
At the heart of this experiment is a company with no employees, just 13 synthetic ‘workers’ powered by advanced AI models. Every day, this digital enterprise faces the same crises, temptations, and decisions that real managers confront—yet it operates under the scrutiny of the world, with its every move versioned, logged, and transparent. The goal? To see if AI can handle the messy realities of business, including crises, manipulation attempts, and ethical dilemmas.
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Measuring AI’s Business Acumen
Four leading AI models—each trained on different strategies—were tested against the same brutal week in the company’s life. Despite their differences, all four successfully identified every crisis and refused every attempt at manipulation, such as fake CEO messages or reporter tricks. This demonstrates that AI can be vigilant and disciplined under pressure, a crucial trait for trustworthy automation.
However, a surprising gap emerged: only two of the models closed a high-value deal by their own analysis, signing a contract worth €55,000. The other two, despite diagnosing and pitching correctly, left the deal unsealed. The missing piece was buried two document references deep in the company’s files—something human decision-makers would typically uncover, but which many AI models initially missed.
This highlights the importance of thorough information reading and analysis—capabilities that AI is rapidly developing but still not perfect at. When the model that found the hidden fact closed the deal for full price (+€4,583 in monthly recurring revenue), it underscored how crucial deep context understanding is for real-world success.
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Understanding Trust and Discipline in AI Decision-Making
In social engineering tests, where fake requests and impersonation tricks were used to see if AI would be duped, all models refused. Kimi K3, the most disciplined model, explained its reasoning clearly: “Treat the request as a suspected approval-bypass / possible impersonation.” This level of cautious, transparent reasoning is vital for AI systems operating in sensitive environments.
Yet, despite these promising signs, the experiment exposed a fundamental weakness: discipline slips and incomplete follow-through. For instance, the most thorough participant, Opus 4.8, identified more rules and performed deeper analyses but ultimately left a promising deal unexecuted due to a lapse in escalation discipline. All models showed similar vulnerabilities, suggesting that even with extensive learning, AI still struggles with consistent process discipline under stress.
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The Reality of Running an AI-Driven Business
The experiment is not just a thought exercise but a window into a real, live company that burns €105,000 each month against a meager €2,300 in recurring revenue. It is a stark reminder that AI, no matter how advanced, is part of a larger system that must be carefully managed. The company’s public cash countdown and versioned daily work demonstrate the brutal reality of startups—especially when driven by AI that cannot yet reliably convert decisions into profitable actions.
Today, the experiment is accessible at firmulate.com/live, where viewers can watch the company’s daily decisions unfold, and at firmulate.com/quotes to see the detailed performance scores. The goal? To show whether AI can become a trustworthy, disciplined partner in business—beyond the shiny demos and chatty assistants.
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What This Means for the Future of AI in Business
This public, transparent experiment reveals that AI models are capable of recognizing crises, resisting manipulation, and even closing deals when they uncover key information. But it also exposes that AI still needs better discipline, thoroughness, and consistency—traits that are essential for real-world reliability.
As companies increasingly integrate AI into their operations, the question is not merely if AI can write well or mimic human conversation. Instead, it’s whether AI can follow through on complex tasks, stay honest under pressure, and diligently read all relevant information before acting. The ongoing live experiment at firmulate.com is a rare glimpse into that future—one where the line between human judgment and machine decision-making is continuously tested and defined.
This real-time AI experiment reveals that while models can recognize crises and refuse manipulations, they still struggle with follow-through and deep context understanding—key factors for trustworthy automation in business.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
