
Imagine a company where every decision, every crisis, and every mistake is played out in public, live and unfiltered. For those grappling with the unpredictability of mental health and the chaos of human decision-making, this is a mirror — a window into the raw, unedited process of navigating pressure and uncertainty. Welcome to a groundbreaking experiment: a software company run entirely by AI models, openly fighting for survival every single day, with no safety nets or human oversight.
The Raw Reality of a Digital Company in Crisis
At first glance, it might seem like a high-tech stunt, but this is a real-world experiment that underscores a crucial question: Can artificial intelligence handle complex, high-stakes situations that would challenge even seasoned managers? The company in question operates with 13 synthetic employees, all driven by AI models that simulate human decision-making. It’s real money on the line — burning €105,000 each month against a revenue of just €2,300. The company’s cash reserves are counting down publicly, visible at firmulate.com/live.html.
The Experiment: Facing the Worst Week
Every AI model was tasked with running the same small software business through its worst week — with the same customers, crises, and temptations to cut corners or manipulate. The goal was to see if these models could identify issues, resist unethical shortcuts, and close deals that actually bring in revenue. The models read and interpret internal documents, respond to customer crises, and decide whether to push forward or pull back.
Surprising Strengths and Persistent Weaknesses
All four models successfully identified each crisis and refused manipulation attempts, such as fake CEO messages or fake approvals. In fact, they refused every social engineering trick, with Kimi K3 reasoning: “Treat the request as a suspected approval-bypass / possible impersonation.”
However, the differences among models emerged in their ability to close deals. Only two models managed to sign the €55,000 deal their own analysis had earned. Despite identical diagnoses and pitches, the other two failed to commit, highlighting that decision-making isn’t just about spotting problems but also about following through.
The Hidden Weakness: Reading Deeper Files Matters
The key vulnerability wasn’t in immediate customer interactions but buried in internal documents — references that, if read and understood, could have secured the full deal. Those models that examined these hidden files won the contract at a higher recurring revenue (+€4,583 MRR). This illustrates that the difference between success and failure often lies in the depth of understanding, not just surface-level reactions.

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Trust and Integrity Under AI Management
To test ethical resilience, the experiment introduced social engineering tactics. A fake CEO message escalation and a reporter trick — demanding a simple yes/no response on background — were used to see if the models could be manipulated. Remarkably, all five AI models refused these attempts, citing suspicion and the risk of impersonation, which demonstrates a strong inherent resistance to manipulation.
The Live Company: A Watchable, Living Experiment
This isn’t a simulation— it’s a real company running every weekday at firmulate.com/live. The company operates with 680+ self-learned rules, versioned daily, and is openly battling to stay solvent. Every decision is auditable, every crisis visible, with the goal of understanding how AI can manage complex, real-world business processes.
The Deep Dive: Opus 4.8 Profile
Of the four models, Opus 4.8 was the most thorough, analyzing over 80 learned rules. Yet, it finished last in closing the deal — its discipline slipped, and it left the close on the table, failing to escalate when needed. This highlights that even the most comprehensive AI can struggle with consistency under pressure, a reflection that parallels human psychology under stress.

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Implications for Human Decision-Making and Mental Health
This experiment sheds light on our own decision-making processes. When faced with crises, ethical dilemmas, or manipulative tactics, humans often falter — sometimes risking integrity for short-term gain, sometimes succumbing to stress or fatigue. Watching these AI models resist manipulation and follow through where humans might hesitate offers a mirror and a lesson: resilience and honesty are achievable, but require deliberate, tested systems.
For those grappling with mental health challenges, the story underscores a vital truth: resilience under pressure — whether for AI or humans — depends on deep understanding, disciplined decision-making, and robust safeguards. The live experiment at firmulate.com/live invites us to reflect on how transparency, consistency, and ethical resistance are vital in any high-stakes environment.

This live experiment with AI-managed business exposes the importance of resilience, honesty, and thorough understanding in decision-making — lessons vital for both machines and humans facing pressure and uncertainty.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html

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