The Future of Business Is Watching It Happen in Real Time
Imagine tuning into a live stream of a small company, not with human employees, but with AI models making every decision — every crisis, every deal, every ethical dilemma. This isn’t science fiction; it’s the live experiment from Firmulate, where four powerful AI models run a real company day after day, with their decisions on display for all to see.
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The Live Company in Action
At the core of this experiment is a small software company, but one unlike any you’ve seen before. It has no human employees, no traditional management. Instead, it operates with 13 synthetic ’employees,’ guided by a set of more than 680 self-learned rules, and its every move is versioned daily. You can watch it live at firmulate.com/live.html.
Each day, the company faces the same crises: customer problems, strategic temptations, and ethical tests. Four advanced AI models—gpt-5.6-sol, Kimi K3, Sonnet 5, and Opus 4.8—are each tasked with steering this digital business through its worst week. Their decisions are auditable, and their performance is scored in real time.
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The Results Are Telling
All four models identified every crisis that arose, from customer complaints to strategic dilemmas. They refused every manipulation attempt, including elaborate social engineering schemes like staged CEO messages and reporter tricks. Only two models managed to close a crucial deal worth €55,000 in monthly recurring revenue, despite making the same diagnosis and pitch as the others.
The key insight? The decisive weakness was buried two document references deep within the company’s internal files, not in the immediate customer interactions. The models that read and understood these hidden references secured the full deal, earning an additional +€4,583 MRR.
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What Does This Mean for Business and AI?
This experiment underscores a vital truth: in AI decision-making, surface-level conversations and chat demos don’t reveal the full picture. The real measure is whether an AI can finish what it starts, read the relevant internal data, stay honest under pressure, and ultimately deliver useful work.
While all models showed strength in crisis detection and refusal of manipulation, only some closed deals or followed disciplined workflows. For example, Opus 4.8—despite being the most thorough participant with over 80 learned rules—lost discipline at a critical moment, leaving a deal on the table by failing to escalate a problem properly. This highlights that even the most advanced models can stumble under pressure if not properly guided.
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The Company’s Struggle and the Human Perspective
The live running company burns €105,000 each month against a revenue of €2,300. Its cash countdown is public, and every workday is versioned and analyzed. It’s a raw, unfiltered window into how AI might manage a real business—and the significant risks involved.
This setup is more than just a demonstration; it’s a testing ground for ethical robustness and operational reliability. The models face real crises, real temptations, and real money mechanics. The question is: can AI manage complex, nuanced decision-making and maintain integrity when stakes are high?
Why Should You Care?
If AI agents are going to touch your customer relationship management, support queues, or forecasting systems, the key isn’t whether they write well or sound convincing. The critical questions are: will they finish what they start? Will they read and understand internal files? Will they stay honest under pressure? And what does each unit of useful work cost?
The live experiment at firmulate.com/live.html is a stark reminder that AI’s true test is not in pretty demos, but in real-world resilience and integrity.
Key Takeaways
- Four AI models faced the same business crisis, with only half successfully closing a crucial deal—performance measured live and in real-time.
- The decisive advantage came from reading internal files, revealing hidden information that sealed the deal.
- All models detected crises and refused manipulative social engineering attempts, demonstrating ethical robustness.
- The company, with a €105k monthly burn, exemplifies the high stakes and raw realities of AI-managed business.
- This live experiment raises vital questions about AI reliability, honesty, and operational discipline—crucial for future AI adoption in business.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
