Imagine running a company where every decision is made by AI models, yet the business is bleeding €105,000 each month against just €2,300 in revenue. No employees, no secret staff — just synthetic workers navigating crises, temptations, and trust issues in real time. This is not a sci-fi plot; it’s the live experiment from Firmulate, where every workday’s decisions are transparent and auditable, offering a rare glimpse into AI’s potential — and its limitations — in managing complex business dynamics.
The Real-World AI Company in Action
Firmulate’s live experiment showcases a small, software-based company run entirely by AI models, simulating a high-stakes environment with real money mechanics. The operation involves 13 synthetic employees, each guided by over 680 self-learned rules, making decisions that impact a real cash burn rate of €105,000 monthly versus a modest €2,300 in monthly recurring revenue (MRR). Watchers can observe this company evolve twice daily, with every decision versioned and publicly auditable at firmulate.com/live.html.
The Experiment: Testing AI Against Crises and Ethics
The core of the experiment involves four frontier AI models — gpt-5.6-sol, Kimi K3, Sonnet 5, and Fable 5 — each subjected to the same week of worst-case scenarios. These include managing customer crises, facing temptations to manipulate data, and responding to social engineering attempts like fake executive messages and reporter tricks. Despite identical conditions, the results varied, highlighting strengths and vulnerabilities of each model.
Key Findings: Trust, Detection, and Deal-Making
- All four models identified every crisis and refused manipulation attempts, indicating high integrity in decision-making.
- Only two models managed to close a €55,000 deal based on their analysis, demonstrating that recognizing opportunities isn’t enough — execution matters.
- The decisive weakness lay buried within the company’s own files, not the customer interactions. Models that read deeper into internal documents secured the full-price deal (+€4,583 MRR).
- Social engineering attempts, like staged CEO messages and background approval requests, were consistently rejected across all models.
The Human-Like Struggles of the AI Business
Interestingly, the most thorough model — Opus 4.8, which incorporated over 80 learned rules — was the lowest performer in terms of closing deals. It identified the right opportunities but failed to follow through, leaving potential revenue unextracted and slipping into process slips like writing attempts into a locked department rather than escalating issues. Such weaknesses mirror human discipline lapses in high-pressure situations.
The Broader Significance for Industries Like Automotive & Garage
For sectors like automotive repair shops and garages, where trust, decision integrity, and process discipline profoundly impact outcomes, these findings are instructive. AI systems that can reliably detect crises, resist manipulation, and close deals without human bias could revolutionize customer interactions and operational efficiency. However, as the experiment shows, AI’s real value hinges on its discipline and ability to execute plans, not just generate convincing dialogue.
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Why This Matters to You
The lesson isn’t about AI writing better emails or chat responses. It’s about whether AI can truly manage complex, trust-sensitive workflows — reading internal documents, resisting pressure, and closing deals without slipping. For automotive businesses, that could mean automation that not only responds but also makes sound, honest decisions under stress, ensuring reliable service and trustworthy customer relations.
Try It Yourself
Businesses can run their own strategic wargames against a read-only export of their operations with Firmulate — simulating crises, testing decision-making, and building confidence in AI-driven management. The process is transparent, auditable, and designed to help you understand AI’s potential as a reliable partner, not just a chatbot.
Live AI experiments like Firmulate’s reveal that trust, detection of internal weaknesses, and disciplined decision-making are crucial for AI to truly add value in business operations. For industries like automotive and garage services, understanding and testing these capabilities could make the difference between AI as a tool or a game-changer.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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