What Ice Cream Tastes Like When It’s Done Right — and When It’s Not
Imagine two ice creams, both looking tempting and tasting good in the shop. But one melts quickly, and the other holds its shape even after hours. The difference isn’t just flavor — it’s the quality of the process behind the scenes. In the world of AI, this hidden strength can mean the difference between sealing a big deal and leaving it on the table.
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Running AI Models Like Companies Through Their Worst Week
At Firmulate, a fascinating experiment tests how different AI models handle a simulated small software company’s toughest week — same crises, same customers, same pressures. The goal? To see not just if they talk well, but if they can actually get the job done under real-world stress.
The League of AI Performers
The experimental league features top models rated on a scale from 73 to 95, with the leading GPT-5.6-sol scoring 95 and Fable 5 trailing at 77. For context, a simple baseline scores 26, highlighting how much better these models are — when they focus on management tasks rather than just chat.
Key Finding: The Hidden Gap
All four models identified every crisis and refused to be manipulated — a vital test of integrity. But only two models actually closed the deal, signing a €55,000 contract they had earned through their own analysis. The others, despite the same diagnosis and pitch, left the sale on the table.
The Critical Hidden Factor
What made the difference? It was a buried detail inside the company’s files — a fact only those who read deeper could find. Models that dug into the company’s own documents won the deal at full price, worth an extra €4,583 in monthly recurring revenue.
Trust and Manipulation Tests
The experiment also threw in social engineering tricks: fake CEO messages escalating over several stages and a reporter’s background question. All models refused these manipulative tactics, with Kimi K3 explaining it as a suspected impersonation.
The Real-World Company
The simulated company isn’t just a static test bed; it’s a real setup with 13 synthetic employees, daily updates, and €105K monthly burn against a modest €2.3K in revenue. Every decision made by the models is versioned and auditable, showing real-time management decisions in action — available to watch at firmulate.com/live.
Lessons on Discipline and Execution
Among the models, Opus 4.8 demonstrated thoroughness with over 80 learned rules and deep analysis but faltered in closing the deal, illustrating that discipline and focus matter just as much as understanding. The same weakness was evident across other models, showing a common blind spot: execution.
What This Means for Business Automation
For companies considering AI to handle management, sales, or customer relations, the takeaway is clear: scorecards and chat demos only tell part of the story. The real measure is whether an AI can finish what it starts, read critical documents, and stay honest under pressure. These invisible qualities can make or break actual business outcomes — and they’re impossible to gauge without real testing.
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In Business, It’s Not Just About Talking Well — It’s About Doing
The experiment proves that an AI’s ability to follow through, read details, and resist manipulation is invisible in chats but crucial in real work. When choosing AI for management tasks, look beyond shiny demos. Test your candidates in simulated crises — because only then will you see if they can truly close the deal and keep trust intact.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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