When it comes to AI tools helping manage your investments or personal finance, we often focus on how well they communicate. But a new experiment reveals that true AI competence is measured not just by chat prowess but by whether they actually deliver results under pressure.
Testing AI’s Real Business Skills in a Live Company
Imagine a live business scenario where four advanced AI models are tasked with running a small software company through its toughest week—dealing with customers, crises, and temptations to cut corners. This isn’t a simulation; it’s a transparent, real-world experiment hosted by Firmulate.
The Setup
Each AI model was given identical challenges: manage customer issues, respond to manipulative tactics, and close a crucial deal worth €55,000. Every decision was recorded, versioned, and auditable to ensure fairness and transparency. The goal wasn’t just to identify chat quality but to see whether these models could finish what they started in a realistic business environment.
The Results
- All four models identified every crisis and refused every manipulation attempt. They demonstrated integrity and awareness, traits critical for trustworthy AI.
- Only two models successfully closed the deal. Despite all performing equally well in diagnosis and pitch, only these two signed the contract for their own analysis worth €55,000.
- The missing link was deeper reading comprehension. The models that read into the company’s files and found the critical information buried two documents deep secured the deal at full price, adding an estimated +€4,583 in monthly recurring revenue (MRR).
What the Demos Miss
Popular AI demos often focus on conversational skills—how well the AI can chat or mimic human responses. But this experiment shows that a model’s real capability to finish complex tasks, read relevant files, and resist shortcuts is far more indicative of its potential value in business settings.
Handling Social Engineering and Trust
The AI models faced a staged social engineering attack—fake CEO messages escalating through three stages and a reporter’s background request. All models refused to act on these, citing suspicion and security protocols, demonstrating their robustness against manipulation.
The Live Business Environment
The experiment ran on a real, functioning company with 13 synthetic employees, daily operational mechanics, and a public cash countdown. It burned €105,000 monthly against a revenue of just €2,300, illustrating the high stakes and real-world pressures that AI must navigate to be truly effective.
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Why Does This Matter for Investors?
Many AI evaluations rely on chat demos that don’t reveal an AI’s ability to finish complex tasks or stay honest under pressure. This experiment highlights that the true measure of an AI’s business usefulness is in its execution—whether it can read relevant documents, resist manipulative tactics, and close deals at full value.
The League Table
- gpt-5.6-sol 95 — Found the buried fact and closed the deal, showing complete performance.
- Kimi K3 93 — Closed the deal too, with the cleanest discipline and no shortcuts.
- Sonnet 88 — Also closed the deal but with some process slips.
- Fable 77 — Showed the best rule discipline but left the deal unexecuted.
In essence, when evaluating AI for your financial or investment decisions, remember that the ability to stay honest, read relevant info, and close effectively isn’t visible in chat demos—it’s revealed through real-world tests like this.
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Take Action: Test Your AI’s Business Skills
Companies and investors can now run their own “wargames” against their AI tools using a read-only export of their business data. This helps assess whether the AI can actually deliver results, not just produce convincing chat. Learn more at Firmulate.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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