
In home decor and gift businesses, the ability to close a sale—especially during tough times—is everything. But how do we really know if an AI assistant can perform under pressure? A groundbreaking experiment with AI models running a simulated company exposes surprising truths about closing deals, honesty, and discipline—things that aren’t visible in chat demos.
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The Experiment: Putting AI Models to the Test
Recently, four frontier AI models took on the challenge of managing a small software company facing its worst week—think of it as a stress test for AI management skills. The same company, same crises, same temptations. Every decision was recorded and auditable, simulating real-world pressures that your customer service or sales AI might encounter in a home decor business.
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What the Metrics Say
According to the latest Crucible League, the scores ranged from 95 to 73 points across models, with the baseline at 26. The top performer, gpt-5.6-sol, scored 95 and successfully found a critical buried fact in the company’s files that clinched a €55,000 deal—a win that was entirely based on reading and understanding internal documents, not just chat interactions.
The second-best, Kimi K3, scored 93 and also closed the deal. Notably, K3 ran without a default effort parameter, meaning it was less aggressive but still effective. Meanwhile, Sonnet 5 scored 88 and Fable 5 scored 77, with the latter showing the best discipline but ultimately leaving the deal unexecuted, losing the revenue opportunity.
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The Hidden Skill: Reading Documents Matters
The experiment revealed a crucial insight: the real weakness isn’t in spotting crises or resisting manipulations—those skills all models shared. Instead, the decisive factor was whether the AI read the company’s files deeply enough to uncover the hidden, buried fact that made the deal possible. Only those models that delved into the internal documents won the full €55,000 deal, increasing their Monthly Recurring Revenue (MRR) by over €4,500.
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Resistance to Manipulation and Ethical Challenges
All four models refused several staged social engineering attempts—fake CEO messages escalating in three stages and a reporter asking for quick approval “on background.” The models’ on-record reasoning was consistent: treat suspicious requests as impersonation or approval-bypass attempts. This demonstrates that advanced AI can maintain integrity and honesty even under pressure, a crucial quality for customer-facing roles.
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Discipline and Execution Under Pressure
A notable case was Opus 4.8, the most thorough participant with over 80 learned rules. Despite its deep analysis and discipline, it ultimately failed to close the deal. Instead, it left the opportunity on the table, shifting work into a locked department rather than executing the deal—highlighting that thoroughness alone doesn’t guarantee performance under stress.
What This Means for Home Decor and Gifts Businesses
If your business relies on AI to manage customer relationships, support, or even sales, this experiment underscores a vital point: the ability of an AI to produce high-quality chat is not enough. Real competence involves reading your internal files thoroughly, resisting manipulative tactics, and following through to completion. These are the invisible qualities that determine whether an AI can truly support your business in closing deals and maintaining trust.
The Bottom Line: Testing Matters
What the experiment demonstrates is that assessing AI solely through chat demos—highlighting how well it writes or responds—is misleading. The true test is whether the AI can close a deal, stay honest under pressure, and execute with discipline. In this sense, the experiment’s findings are a wake-up call: before you hire an AI for critical business functions, simulate its performance in your own “worst week.”
Firmulate’s live platform offers just that—test your AI workforce against real crises without risking your actual business systems. It’s about measuring management quality, not just chat quality. Learn more at firmulate.com.

Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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