In the world of smart home appliances, a slick chatbot that can answer questions is impressive—but does it actually get the job done when it counts? As companies compete to replace human support and sales teams with AI, the real test isn’t how well these models chat—it’s whether they can close deals, follow through on commitments, and stay honest under pressure. Recent experiments reveal that many AI systems excel at detecting crises and resisting manipulation, but only a few can execute what they’ve analyzed and deliver real results.
What’s at Stake in AI-Driven Business Operations?
For businesses in the smart home sector, AI isn’t just about answering customer questions faster. It’s about managing complex operations, closing sales, and maintaining trust—especially when facing crises or shady requests. A recent live experiment conducted by Firmulate tested four cutting-edge AI models by running a simulated small software company through its worst week, complete with real crises, competitive pressure, and manipulative tactics. The goal? See which AI could not only spot problems but also act decisively to close a €55,000 deal based on its own analysis.
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How the Experiment Worked
The models—gpt-5.6-sol, Kimi K3, Sonnet 5, and Fable 5—were given the same company profile, same customers, and identical crises. They had to make management decisions, handle fake CEO messages, and decide whether to sign the deal. Every decision was tracked and auditable, giving clear insight into their reasoning and discipline in execution.
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Key Findings: Spotting Crises Is Not Enough
All four models demonstrated impressive capabilities—they identified every crisis and refused to fall for manipulation attempts, such as fake CEO messages or reporter tricks. For example, every AI refused to approve dubious requests, with Kimi K3 explicitly stating it would treat suspicious approval requests as potential impersonation.
But here’s the catch: only two models actually executed the deal that their own analysis had justified. The gpt-5.6-sol and Kimi K3 signed the agreement, earning themselves full €55,000 commissions. The others, despite recognizing the problem, left the deal unexecuted, leaving value on the table.
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The Hidden Weakness: Reading the Files Matters
Digging deeper, the experiment uncovered a crucial weakness: the decisive information wasn’t in the customer interactions but buried two document references deep in the company’s internal files. The models that read and understood these internal documents successfully closed the deal at full price, adding an extra €4,583 MRR. It’s a stark reminder that true operational intelligence—reading the full context—is vital for real-world success.
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Resisting Manipulation Is Not Enough
The models’ refusal of social engineering tactics—fake CEO messages and reporter tricks—showed their integrity. All five models rejected manipulative requests, showing they can resist pressure and remain honest. However, only those that followed through on their analysis and signed the deal demonstrated the ability to translate understanding into action.
The Real Test of AI Business Skills
In the live company simulation, 13 synthetic employees with real money mechanics, the models faced daily crises, a cash countdown, and an ever-changing playbook of rules. The model that performed best—gpt-5.6-sol—successfully closed the full deal. Others, like Opus 4.8, ran a more thorough analysis but slipped in discipline, leaving the deal unexecuted, despite understanding the value.
What This Means for Smart Home Companies
The takeaway is clear: the ability to detect and resist manipulation is not enough. For AI to truly augment business operations—whether managing smart appliances, customer support, or sales—it must be able to read, understand, and act on critical information buried in internal data. It’s about execution, not just chat quality.
Testing Your AI Workforce Before Deployment
Firmulate offers a unique opportunity for enterprises to run the same type of wargame against their own AI systems. Using a read-only export of your business data, you can gauge whether an AI model will read your files carefully, follow through on decisions, and stay honest under pressure—without risking real-world consequences. You can watch the simulation live, examine decision logs, and assess whether your AI can truly deliver on its promises.
Conclusion: Closing the Gap Between Diagnosis and Action
Smart home companies investing in AI should focus on the model’s ability to get the job done, not just generate convincing chat. The live experiment by Firmulate confirms that AI’s true strength lies in execution—reading the full context, resisting manipulation, and closing deals or solving problems without hesitation. As AI continues to integrate into your operations, testing these capabilities before deployment will be critical to avoid costly failures and unlock real value.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
