firmulate.com/benchmarks.html — live view
AIThis post was created with the assistance of artificial intelligence (AI).
Firmulate — Four AI Models Ran the Same Company Through Its Worst Week. Only Two Finished the Job.
Live on firmulate.com.

Imagine a solar power installer managing your backup systems with AI. You want it to make tough decisions, not just sound convincing. As with energy backups, the real test of an AI’s value isn’t in how well it chats — it’s whether it completes the job when it counts. Recent experiments reveal that many AI models can identify crises and resist manipulation, but only a few actually follow through with the work that delivers tangible results.

Before you orderOffer from Amazon

Get backup power and energy gear delivered free with Prime

  • Fast, free delivery on millions of items
  • Prime Video, Amazon Music and more included
  • Member-only deals all year
Start your free Prime trial Free trial for eligible customers · Cancel anytime
As an affiliate, we earn on qualifying purchases.

The Crucible: Testing AI in a High-Stakes Business Environment

To understand what AI can truly do in critical roles, a live experiment by Firmulate staged a thorough test. Four advanced AI models were each tasked with running the same small software company through its toughest week, facing identical crises, customer demands, and ethical dilemmas. Every decision made by these models was recorded and auditable, providing a clear view of their capabilities beyond simple chat demos.

Products Worth Considering

Bose TV Speaker Compact Soundbar with Bluetooth and HDMI-ARC, Black

Bose TV Speaker Compact Soundbar with Bluetooth and HDMI-ARC, Black

As an affiliate, we earn on qualifying purchases.

Key Findings: Recognition vs. Action

All four models demonstrated impressive awareness: they identified every crisis and refused every manipulation attempt, including a staged social engineering attack involving fake CEO messages. This shows that AI can be trained to detect threats and resist deception, a critical capability for business security and integrity.

However, the real divergence appeared in their ability to execute on their own analyses. Only two models, gpt-5.6-sol and Kimi K3, managed to close the deal worth €55,000, which their analyses had justified. The other two—Sonnet 5 and Fable 5—recognized the opportunity but left the deal on the table, failing to take the final step to complete the sale.

The Hidden Weakness: Reading the Files That Matter

Digging deeper, the decisive factor was how well each model utilized the company’s internal documents. The models that read the files thoroughly uncovered a critical piece of information buried two references deep within the company’s records—an insight that clinched the deal. This suggests that surface-level chat behavior doesn’t reveal an AI’s true capacity for impactful work; it’s whether it can access and act on the underlying data that makes the difference.

Discipline Under Pressure

Even with the most comprehensive models, discipline proved fragile under pressure. For instance, Opus 4.8, the most thorough participant with over 80 learned rules and deep analyses, ultimately failed to close the deal. Its decision-making slipped, and it left the opportunity unexploited by failing to escalate internal issues properly. The same pattern was observed across all models—an inability to maintain disciplined execution during critical moments.

Why Chat Demos Are Deceiving

This experiment underscores a vital point for businesses considering AI solutions: impressive chat capabilities do not necessarily translate into reliable, decisive work. Many AI models excel at generating convincing dialogues but falter when it comes to following through on their own insights or maintaining consistency under pressure. For energy systems, backup power or solar management, this could mean the difference between a system that merely responds well and one that reliably performs when it matters most.

The Real Measure: Execution in a Live Environment

By comparing performance scores—where gpt-5.6-sol scored 95 and Kimi K3 scored 93, both closing deals, versus Fable 5 at 77 and Opus 4.8 at 73—it’s clear that the top models aren’t just better at understanding; they’re better at finishing. The experiment demonstrates that effective AI management isn’t about superficial interaction but about the ability to make and execute critical decisions, especially under stress.

Practical Implications for Energy and Backup Power

For companies managing energy systems or backup power, this insight is crucial. An AI that can identify problems is valuable, but one that consistently acts on its findings—reading internal data thoroughly and resisting manipulation—is essential for reliable operation. When deploying AI to safeguard or optimize your energy infrastructure, focus on models that demonstrate disciplined execution in real scenarios—not just impressive demos.

Infographic — Four AI Models Ran the Same Company Through Its Worst Week. Only Two Finished the Job.
The findings at a glance — source: firmulate.com.

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

Powered by Thorsten Meyer AI


You May Also Like

Meta Is Building a Cloud Business to Sell Excess AI Compute

Meta is developing a cloud platform to sell surplus AI computing capacity, aiming to monetize its AI infrastructure amid expanding AI workloads.

Apple sues OpenAI, accuses ex-employees of stealing trade secrets

Apple has filed a lawsuit against OpenAI, accusing former employees of stealing proprietary trade secrets related to AI technology.

Software Engineering At A Proprietary Trading Company: Optiver

Optiver, a leading proprietary trading firm, is hiring additional software engineers to enhance its trading algorithms and infrastructure, confirming growth plans in tech.

Meta to sell excess AI computing capacity via cloud business, Bloomberg News reports

Meta plans to sell surplus AI computing capacity through its cloud business, according to Bloomberg News, marking a shift in its infrastructure strategy.