🤔 I struggle with most research papers, but the Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents was an easy read. The paper follows a fascinating study where researchers simulate various LLM models running a vending machine business over time.

What caught my eye wasn’t just the research methodology. It was this post by @benjojo sharing screenshots of the increasingly desperate emails the AI agent sent while trying to save its failing business. Watching an AI spiral into panic mode as quarterly profits tanked? That’s the kind of real-world AI behavior we rarely see documented.

The email screenshots at the end are genuinely wild and worth checking out. You can watch the Agent’s “thought process” deteriorate from professional business correspondence to what can only be described as digital desperation after it keeps getting charged a $2 daily fee to operate.

Finally, AI That Closes the Last 10% Gap

What makes this research particularly relevant is the timing. I would love to see an updated version testing newer LLM models like Claude 3.7 + 4 and OpenAI’s o3 + o3-mini series. This latest generation represents the moment I noticed AI crossing from “sort-of good” to actually reliable.

Previously, I was happy having AI solve 90% of my random side project problems and finishing the rest myself. But once Claude 3.7 and o3-mini hit production, something shifted. I could throw most issues at them and find complete, working solutions.

The sweet spot example: Asking an LLM to build Stripe from scratch? It’s still too ambitious. But requesting it adds three specific Stripe subscription plans to an existing Django website, with proper error handling and webhook integration? That’s now a 10-minute task that seems to work.

Real-world test: My seven-year-old and I fell down a 45-minute YouTube rabbit hole about “How to Run a Vending Machine Business” over the weekend. We’re not actually planning to start one, but his uncle runs a laundromat and mentioned wanting to add vending machines on one of our last family visits. This research paper felt less academic and more like a preview of what’s possible when AI agents handle small business operations' mundane but critical parts.

I’m conflicted about the paper because many people won’t read it and skip to the failure as “further proof” to confirm their bias. That said, we are moving to a future where AI agents can manage the boring parts of our businesses so we can focus on what matters.

Written by Jeff, typos fixed by Grammarly, feedback and heading suggestions via Claude 4