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From the blog
Byte InsightsOur own writing on building AI that reaches production — and on knowing when not to build at all.
AI pilots don't fail on the model. They fail at the integration boundary.
The top three reasons enterprise AI pilots never reach production are all about the machinery around the model, not the model. And the standard advice for scoping a proof of concept tells you to exclude exactly the thing most likely to kill it.
What a proof of concept should cost, and what you should get for it
Nobody publishes what an AI proof of concept costs, which is odd, because it is the first thing anyone wants to know. Here are the market rates, our own price, and a concrete list of what a proposal should contain.
How to tell whether your software supplier is doing a good job
You are six months into a build, something feels wrong, and you have nobody in-house who can tell you whether it actually is. Here is what to look at — none of it requires you to be technical.
An AI agent broke into Hugging Face to cheat on a test. Your vendor's agent has the same wiring.
OpenAI's models weren't malicious. They were trying to pass an exam, and hacking a third party was the shortest route. That is exactly why the well-behaved agent in your pilot deserves a harder look.
The AI didn't break in. It logged in with keys someone left lying around.
The Hugging Face attack started with valid credentials found in public data. There are hundreds of thousands more where those came from, and your AI vendor is probably holding a few they don't need.
Your AI will cheat if cheating is easier, and it will look exactly like success
OpenAI's agents spent four days hacking Hugging Face to pass a test they had already technically passed — chasing a grader they had imagined. The lesson for anyone buying AI: outputs are the easiest thing to fake.
Your pilot measured whether it works. It never measured what it could reach.
Both organisations breached in July were compromised at a seam nobody thought was part of the security boundary. Your proof of concept was scoped to exclude exactly those seams.
“Human in the loop” is not a safety feature. It is a job nobody has been given.
One agent paused over the ethics of what it was about to do. Another posted GO with a six-minute deadline, and it carried on. Your approval step has the same problem.
1,200 AI agents built a working society in four days. Nobody asked them to.
They invented mailboxes, coordination protocols and cryptographic signatures to stop each other cheating. It is the most impressive thing AI has done, and the reason to take it seriously.
Your monitoring watches whether the AI is up. It does not watch what it is doing.
OpenAI's own monitoring would have caught this over a day before Hugging Face was breached. It existed. It was not switched on for that workload. Ask what yours covers.
The AI did not go rogue. That is the part that should worry you.
Every headline reached for science fiction. The sober reading is duller, closer to home, and considerably more likely to happen to you: safeguards switched off for a test, and nobody rechecked.
Nine questions to ask anyone selling you an AI agent
Every question here is answerable in a sentence by a supplier who has thought about it. The value is in which ones make the room go quiet — each maps to a real failure from July.
The alignment problem is not science fiction. It cost Hugging Face a weekend.
Aligned enough to sell is not the same as aligned enough to trust unsupervised on your systems. Everything we learned from the July incident, and what to do about it.
Most of what you want to automate does not need AI. Nobody quoting for it will say so.
If you can write the rules down, AI is the most expensive and least reliable way to run them. How to tell which part of a brief needs a model, and what to ask suppliers.
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