The movie has a sequel: oracle poisoning ☠️🤖
Last time the system fooled itself. This time someone does it on purpose.
Researchers are already documenting it in agent stacks: “the better the agent reasons, the more convincingly it propagates the attacker’s false premises” 😩
That’s the job. Not compliance paperwork but an anchor with manipulation resistance.
Building it at @agentic_data ⚓️
Paper + full argument 👇
Replying to @mierzwik @agentic_data
Oracle poisoning paper:
arxiv.org/abs/2605.09822
The longer argument on why agent graphs need an anchor: governedagent.substack.com
mierzwik retweeted
Nadciąga fala awantur w matematyce. Modele AI są już wystarczająco silne, by wskazywać błędy w opublikowanych dowodach, więc będzie wesoło…
Enterprise data needs the same thing before agents run on it: semantic definitions with owners, enforced OUTSIDE the loops that could easily game them 🫡
That's what we’re building at @agentic_data ⚓️
agentic-data.com
Ask an agent for FX exposure, and it writes SUM(fx_rate). The query runs. The judge model approves it. The evals score it reliable. But the number is garbage. A rate isn't additive, and nothing in that stack knows what the column means.
More loops won't fix this.
An anchor will.
I wrote the full second-by-second post-mortem, plus the blast-radius audit and an incident-response card you can lift:
open.substack.com/pub/govern…
This failure class has a name, too. That's the next one.
Sources:
• PocketOS: theregister.com/software/202…
• Replit: fortune.com/2025/07/23/ai-co…
(The agent was Cursor running Claude Opus 4.6.)
In April, an AI coding agent wiped a startup's entire production database in 9 seconds, and the backups with it, since they sat in the same volume.
The founder, @lifeofjer, posted the whole story.
But the agent isn't really the story. 🧵






