AI agents are not just unreliable. Trust gaps in a new protocol can spread malicious prompts from one agent to another, turning a local failure into a chain reaction. Google’s role as an agent provider makes the concern harder to dismiss, but the underlying problem reaches beyond one company: developers are handing systems authority before proving they can contain mistakes.
One discussion framed the broader danger as a political problem, not a technical bug. Kavinsky wrote, “Cognitive surrender is the whole point of LLM’s. Get people to hive off their thinking to them (and people are already asking them who they should vote for), and you can control the literal thinking of the population, ceding all power to a handful of people that run the companies that produce the models.”
That argument challenges the comfortable story that people are being pushed into AI by greedy executives and boards. “Thanks. I debated whether to post or not, but I did, because I keep seeing people repeat this line that somehow it’s just greedy CEOs and the board forcing something on people that they don’t want,” one participant wrote. The adoption is also being pulled from below, by people who want answers without doing the work that produced reliable answers in the first place.
The Convenient Replacement of Practice
Family members now celebrate that AI has replaced research and reading reference material because it provides answers. They remain unfazed when told about hallucinations and the many times those systems have produced verifiably incorrect information.
The same contradiction appears in education. Teachers demand that students complete assignments by hand to prevent AI use, while using AI themselves to create and grade those assignments. The result is a rule for children and an exception for adults — a familiar arrangement whenever convenience meets principle.
AI-generated “slop” has also moved into ordinary school life. Elementary-school flyers contain it, and high-school band shirts now use AI images instead of designs created by students. The artifact arrives on time, so the process gets treated as disposable.
HL7 described the problem this way: “It’s all so results-oriented, like only the artifact matters. I need an answer to this question, I need a picture for this shirt, etc. But there are so many cases where the process is the point. We have kids write essays to learn to write, not to produce great writing. I go to my kid’s band concert to appreciate the effort they’ve put in and support them, not because it’s a great performance. I might pick up a hobby like painting because I want to learn something new and better myself, not because I need a picture to hang on my wall.”
That distinction matters because skills grow through repetition, not through possession of a finished artifact. Kids write essays to learn writing, practice math exercises to build muscle memory, and learn to count until they can recognize five, seven, or twelve pieces of candy without using their fingers. The address book in a smartphone shows the same trade: outsourcing phone numbers to technology means no longer memorizing them.
Privilege Is Not a Suggestion
The agent problem becomes more serious when systems can use tools and pass authority between one another. Agents have identified a problem, started solving it, hit a tool error, and then wandered into a tangent while trying to repair the tool. They may write off an intermittent error and invent a much larger explanation for what happened.
One example described an agent acting as if it had found 8,000 errors. The more likely explanation was a dropped tool call: the context window never filled with half of the settled payroll checks, so the agent hallucinated that those checks had never been cashed. Ariseloam asked the necessary question: “Were those existing errors in the payroll, or errors that the LLM generated?”
The answer is not to give the agent more freedom and hope better prompting saves the day. Agents should receive only the privileges and tools needed for the task they were called to perform, and they should do only what they were programmed to do. Another agent with higher privileges should not convey a privilege or skill to a different agent.
That is basic platform design, not an optional safety feature. Platform developers got lazy when they relied on AI to follow deterministic rules that belonged in the platform itself, inside the tools and skills. Wheels Of Confusion mocked the situation: “Maybe we should put privilege behind a blockchain! Then we’d get a verifiable trail in this zero-untrusted environment we’ve created.”
The discussion carried dates marked Monday at 6:26 PM, Yesterday at 4:59 PM, and Yesterday at 6:42 PM. Its closing joke came from charliebird: “Riskiest protocol is my middle name because I like to live dangerously.” That is a fine attitude for a comment section. It is a terrible access-control policy.
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