Famed iPhone, Sony Hacker Says AI Coding Agents Are a Disaster Waiting to Happen

It never quite does.

Not about ego

Hotz anticipates the obvious pushback: a programmer who defines part of his identity through his craft would naturally resist tools that threaten to replace him. He takes the objection seriously and dismisses it on the merits.

“​​I thought more about the self worth preservation thing. Google’s AFL found more bugs than LLMs and nobody felt that way about it. Chess and Go are more popular than ever,” Hotz wrote. And he’s right in the sense that Chess AI has dominated humans for decades and the game only grew more popular.

So, his concern isn't about being replaced. It's about what happens to code quality when everyone is using these tools at once, especially when Big Tech and Wall Street are constantly pushing for the mass use of these tools.

“I almost think this is some kind of psyop to sell agents,” Hotz argues. “Fear of loss is one of the only ways to make big companies move. Though I think in that fear they are making a big mistake.”

His central argument is organizational. High performers have tight enough feedback loops to catch agent-generated problems before they ship. They read the code, spot the errors, and calibrate when to trust the tool. "The bottom performers won't have that self check," he writes—and they're the ones using agents to produce 10 times their previous output. At a large company, that math produces something specific: faster degradation of average code quality, masked by sheer volume.

The outcome, he argues, will be "a golden era for buckets and buckets of slop, and a dark age for gems of quality." As a concrete example, he points to reports that Apple is pushing AI coding tools across its entire engineering organization, then asks simply: "Do you think macOS will get better or worse in the next 2 years?"

Where the camps stand

Hotz now places himself in what he calls the "LeCun/Marcus camp"—referring to Yann LeCun, Meta's chief AI scientist, and Gary Marcus, a longtime LLM skeptic. Both have argued that language models are fundamentally sophisticated pattern-matchers: They can imitate the distribution of existing code, but can't reason through genuinely new problems from first principles.

Vibe coding—describing what you want in plain language and letting AI generate the implementation—has exploded over the past year, and the major labs have positioned agent-based coding as a flagship product. Microsoft transformed GitHub Copilot into a full agentic system in 2025, with CEO Satya Nadella describing it as a platform-level shift comparable to the move to cloud.

The pushback to Hotz's position isn't abstract. Karpathy, who had been skeptical of agents earlier in 2025, reversed his position after new model releases and joined Anthropic's pre-training team on May 19—five days before Hotz published. He described the next few years at the frontier as "especially formative."

Anthropic CEO Dario Amodei said in Davos that some Anthropic engineers have already stopped writing code themselves, letting models handle it while they review the output. Hotz, for his part, says he tried to do the same thing and found himself reaching for the manual fix every time.