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codex · operators · Cat Wu · ins_remove-features-as-models-improve

When a new model lands, re-read the system prompt and remove crutches

By Cat Wu · Head of Product, Claude Code + Co-work, Anthropic · 2026-04-27 · podcast · How Anthropic's product team moves faster than anyone else — Lenny's Podcast

Tier A · TL;DR
When a new model lands, re-read the system prompt and remove crutches

Claim

Most features in an AI product are crutches for a model weakness. When a new model ships, the disciplined response is to re-read the entire system prompt and remove the sections the new model no longer needs. Counterintuitively, model launches are deletion events as much as addition events.

Mechanism

Scaffolding around a weakness encodes that weakness into the product. A todo-list step that exists because the old model stopped after 5 of 20 sites becomes friction once the new model handles all 20 natively. Leaving the scaffolding in place degrades the experience and trains users to think the AI is dumber than it is. Removing it surfaces the new capability immediately.

Conditions

Holds when:

Fails when:

Evidence

"A lot of the changes with a new model is removing features that are no longer needed."

The to-do list inside Claude Code was added because Claude would stop after 5 of 20 refactor sites. Opus 4 made the 20-site loop natural; the to-do list is now de-emphasized. Every new model launch, Cat's team re-reads the full system prompt and cuts what is no longer needed.

— Cat Wu on Lenny's Podcast, 2026-04-27

Signals

Counter-evidence

Removing a feature breaks workflows that depended on it, even if the model now does the work natively. Sherwin Wu's "models eat your scaffolding for breakfast" is the same shape but cuts both ways: it's a warning to not over-build the scaffolding in the first place, and a directive to remove it once obsolete. Aggressive removers without good change communication erode user trust faster than slow removers preserve it.

Cross-references

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