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90% of Code Written by AI: What Product Changes

Mike Krieger
Chief Product Officer, Anthropic
Co-founder, Instagram
JAN 2025
The Shift

From 0% to 90% AI-Generated Code

CODE GENERATION GROWTH
"The team that works in the most futuristic way is the Claude Code team. They're using Claude Code to build Claude Code in a very self-improving kind of way. Probably over 70% of pull requests are Claude Code generated now."
  • From zero to 70% AI-written code at Anthropic in months
  • Claude Code team uses Claude to build Claude — self-improving architecture
  • Over half of all pull requests are now AI-generated
  • The codebase itself became the experimental ground for AI development
New Bottlenecks

What Changes When Code Writes Itself

IDEATIONCODEMERGEDECISIONEXECUTIONDEPLOYMENT
  • Decision bottleneck: Deciding what to build and aligning everyone faster than engineers can code
  • Merge bottleneck: Infrastructure can't keep up with volume of pull requests
  • Review complexity: Line-by-line reviews impossible; need Claude-to-Claude review instead
70%+
PRs AI-generated
100%
faster iteration
The key insight

Engineers are no longer the constraint. Decision-making, alignment, and infrastructure are. The entire development process must be re-architected.

What Changed

PMs, Designers & Engineers in the Age of AI Coding

  • Designers now prototype: PMs and designers use Claude + Artifacts to build functional demos before engineering even starts
  • Earlier visibility: What used to take weeks to validate takes hours — then review happens much faster
  • Role shift: Engineers focus on architecture, prompt composition, backend/frontend decisions — not typing code
  • Review reimagined: Claude Code team uses Claude to review PRs instead of line-by-line human review
The hidden skill

Knowing what to ask the AI, how to compose a question, how to structure a change — these are now the specialized skills that still require experienced engineers.

New priority: strategy

"I need to provide the minimum viable strategy to let people feel empowered to go run and type and build at the edge of model capabilities." — Mike Krieger

Playbook

Build for AI Velocity

  • Empower with minimal strategy, not detailed specs — let AI and teams explore
  • Re-architect your merge queue and deployment infrastructure immediately
  • Use Claude-to-Claude for code review, human acceptance testing for validation
  • Hire founding engineers with strong opinions, not just individual contributors
  • Change your conception of software building every 6–12 months; don't hold on to old processes
The future playbookA year from now, the way we conceive of building and shipping software will be radically different. Trying to do this the old way will become very painful.
Contrarian

AI + Engineering Myths

AI means engineers do less workINSTEAD →Engineers shift to harder problems: architecture, decision-making, and guiding AI. The work gets deeper, not lighter.
Prompting is a junior skillINSTEAD →Composing the right question for AI is a highly specialized, senior engineering skill. It directly determines quality.
You need way more engineersINSTEAD →You need fewer, but stronger founding engineers paired with great product and design. One strong person + AI is more powerful than before.
Product process stays the sameINSTEAD →Everything changes: how you spec, how you review, how you deploy, who decides what to build. It's a complete reset.
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