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| type | title | author | url | date_published | date_archived | domain | secondary_domains | status | processed_by | tags | sourced_via | twitter_id | ||||||
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| source | When AI Writes the World's Software, Who Verifies It? | Leonardo de Moura | https://leodemoura.github.io/blog/2026/02/28/when-ai-writes-the-worlds-software-who-verifies-it | 2026-02-28 | 2026-03-16 | ai-alignment |
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Alex Obadia (@ObadiaAlex) tweet, ARIA Research Scaling Trust programme | 712705562191011841 |
When AI Writes the World's Software, Who Verifies It?
Leonardo de Moura (AWS, Chief Architect of Lean FRO) argues AI-generated code is proliferating faster than verification can scale. Mathematical proof — not testing alone — becomes essential infrastructure.
Key evidence:
- Google: >25% of new code is AI-generated; Microsoft: ~30%. Microsoft CTO predicts 95% by 2030.
- Anthropic built 100,000-line C compiler using AI agents in 2 weeks for <$20,000
- "Nearly half of AI-generated code fails basic security tests"
- Poor software quality costs US economy $2.41T/year (CSIQ 2022)
Key arguments:
- Testing provides confidence but not guarantees. "A proof cannot be gamed."
- AI overfits test suites — Claude C Compiler "hard-codes values to satisfy the test suite" and "will not generalize"
- Supply chain attacks via poisoned training data can "inject subtle vulnerabilities into every system AI touches"
- Lean has become the de facto formal verification platform (AlphaProof, 200K+ formalized theorems, 5 Fields medalists)
- Morrison (Lean FRO) demonstrated AI-generated Lean implementation of zlib with mathematical proof of correctness
- "The barrier to verified software is no longer AI capability. It is platform readiness."
Directly relevant to formal verification of AI-generated proofs provides scalable oversight that human review cannot match because machine-checked correctness scales with AI capability while human verification degrades.