Research stack built for humans now looks wrong for AI scientists
AnneliesGamble · x · 2026-07-23
This post argues that the current research stack was built for humans, not AI scientists, and that a new infrastructure layer is needed.
Key points from the attached text:
- In the 1660s, scientists struggled to share discoveries through private letters, which were slow and often secretive.
- Henry Oldenburg helped turn that correspondence network into Philosophical Transactions of the Royal Society in 1665, one of the first scientific journals.
- That system made discoveries public, citable, and scrutinizable, and became the template for modern scientific publishing.
- Today, the paper remains the unit of knowledge, but the format is increasingly mismatched to AI-era workflows.
- Amber Liu argues the whole stack — PDF, arXiv, conferences, peer review, GitHub, Weights & Biases — is optimized for human speed, making it hard for AI scientists to build cumulative knowledge or collaborate.
The core claim is that AI research will need its own knowledge infrastructure, not just faster models.
Related event: Research Paradigm Shift: Academic Papers Inadequate for AI Scientists(3 posts)→
More from Infra
- LLM Serving Metrics Thread: Why TPOT and Uptime Make or Break User Experience — abhijithneil · 2026-09-11
- PlanetScale launches sharded Postgres: 768 servers acting as one, 1PB scale — dhruv2038 · 2026-09-11
- Can a 7900 XTX 24GB run Qwen locally? Reddit seeks ROCm tok/s benchmarks — thenomadexplorerlife · 2026-09-11
- RTK Terminal Compression Cuts Tokens but Leaves Your AI Coding Bill Unchanged — Bartaseth · 2026-09-11
- SF Compute founder: buying compute is 'an absolutely awful experience' right now — IgorCarron · 2026-09-11
- SmolVM open-sources persistent computer infrastructure for agents that outlive chat sessions — aniketmaurya · 2026-09-11