Post by **Addy Osmani** on his Substack *Elevate*, published on **October 14, 2026**; ~1,900 words. Thesis: with current models, the bottleneck is no longer writing code but **verifying** its correctness; human work shifts from *"review every line"* to *"build loops the agent can run itself."*
Talk by **Eno Reyes** (co-founder and CTO of **Factory**, whose "droids" agents are described in the introduction as used by hundreds of thousands of developers and companies such as **Nvidia** and **MongoDB**, right after a **$150 million Series C**), published on **September 22, 2026** on the **FirstMark Capital** channel (25 min 51 s video, transcript of about 5,300 words). He presents the "software factory" as an agent-driven feedback loop, and the role of humans as stewards of this factory.
#software factory#software factory#Factory
Eno Reyes — cofondateur et CTO de Factory ; conférence vidéo (FirstMark Capital).
*Deepdive* by **Gergely Orosz**, **Jessica Salmon**, and **Ivan Klaric** in *The Pragmatic Engineer*, published on **August 25, 2026**, based on interviews with Ramp's CTO **Rahul Sengottuvelu**, head of engineering **Hamid Dadkhah**, and **Zach Bruggeman**, founding engineer of **Inspect**. Paywalled article: the note covers the public portion (sections 1 through 3 and the opening of section 4; detailed architecture, sandbox internals, and collaboration remain behind the paywall).
Long-form guide from **Anthropic** by **Louis Claxton** (Applied AI team), published on **August 21, 2026** on the claude.com blog: a stated **40-minute** read, roughly **64,000 characters**, presented as a collection of *plays* drawn from the team's work with its clients. (A) The diagnosis: with code no longer the bottleneck, it shifts to the stages on either side of the build (plan, review/test, deploy), line-by-line controls stop holding once the agent writes most of the diff, and governance cost rises as exceptions still route through periodic committees. (B) The response: six stages (Plan, Design, Build, Test, Deploy, Maintain) organized as a **loop** rather than a chain, each ending with a **committed artifact** that the next stage reads — `intent.md`, `spec.md`, `plan.md`, the diff and its tests, the PR and its findings, the incident record. (1) Institutional knowledge becomes versioned files: `CLAUDE.md`, skills, `REVIEW.md`, `bands.yaml`. (2) Governance splits into two layers, with the skill positioned as an advisory control and the hook as the deterministic layer behind it. Separation of duties is set as an invariant — the agent that writes the code cannot approve it — and the piece closes on *"The loop keeps running. Human judgement stays above it."* The corpus already holds [[clinton-anthropic-secure-ai-native-sdlc-2026-07-21]] on the security side of the same cycle, and [[hingel-augment-how-ai-changes-sdlc-six-stages-2026-06-08]] on the same six-stage breakdown as seen by a competitor.
#AI-native SDLC#software development lifecycle#plays
Louis Claxton (Anthropic, équipe Applied AI) · sur le blog claude.com ; contributions créditées à Jim Blackhurst · Will Steuk et Jamal Arif.
Philippe Ensarguet (Orange) argues that fifty years of design patterns form a continuous lineage: at a time when AI commoditizes code and breaks the traditional way architects are trained, "pattern literacy" (reading a system through its invariant forces) becomes the durable skill to teach — as a grammar, not as catalogues.