Simon Willison

Quoting voxium

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Simon Willison describes his experience at a large company where all documentation, code, tests, PRDs, tickets, and reports are generated by Claude Code. His team is forced to ship rapidly, working long hours, yet management insists that code push is not a bottleneck, leading to frustration and a lack of meaningful reading or review. The situation highlights a reliance on AI-generated content that may undermine quality and collaboration.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Simon Willison.

Simon Willison
Sep 14

Quoting Laurie Voss

Laurie Voss argues that while the cost of writing code has fallen dramatically, the costs of reviewing, fixing, and operating software are rising and will continue to do so. She emphasizes that the true expense lies in understanding user needs, precisely defining requirements, and ensuring a pleasant user experience—costs that are unique to each software product and do not scale with reuse. As software demand grows without an upper limit, these user‑centric costs will dominate the overall development effort.

Simon Willison
2d ago

Quoting Paul Ford

The article highlights Paul Ford’s observation that web browsers are extremely powerful for building applications, and the cost of leveraging that power is continually decreasing. It emphasizes the growing accessibility and affordability of browser-based development tools.

Simon Willison
Sep 12

Quoting Paul Ford

Simon Willison reflects on the evolving role of software developers in the age of AI, noting that while AI can produce high‑quality code, it also enables poor execution that leads to project failures. He argues that the industry is beginning to recognize the continued need for human collaboration and expertise to truly innovate. The piece highlights the tension between automation and the essential human element in software creation.

Simon Willison
Sep 11

Quoting Boris Cherny

The article discusses how production code generated by Claude, Anthropic’s AI, should meet higher standards than human-written code. Anthropic enforces this through numerous guardrails such as lint rules, extensive testing, Claude-driven end‑to‑end tests, daily fuzzers, automated code and security reviews, and automated refactoring. These measures aim to prevent the code from becoming difficult to maintain.

Simon Willison
6d ago

Quoting Kyle Kingsbury

The article discusses how large language models (LLMs) undermine trust in documentation, software, and the organizations that produce them, making it easier to counterfeit signals of a mature system. It questions what maintainers can do to ensure software correctness and accurate documentation in the age of LLMs, and how they can demonstrate this quality to users.