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.
The article reflects on the shift in perspective after the release of Fable, a new model that promised to solve many coding challenges at a comparable or lower cost. Prior to Fable, developers felt it was pointless to invest heavily in coding tools or context strategies, as newer models would likely render them obsolete. However, Fable’s performance was so impressive that, despite its high cost, it prompted a reevaluation of how work was distributed across different models such as Opus, 5.6, K3, and GLM.
SF October 14th: A Birds of a Feather Session on Agentic Engineering
I'm hosting an evening event with Jesse Vincent in San Francisco on Wednesday 14th October for people who are building weird and in...
But then users start to report a weird bug. It's the 4th time your team has been trying to fix it.
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 reflects on the emotional impact of AI tools that can produce code quickly, noting that many developers experience an initial sense of disheartenment. He argues that recognizing the shift from coding to higher‑level problem solving allows experienced engineers to leverage new tools and add greater value. Willison emphasizes that software engineering has always faced rapid change, so adapting to AI is part of the profession’s ongoing evolution.