[On using generative AI for work despite the risk of errors:]
- AI is helpful despite being error-prone if it is faster to verify the output than it is to do the work yourself. For example, if you're using it to find a product that matches a given set of specifications, verification may be a lot faster than search.
- There are many uses where errors don't matter, like using it to enhance creativity by suggesting or critiquing ideas.
- At a meta level, if you use AI without a plan and simply turn to AI tools when you feel like it, then you're unlikely to be able to think through risks and mitigations. It is better to identify concrete ways to integrate AI into your workflows, with known benefits and risks, that you can employ repeatedly.
Recent articles
- Highlights from my appearance on the Data Renegades podcast with CL Kao and Dori Wilson - 26th November 2025
- Claude Opus 4.5, and why evaluating new LLMs is increasingly difficult - 24th November 2025
- sqlite-utils 4.0a1 has several (minor) backwards incompatible changes - 24th November 2025