Introducing wrapture
- ID
- 20051
- Status
- summarized
- Published
- 01 Sep 2026, 7:59 AM
- Fetched
- 01 Sep 2026, 9:09 AM
- Provider
- Simon Willison
- Category
- developer-ai
- Original URL
- https://simonwillison.net/2026/Aug/31/introducing-wrapture/
- Source URL
- https://simonwillison.net/atom/everything/
Summary
- Score
- 6.5
- Created
- 01 Sep 2026, 9:09 AM
- Tags
- Audience
- developersvibe_codersai_agent_users
What happened
Graham Dumpleton, creator of wrapt and mod_wsgi, released 'wrapture,' a young Python library that extends wrapt's monkeypatching concepts to both testing and tracing simultaneously, serving as an alternative to unittest.mock with OpenTelemetry support and a config-based tracing mechanism. Notably, every line of code and documentation was written by an AI assistant under Graham's direction, which he explicitly distinguishes from 'vibe coding'—he engineered the design himself and used AI as the production means, not the design source.
Why it matters
If you write Python, wrapture offers a concrete alternative to unittest.mock that also doubles as a tracing tool with OpenTelemetry support—worth evaluating for projects where you need to observe or override functions in code you don't control. More broadly, Graham's explicit distinction between agent-driven development with engineering rigor versus vibe coding is a useful framing if you're deciding how to deploy AI agents in your own build process: the takeaway is that AI-as-production-tool works when you already know exactly what the result should be, not when you're hoping the output is correct.
Discussion angle
Graham's line between 'I engineered this carefully and AI was the means of production' versus vibe coding is a practical test for your own AI-assisted work: do you have the domain knowledge to judge every line the agent produced, or are you trusting output you can't evaluate?