GPT-6 Astra in ChatGPT Work generates running routes from OSM data
Simon Willison tested ChatGPT Work with GPT-6 Astra (Max) to generate 5K and 10K running routes from his home using OpenStreetMap data. The tool worked for 27 minutes and produced the requested routes as embedded visualizations and downloadable GPX and GeoJSON files, but the underlying code was not visible in the UI. Willison criticized this lack of transparency as an anti-feature, noting that after thread compaction, ChatGPT could not provide the Python code it had used.
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Simon Willison
Here's a neat thing I had ChatGPT Work with GPT-6 Astra (Max) do this morning: I live at <my address>. Figure out 5K and 10K running routes from me that loop from my house. Use OSM data. It worked for 27 minutes and produced exactly what I'd asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here's that 5K route: When I asked it how it had created the route, it replied: I used Nominatim to locate the address and Overpass to download local OpenStreetMap roads and trails , then calculated the loops locally. Frustratingly, the actual code it ran and exact details of what it did weren't visible to me in the ChatGPT UI. I see this lack of transparency is an anti-feature. By the time I thought to ask for a copy of the Python code it had used, ChatGPT was unable to provide it. This appears to be because the thread had been compacted. I think any LLM system that uses compaction needs to both preserve the pre-compacted text and make that text available via
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