A route-planning experiment shows the practical ceiling of one-prompt AI work

Focus: Applied Generative AI for Knowledge Workers
Date: September 12, 2026
Topics: ChatGPT Work, research agents, interactive maps, human verification
Evidence: Practitioner Analysis
Availability: General Availability

Textbook city-map workflow with researched map data, 5K and 10K route loops, river and crossing constraints, uncertain segments to verify, distance checks, and an interactive-view output.

Summary: Simon Willison asked GPT-6 Astra in ChatGPT Work to research and build 5K and 10K running routes around San Francisco’s Marina, including an interactive D3 map. The system combined web research, geospatial data, code, and presentation in one run, producing a useful artifact but also route details that still required real-world checking.

Why it matters: The useful unit of work is no longer just a memo: an agent can research, compute, code, and publish an interactive decision aid. The experiment is one practitioner example, and route safety, closures, distance accuracy, and accessibility cannot be delegated to an attractive map without independent checks.

What to do now

Build one interactive explainer: Choose a real teaching or consulting question, require an interactive output, and predefine the facts a human must verify.

Source: Generating running routes with GPT-6 Astra and ChatGPT Work

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