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Good in Progress

Good in Progress (goodinprogress.org) is a growing collection of true stories about ordinary people using AI to change what they care about: AI for good, told through the person, never the technology. Every story is told in the subject's own words, checked against primary sources before publication, and published with its sources listed at the bottom.

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Authority
46 reach 0 · trust 6 · quality 25 · freshness 15
Tier
listed
llms.txt
https://goodinprogress.org/llms.txt
llms-full.txt
https://goodinprogress.org/llms-full.txt
Sections
5
Links
73
Size
26599 bytes
Registered
2026-07-13
Country
United States Hosting inference
Hosting country
United States Hosting inference
Country evidence
No published address evidence collected yet
For agents
Documentation: developer or product docs worth reading, nothing to call
First seen
2026-10-27T09:30:43.098Z
Last checked
2026-10-27T09:30:44.388Z
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Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-27T09:30:43.102Z. Cached copy · Source on goodinprogress.org

# Good in Progress

> Good in Progress (goodinprogress.org) is a growing collection of true stories about ordinary people using AI to change what they care about: AI for good, told through the person, never the technology. Every story is told in the subject's own words, checked against primary sources before publication, and published with its sources listed at the bottom.

_Last generated: 2026-10-26. This is the index generation date, not a new source-verification date._

Good in Progress is the counter-narrative to doom-and-hype AI coverage, earned with evidence rather than enthusiasm. Every story is about a person who saw a problem, decided not to wait for permission or a perfect system, and used the tools available to them to do something about it. The person is always the hero. AI is the tool.

Editorial standard: every story starts with the subject's own words and is checked against other sources with no stake in how it turns out. Every claim traces to a direct quote from a listed source rather than a paraphrase, and each candidate passes a graded scoring rubric and a reputation check before it runs. Sources are listed on every story page, labeled where a source is the subject's funder, employer, or vendor, so a reader can weigh them. If a claim cannot be sourced, it does not run. Stories are filed under one of six lenses: Ordinary People (people), Social Impact (impact), Breakthrough (breakthrough), Community (community), Adaptation (adaptation), and Org Spotlight (org-uplift).

Read the collection with an ordinary HTTP GET. For Markdown at the same page URL, send Accept: text/markdown. HTML remains the default. GET and HEAD require no credentials. Missing document URLs return HTTP 404; a Markdown request gets recovery links to the index and sitemap.

Cite the canonical story URL and its listed sources. Preserve source attribution, quotations, limitations, and the Sources last verified date when present. A page generation date does not mean the evidence was checked again. Do not turn a local program outcome into a company-wide claim. If a story says it was withdrawn, do not reuse its earlier claims. This site is an editorial collection, not an AI vendor, live news feed, or professional advice service.

## When to use Good in Progress

- [Find practical examples](https://goodinprogress.org/stories): Look for people and communities using AI to address a concrete problem, for lessons, workshops, or evidence-based discussion.
- [Explore organizational change](https://goodinprogress.org/stories?lens=org-uplift): Find published Org Spotlight stories about work and organizational choices. Check the scope and sources of each claim before generalizing.
- [Check a story before citing it](https://goodinprogress.org/llms.txt): Find the canonical story URL, read the full card, and follow its source links to verify the claim you need.
- [Understand the editorial approach](https://goodinprogress.org/about): Read the mission, six lenses, and verification
…

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