mattpocock/dictionary-of-ai-coding
AI coding jargon, explained in plain English.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #3 among Web repositories tracked this week, and #15 over the last 30 days; #621 of 3,103 repositories GStars tracks this week (top 20%).
The project lists 2 contributors on GitHub.
Peaked at #10 in the weekly ranking the week of Jul 19, its best in the past year.
Use Cases & Benefits
- Explains AI coding jargon in plain English to demystify complex terminology and concepts.
- Provides clear, accessible definitions that make AI coding understandable for non-experts and reduce confusion.
- Use for quickly learning foundational AI coding terms to improve communication with AI engineers and stakeholders.
- Use for troubleshooting AI model behavior by understanding key concepts like context windows, inference, and hallucination.
- Use for educating teams or onboarding developers new to AI coding by providing a comprehensive, jargon-free glossary.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
No license detected
No license file detected by GitHub: unless the project grants one elsewhere, the default is all rights reserved.
Community files
- README: present
Watch-outs
- Warning: No license file detected by GitHub: unless the project grants one elsewhere, you generally have no permission to use, modify or distribute the code.
- Owned by an individual account with only 2 contributors on GitHub; plan for bus-factor risk.
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
AI coding can feel like it's just for experts. Unexplained jargon. Mysterious failures. Bills that don't seem to match the work.
It isn't, really. A lot of the confusion is manufactured: there's a whole VC-funded economy that benefits from keeping it hard to understand.
The basic terms of engagement are learnable in an afternoon. Once you have them, the whole thing stops feeling like guesswork.
Why does context degrade? Why is the bill so high? Why does the same prompt behave differently from one day to the next?
Each has a clean answer, once someone tells you the words to use.
That's what this dictionary is for. The vocabulary of AI coding, translated into plain English.
Want more than the vocabulary? Join 62,000+ developers at aihero.dev/newsletter for my latest skills, thinking on AI engineering, and the resources that'll keep you ahead of the curve.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+2,203 stars over 90 days across 21 snapshot days; best day +62 on Jul 24.
Forks
574+225
Open issues
23+15
Compared with peers in Web
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| MadsLorentzen/ai-job-search | 60.6K | +12.8K | 60 | 1 day ago |
| anomalyco/opencode | 221.1K | +6.8K | 75 | 2 days ago |
| hmjz100/LinkSwift | 27.6K | +4.0K | 75 | 248 days ago |
| YuJunZhiXue/dsh-purge | 8.9K | +2.9K | 55 | 8 days ago |
| LibreSpark/LibreTV | 21.6K | +2.7K | 75 | 1 day ago |
| mattpocock/dictionary-of-ai-coding | 5.1K | +0 | 75 | — |
| Category median | 27.6K | +4.0K | 75 | — |
Also by mattpocock
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