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louisfb01/ai-engineering-cheatsheets

Give you decision-ready references for the most common AI engineering problems

Latest metrics (snapshot 2026-10-15)

stars354
forks79
issues0
pushed_at2026-08-04T13:11:47Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-15354

ADC Momentum: 26/100

ADC Momentum 26 Leaderboard

Growth velocity42
Consistency34
Recency3
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionGive you decision-ready references for the most common AI engineering problems
urlhttps://github.com/louisfb01/ai-engineering-cheatsheets
topicsagent
agentic-ai
agentic-ai-development
agents
ai
ai-agents
ai-engineer
ai-engineering
llm
llm-agent
created_at2026-03-12T18:05:22Z
homepagehttps://academy.towardsai.net/?ref=1f9b29

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