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AI 资讯

I Kept Losing the "Why" Behind My Code Every Time I Closed an AI Chat, So I Built a Tiny Tool to Save It

Last Tuesday I was deep in a session with an AI assistant, rewriting a caching layer that had been quietly leaking memory in production. We tried Redis first. It worked. Then I looked at the actual data volume (about 50MB, tops) and killed the idea, because spinning up a whole service to cache 50MB felt absurd. We landed on sqlite instead. Good call, I still think. Two days later a teammate opened the branch, saw cache_sqlite.py sitting next to a deleted cache_memory.py , and asked why we weren't just using Redis like the rest of our stack. I didn't have a good answer ready. The reasoning had lived entirely inside a chat session that was long gone by then. I remembered making the decision. I could not reconstruct it convincingly, and "trust me, we talked about it" is not a great answer to give a teammate, or future me, three months from now. That's the part most tooling misses with AI-assisted coding. The code survives. The diff survives. A wave of AI memory tools is racing to store more of what the code does , and a few (Selvedge, presence) are starting to chase the why too, which tells me the pain is real. But almost all of them are MCP servers you have to wire into a specific agent, with a database sitting beside your repo. What I wanted was dumber and more portable: the reasoning, and the approaches I tried and threw out, written in plain text I can read, next to the code, no matter which editor or agent produced it. Because that reasoning lives in a chat window, and chat windows end. You switch from Claude Code to Cursor, or you just close the laptop, and it's gone. The facts stay. The judgment behind them evaporates. This didn't feel like a hard problem, so I built a small thing called Alpheon to fix it for myself, the simplest possible version: one Python file, no server, no database , works off git so it doesn't care what editor or agent you use. Facts vs. reasoning Here's the distinction that clicked for me. A fact is "cache.py was modified, cache_sqlite.py

2026-07-17 原文 →
AI 资讯

Commit Cron: A Simple Daily Commit Bot with GitHub Actions

I built Commit Cron , a small GitHub Actions experiment that creates one automated commit every day. The project updates a text file with the latest execution time, commits the change using the github-actions[bot] account, and pushes it back to the repository. View the project on GitHub: Commit Cron How It Works The workflow runs every day at 10:00 AM Asia/Manila time. on : schedule : - cron : " 0 10 * * *" timezone : " Asia/Manila" workflow_dispatch : The workflow_dispatch trigger also lets me run the workflow manually from the GitHub Actions tab. The workflow checks out the repository, creates the bot directory when needed, and updates bot/last-run.txt : mkdir -p bot printf "Last automatic update: %s \n " \ " $( TZ = Asia/Manila date '+%Y-%m-%d %H:%M:%S %:z (Asia/Manila)' ) " \ > bot/last-run.txt The file contains a timestamp similar to: Last automatic update: 2026-07-17 10:03:24 +08:00 (Asia/Manila) After updating the file, the workflow configures the GitHub Actions bot identity and creates the commit: git config user.name "github-actions[bot]" git config user.email \ "41898282+github-actions[bot]@users.noreply.github.com" git add bot/last-run.txt git commit -m "chore: daily automated update" Before pushing, it pulls the latest branch changes with rebase: git pull --rebase origin " ${ GITHUB_REF_NAME } " git push origin "HEAD: ${ GITHUB_REF_NAME } " This helps prevent the push from failing when another commit is added while the workflow is running. Repository Structure . ├── .github/ │ └── workflows/ │ └── daily-commit.yml ├── bot/ │ └── last-run.txt ├── LICENSE └── README.md Why I Built It Commit Cron is a small demonstration of: Scheduled GitHub Actions workflows Manual workflow triggers Automated file updates Bot-generated Git commits Repository write permissions using GITHUB_TOKEN The workflow uses: permissions : contents : write This allows the built-in GitHub token to push the generated commit. Important Note The automated commits only confirm that the work

2026-07-17 原文 →
开源项目

🔥 PostHog / posthog - 🦔 PostHog is an all-in-one developer platform for building s

GitHub热门项目 | 🦔 PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, data warehouse, a CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack. | Stars: 35,625 | 58 stars today | 语言: Python

2026-07-16 原文 →
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