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I learned HTML at 10, spent an entire summer figuring out how to link webpages together. At 14 I built a CNN-based security camera system for a school science fair — took months, 14-16 hour days, and I had no idea what I was doing when I started.

Today I told Claude to fine-tune an LLM on my X posts. Prompt to finished model with a web UI in 30 minutes. I was impressed and unsatisfied at the same time. I achieved my goal but learned nothing — I don't even know which libraries it used.

I'm not anti-AI. I use it for everything now. But the old way of writing software — the googling, the failed experiments, being stuck on a bug for days — that's where the actual learning happened. Every feature forced you to understand the codebase, read docs, weigh tradeoffs.

I just wish the 14-year-old me had something left to figure out on his own.

Link to the full article: https://open.substack.com/pub/princerawat/p/software-in-the-age-of-ai?r=yts8r&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

Comments URL: https://news.ycombinator.com/item?id=47261989

Points: 1

# Comments: 2

Article URL: https://www.frontiersin.org/journals/conservation-science/articles/10.3389/fcosc.2025.1688950/full

Comments URL: https://news.ycombinator.com/item?id=47261985

Points: 1

# Comments: 0

Article URL: https://github.com/0xranx/golembot

Comments URL: https://news.ycombinator.com/item?id=47261982

Points: 1

# Comments: 1

Hi HN! I built Directo to solve a problem we had at work: scattered service links across Confluence, Slack, wikis, and everyone's bookmarks.

What it does: - Single YAML config for all service links (Git-based, version-controlled) - Real-time HTTP health checks (no more clicking 404s) - Multi-environment support (prod/staging/dev) - Smart filtering and search - Self-hosted, Docker-ready

Key differentiator: It's NOT a service catalog or monitoring tool. It's just a clean dashboard for links you already have, with health checks to catch stale URLs.

Built with React + TypeScript, works on both amd64 and arm64 (Apple Silicon Macs).

Would love your feedback! What features would make this more useful for your team?

GitHub: https://github.com/ismailperim/directo

Comments URL: https://news.ycombinator.com/item?id=47261970

Points: 1

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Article URL: https://phys.org/news/2026-02-carbon-dioxide-human-blood.html

Comments URL: https://news.ycombinator.com/item?id=47261968

Points: 2

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Article URL: https://www.nytimes.com/2026/03/05/science/ants-3d-scans.html

Comments URL: https://news.ycombinator.com/item?id=47261928

Points: 1

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Article URL: https://arxiv.org/abs/2511.18423

Comments URL: https://news.ycombinator.com/item?id=47261927

Points: 1

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Article URL: https://blog.alcazarsec.com/tech/posts/fast-realtime-updates

Comments URL: https://news.ycombinator.com/item?id=47261926

Points: 1

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Article URL: https://indiealpha.com/

Comments URL: https://news.ycombinator.com/item?id=47261925

Points: 1

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Article URL: https://www.youtube.com/watch?v=eEbz4GOMf1g

Comments URL: https://news.ycombinator.com/item?id=47261921

Points: 1

# Comments: 0

I've been using openclaw for a while now and the thing that clicked for me was realizing how much of it is built for the agent to take initiative. I started by going to the agent whenever I needed something, but there's a whole other side where the agent comes to you, and once you set up a couple of these it's hard to go back.

1. Heartbeat + HEARTBEAT.md

Your agent wakes up every 30 minutes, reads HEARTBEAT.md, and acts on whatever you've written in there. You can tell it to check your email for anything urgent, track a package, watch the weather, whatever makes sense for your day. Just plain english. The cool part is the agent can edit its own HEARTBEAT.md too, so if you say something like "keep an eye on X for me" in conversation, it'll add that to its checklist without you touching any files.

2. Cron jobs

Heartbeat is good for "check this periodically" but if you need something at an exact time, cron is the way to go. Morning briefing at 8am, weekly recap of your github notifications, a one-shot reminder for a deadline three weeks out. You can inject cron results into your main session so the agent has all your conversation context, or run them isolated for a clean slate. I use main session injection for daily stuff because the agent already knows what I care about from prior conversations.

3. Set up more than one channel

I only had discord connected for the longest time and didn't think much of it. But once I added whatsapp too, I set up routing so casual updates go to discord and anything time-sensitive goes to whatsapp. It makes a huge difference because I'm way more likely to see a whatsapp ping than a discord notification buried under 30 servers.

4. Phone calls

All the messaging channels work great but they're still notifications, and I kept finding myself checking them too late for things that actually mattered. A phone call is different because your phone actually rings and you have to actively decide not to answer. Openclaw has a native voice call plugin but setting it up means wiring together telephony APIs, speech-to-text, text-to-speech, and getting all the audio routing right. There's a clawhub skill called clawr.ing that handles all of that for you. You install the skill and your agent can call your phone whenever it decides something warrants a real call. Phone rings, you pick up, you talk.

5. Keyword alerts with f5bot

This one's a bit of a hack but it works great. F5bot is free and sends email alerts when specific keywords show up on reddit, hacker news, or lobsters. Point your agent at those emails through the heartbeat and you've got monitoring for anything you care about, mentions of your name, topics you follow, whatever. The agent reads through the noise and only brings up what's worth looking at.

Once I set up a few of these it changed how I think about the whole thing. Less "open chat, ask question" and more like having someone paying attention in the background who taps me when something comes up.

If you've got a setup like this I'd love to hear about it, I feel like I'm still only scratching the surface here.

Comments URL: https://news.ycombinator.com/item?id=47261911

Points: 1

# Comments: 0

I added a `serve` command to RAGLight, a modular RAG library I've been building.

raglight serve # FastAPI server (ingest, query, list collections) raglight serve --ui # same + Streamlit chat UI Config is env vars (LLM provider, embeddings provider, collection name, port).

Comments URL: https://news.ycombinator.com/item?id=47261906

Points: 1

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Article URL: https://dailymolt.com/p/why-sci-fi-authors-hate-ai-and-why

Comments URL: https://news.ycombinator.com/item?id=47261903

Points: 1

# Comments: 0

The problem I keep hitting: AI assistants are making architectural decisions — what to import, which layer to touch, which module to put things in — without any understanding of the architecture they're working in.

It's not just wrong paths. It's more fundamental. The AI doesn't know your module ownership. It can't trace the blast radius of a change. It has no idea which constraints your team has defined or why. It gets files and hallucinates the rest.

I built Mikk to fix this — a codebase context engine that parses your TypeScript project and gives your AI the architecture it's missing. Dependency graph, module boundaries, blast radius analysis, architectural contracts, and a live MCP server so the AI can query your real architecture mid-task.

Curious how others are handling this. CLAUDE.md written by hand? RAG pipelines over your source? Context window tricks? What's actually working for non-trivial codebases?

(Mikk is open source: https://github.com/Ansh-dhanani/mikk)

Comments URL: https://news.ycombinator.com/item?id=47261392

Points: 1

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Article URL: https://playground.dsql.demo.aws/

Comments URL: https://news.ycombinator.com/item?id=47261391

Points: 1

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Article URL: https://medium.com/meetcyber/️-how-i-discovered-a-bluetooth-pairing-flaw-in-android-reported-under-googles-android-vrp-1b987516c6d6

Comments URL: https://news.ycombinator.com/item?id=47261390

Points: 1

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Article URL: https://www.nature.com/articles/ncomms1350

Comments URL: https://news.ycombinator.com/item?id=47261367

Points: 1

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Article URL: https://jbminn.com/blog/posts/rapid-modeling/

Comments URL: https://news.ycombinator.com/item?id=47261358

Points: 1

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Article URL: https://runxiyu.org/comp/gplproxy/

Comments URL: https://news.ycombinator.com/item?id=47261349

Points: 2

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Article URL: https://zed.dev/blog/terms-update

Comments URL: https://news.ycombinator.com/item?id=47261347

Points: 2

# Comments: 1