Hacker News

Article URL: https://www.wsj.com/politics/policy/trump-to-repeal-landmark-climate-finding-in-huge-regulatory-rollback-ff7d58db

Comments URL: https://news.ycombinator.com/item?id=46954496

Points: 5

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Article URL: https://github.com/contrario/aetherlang

Comments URL: https://news.ycombinator.com/item?id=46954284

Points: 1

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Article URL: https://reason.com/2026/02/09/a-goldilocks-effect-for-online-teens-moderate-social-media-users-fare-better-than-abstainers-or-heavy-users/

Comments URL: https://news.ycombinator.com/item?id=46954270

Points: 1

# Comments: 0

I built AICO, an open-source CLI framework built around the core slogan: Manage AI collaborators like managing employees. It turns AI tools/skills into dedicated role-based "AI employees" (PM, Frontend, Backend Engineer, etc).

This is an experimental side project, and over the past two months, I’ve built 2-3 full projects solo using the 3 pre-built roles, each with tailored skills/commands: PM, Frontend Engineer, Backend Engineer. All AI capabilities are role-aligned for real-world work (I’m trying to hit this goal).

1-line setup (pnpm/yarn/npm/bun): pnpm add -g @the-aico/cli && aico init && aico add pm

I’m sharing this just to get some feedback from the community, and I’d really love your input! What AI employee roles should I add next (DevOps? Data Scientist? UX Designer?)? What skills/commands are missing from the current PM/Frontend/Backend roles to make this more useful for your workflow?

Check it out: https://www.the-aico.com/

Would truly appreciate any of your thoughts, critiques and ideas!

Comments URL: https://news.ycombinator.com/item?id=46954262

Points: 1

# Comments: 0

Article URL: https://medicalxpress.com/news/2026-01-baby-headcams-reveal-babies-encounter.html

Comments URL: https://news.ycombinator.com/item?id=46954242

Points: 1

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

Comments URL: https://news.ycombinator.com/item?id=46954237

Points: 1

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Article URL: https://www.phoronix.com/news/Linux-7.0-Btrfs-Changes

Comments URL: https://news.ycombinator.com/item?id=46954214

Points: 1

# Comments: 0

Article URL: https://clawwatcher.com/

Comments URL: https://news.ycombinator.com/item?id=46954200

Points: 1

# Comments: 2

Article URL: https://reclaimthenet.org/the-lost-dog-that-made-constant-surveillance-feel-like-a-favor

Comments URL: https://news.ycombinator.com/item?id=46954195

Points: 1

# Comments: 0

Article URL: https://stackoverflow.blog/2026/02/09/why-demand-for-code-is-infinite-how-ai-creates-more-developer-jobs/

Comments URL: https://news.ycombinator.com/item?id=46954184

Points: 2

# Comments: 0

Article URL: https://www.theguardian.com/games/2026/feb/09/how-a-decades-old-video-game-has-helped-me-defeat-the-doomscroll

Comments URL: https://news.ycombinator.com/item?id=46954182

Points: 1

# Comments: 0

Looking to see how others have solved your business issues? Searching for creators with proven experience?

Just tell Humation AI your business problem. It scans public n8n templates to find the right tools and the experts who built them.

Comments URL: https://news.ycombinator.com/item?id=46954167

Points: 1

# Comments: 0

Article URL: https://www.cse.chalmers.se/~rjmh/Combinators/

Comments URL: https://news.ycombinator.com/item?id=46954159

Points: 1

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I built an autonomous research agent in C# that runs entirely on local LLMs via Ollama.

Give it a topic and it: generates diverse search queries, searches the web (Brave Search API, free tier), fetches and reads relevant sources, analyzes each source for key findings, and synthesizes a structured markdown report with citations.

Everything runs locally — no OpenAI/Anthropic API needed. Just Ollama + llama3.1:8b.

It takes about 15 minutes per research run on a mid-range CPU (Ryzen 5 5500, no GPU needed). Not fast, but it does the research while you do other things.

Tech stack: C#/.NET 8, Ollama, SQLite for semantic memory, Brave Search API.

Why C# instead of Python? Because .NET developers want AI tools too, and the ecosystem is underserved compared to LangChain/LlamaIndex.

Known limitations: CPU inference is slow (~15min/run), 8B models occasionally produce malformed tool calls (handled with retries), and research quality depends on Brave Search results for your topic.

I also made a starter kit if you want to build your own agent from scratch: https://github.com/DynamicCSharp/agentkit

Comments URL: https://news.ycombinator.com/item?id=46954141

Points: 1

# Comments: 0

Article URL: https://github.com/TrevorS/voxtral-mini-realtime-rs

Comments URL: https://news.ycombinator.com/item?id=46954136

Points: 1

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Article URL: https://k2xl.substack.com/p/the-first-time-i-visited-metas-headquarters

Comments URL: https://news.ycombinator.com/item?id=46954127

Points: 1

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- Live demo: https://compsult.github.io/Quickpick-ui/ - GitHub: https://github.com/compsult/Quickpick-ui

Comments URL: https://news.ycombinator.com/item?id=46954126

Points: 1

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Article URL: https://www.youtube.com/watch?v=Ru7BIqXQZns

Comments URL: https://news.ycombinator.com/item?id=46954123

Points: 2

# Comments: 0

Article URL: https://extended.reading.sh/ai-dot-com-crashes-on-superbowl

Comments URL: https://news.ycombinator.com/item?id=46954096

Points: 1

# Comments: 1

Article URL: https://jollycoder.com/posts/rise-of-the-cowboy-coder

Comments URL: https://news.ycombinator.com/item?id=46954080

Points: 1

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