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I'm a hardware engineer who reads schematics, not source code. I kept needing to understand codebases for projects I was managing but couldn't read the syntax. So I built a tool that turns any codebase into an interactive visual map with plain English explanations.

Point it at a folder, get nested colored blocks showing the structure (directories → files → classes → functions). Click to drill down. AI generates summaries written for humans, not programmers. Architecture mode shows a dependency graph so you can see how modules connect.

Built the whole thing in ~30 hours using a multi-node AI workflow: Claude for planning/decisions, Claude Code for implementation, five other models for adversarial security review (42 fixes across 6 rounds). I made every design decision; AI wrote every line of code.

Cloud AI (OpenAI/Groq) or local AI (Ollama) — your choice. pip install codedocent and run the setup wizard.

MIT licensed. Would love feedback from people who actually write code — does this help when onboarding onto unfamiliar codebases?

Comments URL: https://news.ycombinator.com/item?id=47083260

Points: 2

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Article URL: https://news.mit.edu/2026/exposing-biases-moods-personalities-hidden-large-language-models-0219

Comments URL: https://news.ycombinator.com/item?id=47083252

Points: 1

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Article URL: https://www.cnbc.com/2026/02/19/trump-kennedy-glyphosate-maha-midterms-rfk-jr.html

Comments URL: https://news.ycombinator.com/item?id=47083231

Points: 2

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Article URL: https://economist.com/science-and-technology/2026/02/18/brain-like-computers-could-be-built-out-of-perovskites

Comments URL: https://news.ycombinator.com/item?id=47083226

Points: 2

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Article URL: https://djdumpling.github.io/2026/01/31/frontier_training.html

Comments URL: https://news.ycombinator.com/item?id=47083221

Points: 1

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Article URL: https://github.com/nullclaw/nullclaw

Comments URL: https://news.ycombinator.com/item?id=47083200

Points: 1

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Hi HN!

I’m building Antenna, a Mac app to manage an OpenClaw team in one place. If you run multiple agents, it gets messy fast: scattered chats, unclear command approvals, and poor visibility into what happened where. Antenna is my attempt to make that operationally sane.

Right now I’m focused on three things: seeing conversations across agents in one UI, approving commands safely, and keeping sessions manageable as context grows.

I’m currently testing better visibility into usage/context per session, smoother coding/review workflows, and lightweight controls that reduce complexity instead of adding more.

This is early and moving quickly. I’d really value feedback on: what would make this trustworthy enough for daily use, what’s missing for teams running multiple agents, and what would stop you from adopting it.

Comments URL: https://news.ycombinator.com/item?id=47083199

Points: 1

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Over the past 6 months, our small team has been building Qeeebo — a large-scale question-and-answer knowledge archive designed to explore whether massive knowledge corpora can be published sustainably using fully static infrastructure.

This month, we are releasing:

• 150+ million structured questions • 24.5 million topics • 171 million topic-question relationships • 18+ million paginated topic pages • 100% pre-rendered static HTML • No origin servers — served entirely via CDN

Each question includes: – A full answer – A summary – Structured citation formats (APA, MLA, Chicago, IEEE, etc.) – Export formats (BibTeX, RIS, JSON-LD, YAML)

The entire system is generated in independent segments (~45k pages each), built across parallel machines running Hugo, then uploaded via automated multi-threaded pipelines with full failure tracking.

Why build this?

Large Q&A platforms historically struggled with sustainability — especially when operating on database-backed, dynamically rendered systems. We wanted to explore whether extreme-scale static generation could reduce infrastructure cost while increasing long-term durability.

This isn’t positioned as a replacement for Wikipedia or Stack Overflow. Instead, it’s an experiment in permanence and cost-efficient knowledge hosting at very large scale.

Happy to answer technical questions.

Comments URL: https://news.ycombinator.com/item?id=47083185

Points: 2

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Article URL: https://venturecrane.com/articles/agent-context-management-system/

Comments URL: https://news.ycombinator.com/item?id=47083175

Points: 1

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Article URL: https://gist.github.com/rjcorwin/296885590dc8a4ebc64e70879dc04a0f

Comments URL: https://news.ycombinator.com/item?id=47083166

Points: 1

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Hey HN, I’m the founder of SalaryScript, and I wanted to share a project I’ve been working on for over a year: a comprehensive negotiation playbook tailored specifically for big tech roles.

I’ve navigated the FAANG hiring gauntlet multiple times myself, with stints at FAANG companies, so I know firsthand how opaque and high-stakes these negotiations can be. I wrote SalaryScript based on my experience, insights from a dozen FAANG-alumni colleagues, and lessons from recruiters I’ve worked with over the years. We’ve pooled perspectives from engineers, PMs, and execs who’ve collectively negotiated millions in total compensation.

Think of it as a “golden rule” book for tech negotiations. It covers everything from decoding offer letters and leveraging competing offers to scripting responses for common recruiter tactics, handling equity cliffs, and navigating relocation packages. No fluff — just battle-tested scripts, templates, and strategies that have helped people increase their total comp by 30–50% on average.

One contributor, a former Meta engineering manager, shared how he turned a $300K offer into $550K by reframing the RSU vesting conversation. Another, an ex-Apple product lead, broke down the psychology of why “total comp” framing often beats focusing on base salary alone.

Since launching last year at an introductory price of $19, we’ve crossed 1,000+ downloads and sales. Demand has been strong, and as word has spread, we’ve gradually raised the price.

If you’re prepping for interviews or staring at an offer right now, this might be the edge you need.

If you’re interested, you can check it out at salaryscript.com.

Would love your thoughts, war stories, or questions like what’s the biggest negotiation win (or fail) you’ve had in tech?

Cheers

Comments URL: https://news.ycombinator.com/item?id=47083163

Points: 1

# Comments: 0

The DOJ released ~3.5M pages of Epstein documents across 12 datasets. Buried in them are 207 academic papers and 14 books that nobody was really talking about. From what I understand these papers aren't usually freely accesible, but since they are public documents, now they are.

I don't know, thought it was interesting to see what this dude was reading. You can check it out at jeescholar.com

Pipeline: 1. Downloaded all 12 DOJ datasets + House Oversight Committee release 2. Heuristic pre-filter (abstract detection, DOI regex, citation block patterns, affiliation strings) to cut noise 3. LLM classifier to confirm and extract metadata 4. CrossRef and Semantic Scholar APIs for DOI matching, citation counts, abstracts 5. 87 of 207 papers got DOI matches; the rest are identified but not in major indexes Stack: FastAPI + SQLite (FTS5 for full-text search) + Cloudflare R2 for PDFs + nginx/Docker on Hetzner. The fields represented are genuinely iteresting: there's a cluster of child abuse/grooming research, but also quantum gravity, AGI safety, econophysics, and regenerative medicine. Each paper links back to its original government PDF and Bates number. For sure not an exhaustive list. Would be happy to add more if anyone finds them.

Comments URL: https://news.ycombinator.com/item?id=47083160

Points: 2

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Article URL: https://github.com/Citedy/seo-roast

Comments URL: https://news.ycombinator.com/item?id=47083149

Points: 2

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Article URL: https://www.microsoft.com/en-us/security/blog/2026/02/19/running-openclaw-safely-identity-isolation-runtime-risk/

Comments URL: https://news.ycombinator.com/item?id=47082933

Points: 1

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hey, have we (collectively) examined Apollonius circles vs the three-body problem? like via motivic geometry over dynamic parameterization?

Comments URL: https://news.ycombinator.com/item?id=47082926

Points: 1

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Article URL: https://coyotetracks.org/blog/ai-work-vs-stuff/

Comments URL: https://news.ycombinator.com/item?id=47082905

Points: 1

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Article URL: https://moontoprint.com/

Comments URL: https://news.ycombinator.com/item?id=47082876

Points: 1

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Article URL: https://bsky.app/profile/alexbenzer.com/post/3mfauv2c3gk2u

Comments URL: https://news.ycombinator.com/item?id=47082872

Points: 1

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Article URL: https://arstechnica.com/tech-policy/2026/02/wikipedia-might-blacklist-archive-today-after-site-maintainer-ddosed-a-blog/

Comments URL: https://news.ycombinator.com/item?id=47082870

Points: 2

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Article URL: https://basta.substack.com/p/the-imminent-risk-of-vibe-coding

Comments URL: https://news.ycombinator.com/item?id=47082867

Points: 1

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