Show HN: Commit-based code review instead of PR-based https://ift.tt/urziSPH

Show HN: Commit-based code review instead of PR-based Hi HN, I’m experimenting with commit-based code review as an alternative to PR-based review. Instead of analyzing large PR diffs, this reviews each commit incrementally, while context is still fresh. It’s fully configurable and intentionally low-noise, high signal - focused on catching issues that tend to slip through and compound over time. The goal isn’t to replace CI or PR review, but to move some feedback earlier: risky changes hidden in small diffs architectural or consistency drift performance or security footguns Happy to answer questions https://commitguard.ai January 9, 2026 at 03:03AM

Show HN: Layoffstoday – Open database tracking for 10k Companies https://ift.tt/6YG4uxV

Show HN: Layoffstoday – Open database tracking for 10k Companies Hi HN, I built Layoffstoday, an open platform that tracks tech layoffs across ~6,500 companies. What it does: Aggregates layoff events from public news sources Normalizes data by company, date, industry, and affected headcount Shows historical patterns instead of isolated headlines Why I built it: During job transitions, I noticed people had to jump across news articles, spreadsheets, and social posts just to answer simple questions like “Has this company laid people off before?” or “Is this happening across the industry?” This is an attempt to make that information structured, searchable, and accessible. Would love feedback on: Data accuracy / gaps Signals that would actually help job seekers Whether alerts or trend indicators are useful or noisy https://ift.tt/f8gJ01A January 9, 2026 at 12:39AM

Show HN: Executable Markdown files with Unix pipes https://ift.tt/WzoNU8g

Show HN: Executable Markdown files with Unix pipes I wanted to run markdown files like shell scripts. So I built an open source tool that lets you use a shebang to pipe them through Claude Code with full stdin/stdout support. task.md: #!/usr/bin/env claude-run Analyze this codebase and summarize the architecture. Then: chmod +x task.md ./task.md These aren't just prompts. Claude Code has tool use, so a markdown file can run shell commands, write scripts, read files, make API calls. The prompt orchestrates everything. A script that runs your tests and reports results (`run_tests.md`): #!/usr/bin/env claude-run --permission-mode bypassPermissions Run ./test/run_tests.sh and summarize what passed and failed. Because stdin/stdout work like any Unix program, you can chain them: cat data.json | ./analyze.md > results.txt git log -10 | ./summarize.md ./generate.md | ./review.md > final.txt Or mix them with traditional shell scripts: for f in logs/\*.txt; do cat "$f" | ./analyze.md >> summary.txt done This replaced a lot of Python glue code for us. Tasks that needed LLM orchestration libraries are now markdown files composed with standard Unix tools. Composable as building blocks, runnable as cron jobs, etc. One thing we didn't expect is that these are more auditable (and shareable) than shell scripts. Install scripts like `curl -fsSL https://bun.com/install | bash` could become: `curl -fsSL https://ift.tt/owP4YXZ | claude-run` Where install.md says something like "Detect my OS and architecture, download the right binary from GitHub releases, extract to ~/.local/bin, update my shell config." A normal human can actually read and verify that. The (really cool) executable markdown idea and auditability examples are from Pete Koomen (@koomen on X). As Pete says: "Markdown feels increasingly important in a way I'm not sure most people have wrapped their heads around yet." We implemented it and added Unix pipe semantics. Currently works with Claude Code - hoping to support other AI coding tools too. You can also route scripts through different cloud providers (AWS Bedrock, etc.) if you want separate billing for automated jobs. GitHub: https://ift.tt/4oN3fTE What workflows would you use this for? January 8, 2026 at 11:29PM

Show HN: Lean4 proof that SSOT requires definition-time hooks and introspection https://ift.tt/k9b23Mv

Show HN: Lean4 proof that SSOT requires definition-time hooks and introspection I formalized the Single Source of Truth (SSOT) principle in Lean 4 (~2.1k LOC, zero sorry) and proved two core results: Structural SSOT is achievable only when a language provides definition-time hooks and runtime introspection. Macros/codegen (before definition) and reflection (after definition) are insufficient. These requirements are derived, not chosen: because structural facts are fixed at definition, derivation must occur at definition time and be introspectable to verify DOF = 1. Would appreciate review, critique, or independent checking of the Lean scripts. https://ift.tt/wLHDhd5 January 8, 2026 at 02:15AM

Show HN: IceRaidsNearMe – Real-time, crowdsourced map of immigration enforcement https://ift.tt/vdZXR0b

Show HN: IceRaidsNearMe – Real-time, crowdsourced map of immigration enforcement I built this to provide transparency around enforcement activities. It uses [mention tech stack, e.g., Mapbox/Leaflet] and a verification system to prevent false positives. Feedback on the verification logic is welcome. https://ift.tt/WRckxiP January 8, 2026 at 12:30AM

Show HN: Cited AI – AI answers with citations linking to exact source passages https://ift.tt/pTPn1is

Show HN: Cited AI – AI answers with citations linking to exact source passages Hey HN! I’m Collin, a 20 year old law student from Amsterdam. I built Cited AI, an AI that gives accurate and verifiable answers from your documents/context. As a law student who uses AI a lot, I know how important it is that answers are actually accurate and verifiable. I remember many instances where I'd ask a chatbot like ChatGPT or Claude about case law or long documents, and it would either hallucinate facts that didn't exist, or fail to give me the exact passages from my source documents so I could verify its answers. Even when specifically asking for exact quotes, finding that passage in the original document is still a hassle. That's why last November I started building Cited. It should work with all types of content, complex PDFs (including math heavy ones) and long documents up to 75k words. No RAG or chunking is used, to make sure the full document is in the LLM's context. I would love to hear your feedback! https://getcitedai.com January 7, 2026 at 09:31AM

Show HN: A RAM-only, end-to-end encrypted P2P terminal chat in Python https://ift.tt/1LcNCsq

Show HN: A RAM-only, end-to-end encrypted P2P terminal chat in Python Hi HN, This is cmd-chat, a Python terminal chat app designed around a few constraints: - No central servers - No message or key persistence - No plaintext credentials ever sent over the network Authentication uses *SRP*, and messages are encrypted after key exchange. All data lives in memory only and disappears when the process exits. This was partly a learning project and partly an experiment in building a “minimum-trust” chat system using standard cryptographic primitives. Curious to hear thoughts on the threat model, crypto choices, and overall design. https://ift.tt/4HYlivE January 7, 2026 at 06:16AM