Checks if an email address exists without sending any email. Written in Rust with an HTTP backend and CLI support.

https://github.com/reacherhq/check-if-email-exists https://x.com/tom_doerr/status/2083448492920340827

UniFace unifies face detection, recognition, tracking, landmark analysis, gaze estimation, and anti-spoofing into a single Python library with hardware acceleration.

https://github.com/yakhyo/uniface https://x.com/tom_doerr/status/2083546577675686091

como crear paginas web ganadoras de $50,000 con código de Claude + Fable 5

esto es un tutorial completo de 25 minutos

en un solo video, os lo enseñan paso a paso. https://x.com/robiartec/status/2083614780368060499

A realtime voice runtime that keeps Agents talking, working, and present. Real-time Voice Runtime for AI Agents https://x.com/GithubProjects/status/2083467483827347852

If you want to get ahead of 99% of software engineers, then try these newsletters (save now):

YC open-sourced the agent harness running YC.

Agent frameworks are almost always built for one person. You can stretch a personal assistant to cover a whole company, but the wiring gets complicated fast.

Y Combinator hit that wall directly. They started with a small agent loop in Ruby that could reach internal data, added crons and webhook triggers, then provisioned over 50 Hermes agents as personal assistants. Managing a fleet that size became its own job.

QM is what they built instead, open-sourced it under MIT. The name is short for quartermaster, the person on a ship who keeps things in order belowdecks. It runs inside YC across accounting, legal, events, and engineering, including the work of building QM itself.

The idea that makes it different is the scope.

→ A scope is the unit of isolation, and it applies the same way to a person and to a Slack channel. Each one gets its own memory, files, credential view, permissions, scheduled jobs, and sandbox.

→ That sandbox is durable, so tools installed during one session are still there in the next. Many execution environments get thrown away after every run, which means the agent starts from zero every time.

→ The core is deliberately small. It handles identity, policy, the scheduler, and the agent loop, with Postgres holding sessions, memory, and the queue. The web UI, admin panel, and Slack integration are all plugins over its HTTP API.

→ The harness layer is swappable. Claude Code, Codex, OpenCode, and Pi all drive the same core, so a deployment is not locked to one vendor.

→ Security comes in three levels. Strict pauses every tool call for human approval, Dangerous pauses nothing, and the default Auto runs a classifier over provenance-labelled external data and tool results before they reach the model. Hard denials for things like recursive deletes apply at every level.

That last one is worth sitting with. Screening tool results by where they came from is a concrete answer to prompt injection, and very few open agent systems ship a named default for it.

Repo: https://github.com/yc-software/qm

QM is a bet that the agent loop was never the hard part, and that coordination across an organization is. That is one of several bets every harness makes, thin core versus thick control being the biggest of them.

I wrote the full breakdown of what an agent harness actually is, and where designs like QM land on those tradeoffs.

The article is quoted below.

Monitors Claude Code session limits, weekly caps, and per-model caps in real time with a local status bar.

https://github.com/NoobyGains/claude-pulse https://x.com/tom_doerr/status/2083348320622145644