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Open Source Radar — October 6: nothing leaves your machine

Today's trending board is all projects we ran earlier this week, so the fresh signal comes from the Product Hunt launch slate instead — three open-source tools that share one instinct: your phone, your pixels and your MCP traffic should stay on hardware you control. All three verified at the source. iphone-use (Rust, MIT, about 59 stars) is computer-use for a real iPhone: an agent reads the screen as text, taps, swipes and types over WebDriverAgent, and every action comes back with an honest v

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AI 101 — What is prompt engineering?

Prompt engineering is the practice of writing instructions for an AI model so it gives you what you actually wanted — from a one-line question in a chat box to the multi-paragraph specifications companies embed in their products. "Prompt" is just the text you send the model; "engineering" is the unglamorous work of making that text specific enough to work. Why it matters right now. Prompting is still how almost everyone touches AI, and the craft keeps getting documented rather than disappearin

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Open Source Radar — October 5: Skill stacks for every harness

The trending board this weekend is less about new frameworks and more about portable taste: skill packs and workflows built in one agent harness, then ported everywhere else. Four fresh picks, all verified at the source. gstack (TypeScript, 135,000+ stars) is YC president Garry Tan's Claude Code setup, opened up: 23 opinionated tools that play CEO, designer, engineering manager, release manager and QA. The repo sits at the top of daily trending, and the appeal is obvious — instead of writing y

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Open Source Radar — October 4: Cloudflare's OS for agents

Today's trending signal is the toolchain opening up: Cloudflare handed the public its internal AI workspace, Addy Osmani's engineering skill pack crossed 100,000 stars, and a nonogram benchmark is puncturing model confidence in public. Cloudflare OS (TypeScript, ~10,700 stars, Apache-2.0) — Cloudflare just open-sourced the "AI productivity environment" a large share of its own workforce uses daily, and it reads less like a demo than an internal product with a security team's fingerprints on it.

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AI 101 — What is AI inference?

Every answer an AI gives you is inference: running a trained model on new input to produce an output. Training is how a model learns; inference is how it works. If training is teaching, inference is doing. Why it matters right now. Training makes the headlines — a new model, a bigger cluster, a record run — but training happens once per model, while inference happens every time anyone asks a question. That asymmetry is why the money has shifted: Google Cloud describes inference as the phase "wh

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Open Source Radar — October 3: Eyes, skills and taste

Today's trending page is all layer-under-the-models: an internet access layer for agents, Google's own skills catalog, a linter for AI-designed frontends, and a browser built for agents to use beside you. Agent-Reach (Python, ~89,200 stars, MIT) — The top AI repository on today's daily trending page, and a fix for the failure every agent hits first: sending it out onto the open web. It gives any command-running agent read and search access to the platforms where useful information actually live

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Open Source Radar — October 2: agent harnesses and their guardrails

Today's daily trending is dominated by infrastructure rather than demos: how agents run, what they're allowed to touch once they run, and — in the one research entry — what happens when a model can animate anything with a skeleton. pi (TypeScript, ~111,500 stars, MIT) — The Pi agent harness hit version 1.0 today, and the release that pushed it to the top of trending is MCP support now on by default. The repository is a full toolkit rather than a single bot: a unified API across OpenAI, Anthropi

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AI 101 — What is a neural network?

A neural network is a computing system made of layers of simple math functions whose internal numbers are tuned by examples until the whole thing gets the right answers — a design loosely inspired by the brain, and the foundation of every AI system in the news. ChatGPT, Midjourney, AlphaFold: all neural networks, all variations on the same idea. The concept is older than computers. In 1943, Warren McCulloch and Walter Pitts described an artificial neuron — a thing that takes inputs and fires w

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Open Source Radar — October 1: the tools agents run on

Today's trending list is less about new models and more about the plumbing: what agents can see in your codebase, which skills they can load, and what they can produce once you point them at a blank canvas. MoneyPrinterTurbo (Python, ~127,800 stars) — A one-stop AI short-video factory: give it a topic or a keyword and it writes the script, picks stock footage, generates subtitles and background music, then cuts a finished HD clip. It offers four entry points — an agent interface, a web UI, an A

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AI 101 — What is CUDA?

CUDA is the software layer that lets ordinary programs run on NVIDIA's graphics chips — and it is the foundation nearly all modern AI is built on. Short for Compute Unified Device Architecture, it first shipped on February 16, 2007, and it turned graphics cards — machines designed to draw video games — into general-purpose computers that any developer could program. Before CUDA, using a graphics chip for serious math meant writing code in the chip's own graphics language, in fragments, with lit

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Open Source Radar — September 30: the infrastructure under agents

The signal today is not another model release — it is the layer beneath the agents: where they run, what they are allowed to reach, and what they already know how to do. NVIDIA OpenShell (Rust, Apache-2.0, ~11,000 stars) — NVIDIA's answer to the question every team running autonomous agents eventually asks out loud: what can this thing actually touch? OpenShell gives each agent a sandbox that starts with almost no outbound network access, then opens specific holes through a proxy that checks th

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Huawei open-sources Pangu 2.0's training stack, code and all

Three things worth your time this hour: the first Chinese lab to give away the code that produces a frontier model, the platforms quietly replacing Hugging Face inside China, and a small OCR model that beat the big generalists on their own benchmark — a month before anyone announced it. Huawei has open-sourced the code that trains Pangu 2.0, not just the weights — publishing the pretraining, supervised fine-tuning and post-training reinforcement-learning pipelines for the model family. The Sept

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