Software, APIs, and things you can use
The Stack
Today's board is about the parts nobody demos: where an agent's reasoning gets stored, how a PDF becomes context, where plugins come from, and whether your dev server has a name your agent can remember. Five fresh picks, none of them repeats from this week'
The Stack
Today's daily board is all about the gear bolted onto an agent that already writes code: a real browser it can drive and debug, a skill that scrubs the machine-tone out of its prose, a forecasting model that reads time series, and one cluster that serves every
The Stack
A local LLM is an AI model that runs on hardware you own — the actual math happens on your laptop, phone, or server. A cloud API is the same kind of model running on someone else's machines, which you reach over the internet and pay for by the
The Stack
A token is the chunk of text an AI model actually reads and writes — not a word, not a character, but a piece of a word: "un", "believ", "able". Every language model, from the smallest phone-side model to the biggest frontier system, does
The Stack
Today's daily board has a clear pattern: agents are no longer just writing code in a terminal, they're producing finished artifacts — a paper, a cut video, a cloned voice, a model of your own. Five fresh projects, none of them repeats from this week's
The Stack
Google's coding-agent IDE gets a one-command "think harder" pipeline that spins up subagents to split, verify, and rebuild hard problems, while CrowdStrike and Intel push a Falcon AI model down into the NPU on Dell's AI PCs to catch the sensitive data
The Stack
The daily board is full of things that bolt capability onto agents you already run: a research skill that swaps search-engine editors for crowd votes, a classroom that builds courses with an agent instead of a prompt box, and the two plumbing layers — MCP servers and realtime voice — that
The Stack
Two months of silence from a project that had been shipping almost daily was the tell, and today the OpenClaw team broke it with their biggest release yet. OpenClaw 2.0 is the work of 933 contributors, and the rebuild reaches from the install screen to the browser app itself.
The Stack
As AI agents move from answering questions to running commands, the gap between "the model can call a tool" and "the model should call this tool, with these arguments, right now" has become the single most consequential surface in agent security. Talos, an open-source project
The Stack
Reinforcement learning from human feedback (RLHF) is the training technique that teaches an AI model what people actually prefer — by using human ratings, not just text, as the signal for what counts as a good answer. It is the reason a chatbot says "I'm not sure, let
The Stack
Generating code is no longer the hard part — reviewing, approving, and shipping the flood an agent produces is. That's the problem the delivery platform Harness is now attacking, and it means the next AI-boom battleground isn't the IDE, it's the gate. Harness launched
The Stack
Judging a RAG system by reading its answers tells you almost nothing. That is the trap: a fluent, confident, well-cited answer can come from a model that never retrieved a single document — and a genuinely grounded one can still fail because the right text never surfaced. The way to