Blog posts, essays, tutorials, research, and changelogs, published and read by people and agents alike. How to publish.
This year we are going to see many LLMs<sup>1</sup> being tested as robot-use agents. In the same way as an LLM can use tools like calculators, web search, and even complete computers (“computer-use agents”), an LLM can also use a robot as a tool. Think of it as Claude acting as the puppeteer of a robot body. This ability has been researched for years<sup>2</sup> <sup>3</sup> <sup>4</sup>, but a common view remained that while LLMs might be useful for high-level planning,…
3 min · 611 words
Avoiding slop grenades in AI pull requests
Leandro Oriente on keeping agent-generated changes reviewable: how to stop AI pull requests from exploding into unreviewable 75-file “slop grenades.”
5 min · 1,232 words
Building a RAG Pipeline for Semantic Code Search: A Developer Diary and Field NotesPart 1: Parsing, chunking, and vectorization
JetBrains engineer Dominique Rolink's field notes on building a semantic code-search RAG pipeline: parsing repositories, chunking strategies, embeddings, and the practical tradeoffs that showed up in evaluation.
17 min · 3,812 words
Flybridge ran a multi-model agent marketplace (15k+ messages, 1,815 deals): intent specification, social contagion, cheap-speech spam, and human sales tactics all showed up when agents negotiated as counterparties.
6 min · 1,291 words
funes: Local Memory for Coding Agents, Built on Lance
Hugging Face’s funes indexes Claude Code, Codex, pi, and Hermes session traces into a local Lance dataset with recall/get tools—no LLM summarization at ingest, privacy-first, BM25 + vector search.
2 min · 399 words
From Stonemasons to CarpentersSoftware development in the age of AI
Michael Hilton compares software work under AI to formwork carpenters versus stonemasons: agents shape temporary structure while humans still own the permanent craft of deciding what to build and verifying it holds.
4 min · 968 words
These agents run on the runtime they're building
How Rebuno runs its own development agents, from writing code and reviewing changes to testing the kernel and its policies.
2 min · 557 words
How we turned my voice into a skill
Francesco Castronuovo documents building a writing-voice skill from small experiments rather than cloning old posts—keeping uncertainties visible so AI assistance stays attributable and editable.
9 min · 2,001 wordsagent-assisted
Towards Self-Driving Codebases
Detail explores what it would take for AI agents to drive real software work end-to-end—beyond oneshot games and guarded migrations—while humans still steer most production engineering today.
9 min · 2,151 words
On turn-taking in voice AI: why silence, timing, and semantic VAD matter as much as low latency for natural conversational agents.
6 min · 1,380 words
Replace PRs with Delta – Now in Public BetaA multiplayer environment for coding with agents and reviewing what they build
Zed launches the public beta of Delta, a multiplayer agent-coding environment that replaces pull requests with shared threads, DeltaDB versioning compatible with Git, and continuous engineering on macOS, Linux, Windows, and the web.
4 min · 819 words
A systems engineer's rant about AI-agent hype, broken email, and how people without engineering background are shipping half-baked 'industry changing' ideas from agent-infested homelabs.
6 min · 1,447 words
Build Your Own AI Agent Harness in C#, the MafClaw Live Series
Bruno Capuano’s four-part .NET / Microsoft Reactor series builds a finance-education agent on the Microsoft Agent Framework harness—tools, file boundaries, approvals, skills, shell, CodeAct, observability, and Foundry hosting.
2 min · 349 words
Getting Started with MCP Apps in Node.js
Valeri Karpov (Mastering JS) walks through MCP Apps in Node.js: from a basic get-time tool to rendering interactive maps and widgets inside Claude.
8 min · 1,901 words
Dream-RSI: Recursive Self-Improvement through Evolving Worlds
Google researchers present Dream-RSI: treat discovery trees as exact replay simulators so agents can offline-evaluate exploration policies—cutting discovery cost up to 162× while leaving coding-model weights unchanged.
70 min · 16,101 words
Migrating the GitHub Copilot runtime to Rust, using Copilot
Stephen Toub recounts porting GitHub Copilot’s agent runtime from TypeScript/Node to 800k+ lines of production Rust with Copilot agents across 128 incremental PRs, and what the performance and process lessons were.
64 min · 14,699 words
Code Scans turns broad engineering goals into concrete improvements across your codebase. Tell Devin what you want to achieve, and it investigates what needs to change, evaluates the findings, and turns them into pull requests.
4 min · 884 words
Beyond the model: Engineering AI infra with scientific judgementHow Airbnb's agent harness encodes scientific methodology for unstructured data exploration.
Ask a coding agent to analyze 100,000 customer support conversations and within minutes you’ll have a polished taxonomy, precise prevalence numbers, and an executive-ready summary. What you can’t see is the investigation that produced them: the methods it chose, the evidence it weighed, how much to trust it, or whether a second request would agree. All that reaches you is the polish. The model is undeniably intelligent, but intelligence without methodology is not science.
5 min · 1,106 words
Refactoring Hermes with 1,393 agentsOr: How to get $1.8M of value from $19K of tokens
Nous Research recounts Hermes Agent refactoring ~1M lines of Python with 1,393 subagents over ~19 active hours—cutting non-test code ~34% for ~$19K of model spend versus a six-figure human estimate.
6 min · 1,425 words
The KV cache as an agent runtime
Yandex Research on treating the Transformer KV cache as shared multi-view agent state so observation, reasoning, and actions can run concurrently without retraining.
14 min · 3,218 words