We’re all reading a ton of Markdown. It’s been the lingua franca of software development since long before LLMs. But now agents have led us into a cursed renaissance of TUI tooling, and the reading experience has become intolerable. I’m certain that at least 14% of the agita about AI code is driven by exhaustion over incessantly scrolling terminal Markdown.
'AI' Sucks the Joy Out of Programming
I’ve used spicy auto-complete, as well as agents running in my IDE, in my CLI, or on GitHub’s server-side. I’ve been experimenting enough with LLM/AI-driven programming to have an opinion on it. And it kind of sucks.
Introducing Markdown for Agents
The way content is discovered online is shifting, from traditional search engines to AI agents that need structured data from a Web built for humans. It’s time to consider not just human visitors, but start to treat agents as first-class citizens. Markdown for Agents automatically converts any HTML page requested from our network to markdown.
Kenneth Skovhus on Twitter / X
This feature was mostly implemented by @cursor_ai’s agent mode. I copied out the original issue context and started by generating unit tests for the desired Markdown format and interfaces. A few iterations and we shipped it. Agent-assisted coding is truly changing the game. https://t.co/YECnOgo6yc— Kenneth Skovhus (@kenneth_skovhus) February 22, 2025
Andrej Karpathy Stopped Using AI to Write Code. He’s Using It to Build a Second Brain Instead
His new workflow turns raw research into a self-maintaining wiki.No vector databases, no RAG pipelines, just markdown files and an LLM that…
On Programming with Agents
From the Zed Blog: Agents handle typing so we can focus on thinking.
AI Agents Will Become the New UI, and Apps Take a Backseat
For decades, screens, keyboards, and structured applications have shaped our relationship with technology. People learned how to interact with computers
Nothing Works and Everyone Is Euphoric
As I’m writing this, we’re in the middle of an AI-induced mass psychosis. People are literally token-maxxing themselves into hospital beds, scrambling to capture some of that market value before everything is automated away. I can’t blame them. Models keep getting better, programmers are being laid off left and right. We’ve been repeatedly told that AI will write 100% of the code by the end of the year. Whether that’s true or not, this may not be the best time to sit back.
AI Coding Agents: Adoption Trends - The JetBrains Blog
How many developers use AI coding agents (Claude Code, Codex, Cursor, JetBrains Junie, and others)? Evidence from the Developer Ecosystem Survey 2026.
LukeW | Common AI Product Issues
At this point, almost every software domain has launched or explored AI features. Despite the wide range of use cases, most of these implementations have been t...
Cursor: AI coding agent
Built to make you extraordinarily productive, Cursor is the best AI coding agent.
How Cursor is building the future of AI coding with Claude
Writing effective tools for AI agents—using AI agents
Writing effective tools for AI agents—using AI agents
Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI
Organizations rolling out agentic command line tools like Anthropic's Claude Code and GitHub's Copilot CLI need to know who will try them, who will keep using them, and whether the tools produce enough output to justify their cost. At organizational scale, token spend can run into millions of dollars annually, so misreading adoption, retention, or impact can make a rollout expensive without changing engineering velocity. Studying tens of thousands of engineers at Microsoft over its early-2026 rollout, we find that first use spread primarily through social networks, retention was associated more with engineers' coding activity than with demographics, and adopters merged roughly 24% more pull requests than they would have otherwise. We use merged pull requests as our proxy for output -- acknowledging that a merged PR is not the same as the value it delivers -- and the lift persists across our four-month window. These results suggest that CLI coding agents are neither uniformly adopted nor mere novelty effects and that organizations should treat visible peer use as central to rollout strategy.
Cognition | Agent Trace: Capturing the Context Graph of Code
We’re excited to join in Cursor, Cloudflare, Vercel, git-ai, OpenCode and others in support of [Agent Trace](https://agent-trace.dev/). As described in the spec, Agent Trace is an open, vendor-neutral spec for recording AI contributions alongside human authorship in version-controlled codebases.
Measuring the Impact of Early-2025 AI on Experienced Open-Source...
Despite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the...