Agents Now Plan Tasks Across Your Codebase
Raycast's AI Chat now runs multi-step tasks autonomously, chaining extension calls, executing code and retrying on failure without per-request interruptions, while shifting billing from rate limits to…
Raycast's AI Chat now runs multi-step tasks autonomously, chaining extension calls, executing code and retrying on failure without per-request interruptions, while shifting billing from rate limits to…
A developer built jevgrep, a semantic code search tool that skips the vector index entirely by combining a ripgrep keyword sweep with a single batched call to TypeSafe's Jev decision model, which retu…
A 2026 pricing survey of AI coding tools reports that 73% of startups now deploy at least one AI coding assistant, with GitHub Copilot the most widely adopted at $10-19 per user per month, followed by…
Amp, the agentic coding tool from Sourcegraph, is now free to use for customers who bring their own compute and model subscriptions or API keys, with users paying only for orbs or running agents free …
A 2026 guide to AI coding assistants reports that 72% of developers now use them daily, with GitHub Copilot remaining the benchmark at $19/month despite enterprise security concerns. The guide highlig…
A developer built vibestretch, a Claude Code plugin that nudges users to stretch during long waits for their coding agent, after exploring and rejecting the idea of selling ads in the terminal. The pl…
GitHub's Copilot code review always submits a comment review and never blocks a merge, a distinction that is often misunderstood in AI code review procurement. CodeRabbit, Copilot, Cody, and CodeBuddy…
Wallarm CEO Ivan Novikov claims a $60-per-month virtual machine running an LLM agent can now perform autonomous security work, including code scanning and patch analysis. He argues that dedicated VMs …
MacAIApps, a new directory of AI-powered Mac applications, has launched, featuring over 60 tools including Vinaa, an AI chat aggregator, and various transcription, coding, and productivity apps. The d…
Amp, a coding-agent company led by CEO and co-founder Quinn Slack, obtained SOC 2 Type II certification while allowing engineers to push code directly to the main branch without mandatory pull request…
FreeBuff, the ad-supported build of Codebuff launched on 12 February 2026, runs small text-only ads between agent turns and may analyze prompts to personalize them, while Clixad, built by the author, …
GitHub Copilot Free, Cursor's Hobby plan, FreeBuff, Clixad, Amp Free, and the Gemini CLI free tier are the only AI coding agents that include model access without an API key, but only Clixad's credit …
A developer explains the current state of coding agent context files, noting that AGENTS.md has become an open, vendor-neutral standard backed by OpenAI, Google, and the Linux Foundation's Agentic AI …
Code retrieval is shifting from embeddings to graph-based approaches, as demonstrated by the trending open-source tool code-graph-rag, which parses repositories with Tree-sitter, builds a knowledge gr…
Sourcegraph launched Amp Free with in-session ads in 2026 but dropped them within six months, citing the releases of Gemini 3 Pro, Opus 4.5, and GPT-5.2 Codex, and replaced them with a vendor-funded d…
A new approach called context engineering moves beyond prompt engineering to prevent hallucinations in AWS Bedrock agents by building a layered context pipeline with persistent, time-sensitive, and tr…
Anthropic released the Model Context Protocol (MCP) in November 2024 as an open standard that lets AI models connect to external tools and data without custom integrations. By early 2025, OpenAI and G…
A developer used AI agentic coding to build a system that crawls a billion web pages in 24 hours, writing less than 4% of the code by hand. The project achieved high throughput at scale, demonstrating…
A developer community consensus has emerged that AI coding agent effectiveness depends more on repository architecture than prompt engineering. Teams are adopting a standardized `AGENTS.md` file at th…
Current large language models cannot safely modify real software systems despite impressive code-generation demos, because they rely on pattern matching rather than causal reasoning. The fundamental g…