Skip to content
All tags

#spec-driven-development

5 posts

AI Agent GitHub Digest — 2026-09-04

github/spec-kit turned one and shipped 1.0.0, with its maintainer stressing that adaptability now matters more than stability. stablyai/orca lets you run a whole fleet of coding agents in parallel worktrees and gained 812 stars in a single day. KeygraphHQ/shannon shipped 3.0, an AI agent that runs real penetration tests and outputs SARIF reports straight into CI/CD. On the browser side, ChromeDevTools/chrome-devtools-mcp opens Chrome's official MCP server up to any agent. On the framework side, Pydantic AI v2.38.0 changes how one-off capabilities get merged (a breaking change), and Claude Code v2.1.259 fixes a long-standing bug where concurrent sessions silently clobbered each other's settings.

CS146S Week 2: Context Engineering, RePPIT, and MCP's 98.7% Cut

Fall 2026 compresses a full week of prompting into one bullet here and adds RePPIT (Research, Propose, Plan, Implement, Test) and MCP. Two RePPIT rules are worth stealing outright: always ask for exactly two proposals, and never let the instance that wrote the code review it. On the MCP side, Anthropic measured turning tools into code calls dropping 150,000 tokens to 2,000.

ai deep-dive

Uncle Bob Doesn't Read His Agents' Code: What He Runs Instead of Code Review

Uncle Bob's 4.18M-view post of 2026/7/23 isn't a manifesto — it's a reply to an engineer who started in 1983 asking whether needing to understand code psychologically makes him old-fashioned. And he doesn't skip the code entirely: his 6/1 four-stage pipeline post says 'I spot check the code,' with thresholds of crap ≤ 6 (convention is 30) and mutation runs that kill all survivors. Plus a breakdown of his open-sourced Acceptance-Pipeline-Specification and the three metric blind spots Grady Booch names.

ai guide

Integrating AI Agents into Your Development Workflow: A Five-Phase SDLC Breakdown

Agentic AI is not just autocomplete — it is an AI system capable of autonomously executing multi-step tasks. This article breaks down the five phases of the SDLC, explaining where to plug in agents at each phase, how to progress from CLI tools to full-pipeline automation, and the most valuable external resources to track right now.

ai guide

Lessons from the Trenches: What AI Native Teams Must Get Right

Not everyone should use a coding agent to modify code directly. AI Native teams need interface specs, test-first development, monorepo, security guardrails, human-in-the-loop, and token budget controls. Building an agent platform layer on top of coding agents and clearly redefining developer roles is the right path forward.