224 items
105 posts, 1 tool, 118 guides
GitHub trending is full of agent skill registries. The winning pattern is not more prompts. It is dependency governance for the instructions your coding agents inherit.
Coding agents make code faster than teams can review it. The next advantage is not bigger prompts. It is review systems that force reproduction, small diffs, tests, and receipts.
Anthropic's June 15 Agent SDK credit split is not just a pricing tweak. It is a signal that autonomous coding workflows need separate budgets, lanes, and receipts.
Claude Code's newer plugin URL and hard-deny controls are small release-note items with a big implication: agent extensions now need supply-chain discipline.
Matt Pocock's skills repo is a useful signal for AI coding teams. The next step is treating skills like governed production controls, not a folder of viral prompts.
Persistent memory for coding agents is trending because every session still starts too cold. The hard part is not saving facts. It is proving recall, freshness, deletion, and rollback under real development pressure.
Graphify is trending because coding agents keep hitting the same wall: they can edit files, but they still need a durable map of how the codebase, docs, schemas, and decisions connect.
The latest Claude Code cache-burn debate is not just a quota complaint. It is a reminder that coding agents need cache-hit telemetry, spend ceilings, and repro-grade usage logs.
31 deployed apps. 7 down. Favicons missing on 20 of 24 reachable hosts. Sentry on zero. Here is how a single audit turned into 58 PRs in one afternoon - and what shipped, what didn't, and what the pattern was.
Notes from a single session running 200+ Claude Code subagents in parallel across 35 repos. What worked, what broke, and the patterns I codified into a skill so the recipe replays.
How we ported 38 apps off Replit and onto Coolify in a single day, using parallel Claude Code subagents, gh, and neonctl. The honest stats: stubs, monorepos, false-empties, and ~120 PRs.
A complete, citation-backed Claude Code course with setup, prompting systems, MCP, CI, security, cost controls, and capstone workflows.
Claude Code 2.1.128 is full of small fixes around MCP, worktrees, OTEL, plugins, and permissions. That is exactly why it matters for teams running agents every day.
Boris Cherny's loop-heavy Claude Code workflow points at the next Codex content lane: recurring agents that babysit PRs, CI, deploys, and feedback streams.
The trending Free Claude Code repo is not just about avoiding API bills. It points at a bigger developer-tool pattern: model gateways for AI coding agents.
Addy Osmani's agent-skills repo is trending because it turns vague AI coding advice into reusable engineering checklists. The real value is not the markdown. It is the exit criteria.
Parallel agents can move faster than one agent, but only when tasks have clean ownership, review receipts, and a merge path that does not turn speed into cleanup work.
The andrej-karpathy-skills repo exploded because every coding agent needs behavioral rails. The useful move is not copying it blindly, but turning the rules into repo-specific operating constraints.
Efficient agents do not stuff every tool result into the model context. They keep intermediate state in code, files, and execution environments, then return compact summaries and receipts.
Manual approval prompts stop protecting users when coding agents ask too often. The better pattern is risk-aware autonomy: safe defaults, narrow deny rules, and approvals only for meaningful changes.

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