AUTOMATION

Review capacity is the real bottleneck now that agents ship pull requests faster than people can read them. A webhook service on Railway that runs OpenCode headless against every PR diff, posts findings as a review, and never touches the code: the complete one-hour build.

Your team already lives in Discord. A slash command, a headless OpenCode agent, and a persistent Railway service add up to a bot that answers questions about your repository in the channel everyone already watches. The complete build, start to finish.

AWS open-sourced Pizza Bot, a local-first inbox for long-running AI agent work. The useful lesson is not the brand. It is the queue, approval, checkpoint, and return-path pattern.

A changelog nobody reads is a story nobody heard. A coding agent reads your real git history and writes a two-speaker script, the ElevenLabs Text to Dialogue API turns it into a host-and-guest conversation, and ffmpeg stitches the episode. The complete one-hour build.

Codex Computer History gives agents a rolling view of work across apps. Here is how it works, where it helps, and the privacy boundaries developers should understand.

Every Grok Bot works on a persistent cloud computer with browser and terminal access, and that single primitive explains everything else about the product. Here is why own-computer beats chat drafts, API integrations, and session-scoped agents.

Grok Bot ships controls over agents rather than controls by agents: approval gates, a chief-of-staff structure, and escalation learning stand in for a settings page. Here is how that oversight model works, and the control questions xAI has not answered publicly.

Grok Bot's routines flip the automation playbook: do the job once while a Bot follows along, correct it in plain language, then let the Bot own the schedule. Here is how the mechanic works, where it fits, and how approval gates keep it safe.

The boring 80 percent of video editing is mechanical: cut the filler, clean the audio, add captions, export. The Descript API turns each of those into a scripted job, so a raw recording becomes a published, captioned cut without opening the editor once.

The agent finishes, the summary scrolls past, and you will read it later. Build the fix: a coding agent that ends every run with a plain-language summary, piped into ElevenLabs text-to-speech and out as an MP3 you can listen to on the way to work. The complete one-hour build.

The most common trigger for an AI coding agent is not a clock, it is an event. A GitHub webhook, a Railway service, and OpenCode headless add up to a repo where a labeled issue gets a real pull request without anyone at the keyboard. The full build, start to finish.

Self-improving applications shift the economics of maintenance. Instead of per-token pricing, you pay per closed issue - and the closed loop (user feedback to GitHub issue to Codex scheduled task to reviewed PR) means the cost is predictable, the fixes are testable, and the human is in the merge decision, not the implementation.

Release notes nobody reads are a content problem with a mechanical fix: have a coding agent write the narration script from real git history, record the demo with Screen Studio, and let Descript narrate and edit it. A complete one-hour build.

An agent CLI plus a cron schedule turns recurring dev chores into background work: dependency bumps, doc freshness checks, morning briefs. The pattern, the guardrails, and where to run it - your own hardware or a cloud host.

A guide to setting up an isolated spare Mac that Claude Code can control remotely over SSH, Remote Control from your phone, and Tailscale.

The architecture side of loop engineering: plan/act/verify cycles, convergence criteria, retry policies, budget-bounded loops, and the loop-until-dry pattern. Concrete TypeScript-shaped patterns for building agent loops that stop when they should.

A new benchmark shows GLM 5.2 processing 59 transactions and producing VAT returns off by only 7 pence - at $2.73 versus typical accounting fees of $1,000+. Here is what the benchmark actually tested, where the model failed, and why the HN discussion focused on liability.

A companion guide to the Codex Record & Replay video: OpenAI Codex can now record a recurring computer task and replay it as a reusable automation skill. Here is what the feature is and where it fits.

A companion guide to the Loop Engineering video: the shift from repeatedly prompting an LLM to building long-running loops, goals, and automations. Here is the core idea and where to go deeper.

Codex-Maxxing should mean bounded autonomy: AGENTS.md, small worktrees, explicit stop conditions, subagents only when work is separable, and review checkpoints that keep humans in control.