I'm considering building an "AI pair-session replay recorder" — would this help your team?

solemness — Thu, 02 Jul 2026 08:51:38 +0000

Thinking about building a tool that records AI coding agent sessions (the prompts, edits, terminal output, decisions) into a shareable replay link — like a scrubbable timeline you could send a teammate instead of screen-recording or narrating what happened. Aimed at teams doing code review or onboarding new devs to an AI-assisted codebase.

Trying to validate before I sink time into it. Genuinely curious:

When you review or explain an AI agent's session to someone else today, what do you actually do — screen share, paste transcripts, screenshots?
If you've tried sharing an agent session with a teammate, what got lost or was hardest to convey?
For onboarding specifically, would seeing how an agent solved something (not just the final diff) actually change how someone learns the codebase, or is the diff enough?

discuss #ai #devtools

Claude Code hooks are the seatbelt nobody buckles — here's the 10-hook setup that makes agent disasters impossible

solemness — Wed, 01 Jul 2026 22:42:47 +0000

Every Claude Code power user has a story: the force-pushed main, the "helpfully" rewritten .env, the API key committed at 2am. The fix has been sitting in the docs the whole time — hooks: shell scripts that run on every tool call, outside the model, so they hold even when the model has a bad day.

Almost nobody sets them up. Writing defensive hook scripts is genuinely fiddly. Here's what I learned building a full 10-hook guard-rail set, including the parts the docs make you discover the hard way.

The three mechanics that matter

1. Exit code 2 is the magic word. A PreToolUse hook that exits 2 blocks the tool call, and everything you wrote to stderr is fed back to Claude as the reason. Claude then adapts — tell it "force-push to main refused, use a feature branch" and it does exactly that. Exit 0 allows; other codes just log.

2. JSON decisions beat exit codes for nuance. Printing {"decision":"block","reason":"..."} on stdout does the same job and works for PostToolUse feedback loops too — that's how you pipe lint errors straight back to the model so it fixes its own warnings.

3. Stop hooks can refuse "done". A Stop hook that runs your test suite and blocks on red means the agent literally cannot declare victory with failing tests. Guard against infinite loops by checking stop_hook_active in the payload.

Design rules for hooks you'll trust

Fail open. If jq is missing or your script errors, allow the action. A guard rail that bricks your session gets uninstalled by lunchtime.
Block with instructions, not just "no". The stderr message is a prompt — tell the model what to do instead.
Make every hook a no-op switch away. REPO_ARMOR_DANGER_OFF=1 beats editing settings.json mid-incident.
Match narrowly. A Bash matcher that blocks rm -rf / must still allow rm -f build/tmp.txt, or you'll drown in false positives and turn it all off.

The full set worth having

Secret-leak blocker, dangerous-command guard, protected-file guard, main-branch commit guard, test-on-stop, format-on-edit, lint feedback loop, desktop notifications, JSONL audit log, and a context guard that injects a warning when your prompt mentions "production".