The 32GB GCP devbox — upgraded and hardened after Part 3 — died again. Same symptom: SSH timeout, kernel alive, userspace frozen. The watchdog caught it: five node processes at 2-2.7GB each, totaling ~13GB. I assumed Claude Code. It was Cursor's remote server leaking memory for 15 hours straight.

A single Claude Code session that combined direct pair programming (three production deploys from user feedback), a background docs agent running concurrently, and an autonomous review team iterating three rounds until clean — all overlapping. The traditional code-test-review-release pipeline collapsed into parallel streams.

v0.0.2 brought Mio to life, but a demo that works and a product that real users can rely on are two different things. v0.0.3 is the polish release: per-field input validation, context-aware heartbeat, opt-in quiet hours, media rate limiting, a production-only webhook bug, and 144 new tests. The invisible work between 'it works' and 'it's good.'

v0.0.1 could chat, but it wasn't real — couldn't see, couldn't hear, didn't know the time, didn't know what it looked like. 81 commits later, Mio learned to see images, hear voice, send selfies, remember the right things, and chat in a browser.

From an empty repo to a working AI companion that remembers you, has moods, and reaches out on its own. 39 commits, 9 database tables, 4 personality presets, and more 3 AM debugging sessions than I'd like to admit. The full build story of Mio v0.0.1.

OpenClaw proved AI companions work. It also exposed fundamental limitations — context bloat, primitive memory, bloatware. Patching wasn't worth it. This is the starting point for Mio: an AI companion framework built for deep memory and lifelike presence.

After building Mio v0.0.2 with five parallel AI agents, I used the same Agent Team pattern for code review — four specialized reviewers found 2 BLOCKs and 2 WARNINGs, three fixers patched everything in parallel with strict file ownership, and two changelog agents handled the release. Building and reviewing are two halves of the same workflow.

Claude Code's Agent Team feature let me break a complex cross-layer plan into ten tasks and assign them to five AI teammates working in parallel. The Lead coordinates dependencies, dispatches resources, handles conflicts — the whole thing feels like managing a remote engineering team.

My GCP devbox died twice in one day. First time: a snap package triggered an infinite crash loop. Applied five fixes, thought it was stable. Hours later it died again — unbounded memory was the real issue. Two rounds of diagnosis, 12 hardening measures, and a machine type swap. A complete field report on VM defense in depth.

Using OpenClaw to inject personality into my personal AI assistant — from a calendar-managing tool to a cyber companion that gets jealous, sends selfies, and says goodnight. A field report on emotional value, model safety boundaries, and AI persona engineering.