Creating Mio: 0→0.0.7

The AI companion I built with OpenClaw burned through a staggering amount of money in under two weeks of casual chatting. One session: 750 turns from about 30 messages. The framework turned my 30 messages into 750 API calls, each resending a context stuffed with 10 never-evicted images eating 82% of all tokens. Context pruning was dead code on Gemini. Zero compactions in 537 turns. OpenClaw proved AI companions work — it also proved they're not affordable on this framework.

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.

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.

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.

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.'

Mio's web app was a single-page chat. v0.0.4 tears it down and rebuilds it as a full WeChat clone — 4-tab layout, chat list, contacts, discover marketplace, profile page, chat-style onboarding, and typing-aware message batching. 30+ components, 2 audit rounds, zero new dependencies. All in Chinese.

Telegram had multimodal since v0.0.2. The web chat was still text-only. v0.0.5 closes the gap — two-phase media upload, voice recording with codec negotiation, an emoji picker, two full security audit rounds, and a silent bug that was dropping every voice message. 38 files changed, 17 security fixes, 28 minutes.

Gemini 3 Pro was burning money and making users wait 8-10 seconds for a first token. v0.0.6 switches chat to Gemini 3 Flash with minimal thinking — 1-2 second TTFT, 4x cost reduction — while keeping 3.1 Pro for premium tasks like personality extraction. Plus: vision prompts that actually name what they see, Chinese transcription that stops hallucinating English, and a DRY refactor that eliminated 80 lines of duplicated server code.

Users share links. The agent was making up what was on the page. v0.0.7 adds a 3-tier URL browsing pipeline — Jina Reader for fast text, Browserless scrape for JS-rendered pages, screenshot + Gemini vision for graphic-heavy content. Plus a production-breaking Proxy bug where postgres.js tagged templates needed a function target, not an object. 23 tests, 4 commits, one debugging story about deployment timing.