| I'm a solo founder. 261 commits, 44 tests, 54 deploys. VAOS runs your AI agent 24/7 on Fly.io -- you give it a prompt and a Telegram channel, it handles the rest. The part I care about most: every 5 minutes, a loop scores each agent response on confidence. Low-confidence ones get flagged for you to review. When you correct something, that correction goes into the agent's context for future responses. Not fine-tuning -- just feeding corrections back as structured context. After a few days, the agent stops repeating the same bad answers. I'm dogfooding it with an agent called Scribe that posts to X for me. Scribe was terrible for the first ~80 interactions. Now it's mostly fine. The cold start period is real and I haven't figured out how to shorten it. What works: Telegram responses in under 2 seconds. Swap between GPT-5.2, Claude Opus 4.6, and Gemini without reconfiguring. The feedback loop does what I wanted. What doesn't: Discord and WhatsApp aren't hooked up. No way to export learned corrections (lock-in problem I need to solve). Observability dashboard exists but only I can see it right now. $29/mo, $10 in AI credits included, 14-day trial. Stack is Node.js on Fly.io. Curious about the confidence-scoring approach. Anything above 0.8 auto-approves, below gets queued for human review. Should I give users that threshold control, or is one knob enough? |