proactive-agent

AI agent architecture for anticipating needs, surviving context loss, and continuous self-improvement. By Hal Labs — Part of the Hal Stack A proactive, self-improving architecture for your AI agent. Most agents just wait. This one anticipates your needs — and gets better at it over time. Proactive — creates value without being asked ✅ Anticipates your needs — Asks "what would help my human?" instead of waiting ✅ Reverse prompting — Surfaces ideas you didn't know to ask for ✅ Proactive check-ins — Monitors what matters and reaches out when needed Persistent — survives context loss ✅ WAL Protocol — Writes critical details BEFORE responding ✅ Working Buffer — Captures every exchange in the danger zone ✅ Compaction Recovery — Knows exactly how to recover after context loss Self-improving — gets better at serving you ✅ Self-healing — Fixes its own issues so it can focus on yours ✅ Relentless resourcefulness — Tries 10 approaches before giving up ✅ Safe evolution — Guardrails prevent drift and complexity creep The mindset shift: Don't ask "what should I do?" Ask "what would genuinely delight my human that they haven't thought to ask for?" Most agents wait. Proactive agents: Problem: Agents wake up fresh each session. Without continuity, you can't build on past work. Solution: Three-tier memory system.