The paradox of AI memory: remembering everything is easy. Remembering wisely is hard.

I've been building a personal AI agent — not a chatbot, a companion. One that knows my projects, preferences, and decisions. That picks up where we left off without me re-explaining everything. But here's what nobody talks about: naive memory is expensive. And not just in dollars. Give an agent a massive context window and fill it with everything it's ever seen. More context doesn't mean more understanding — it means more noise. The signal-to-noise ratio collapses. The agent hallucinates connections between unrelated things, loses track of what matters right now, and slows down while becoming less accurate. Context isn't just a resource — it's a cognitive environment. Pollute it, and your agent gets dumber the more it "knows." The human brain doesn't work this way. You don't replay every conversation you've ever had before answering a question. You forget most things. That forgetting isn't a bug — it's the architecture. So I built memory that works more like ours: Structured extraction