DNA Memory: Making AI Agents Learn, Forget, and Evolve Like a Human Brain

Most AI memory systems solve only one problem: storage . They help an agent remember previous messages, retrieve context, or search old notes. That is useful — but it is not the same as learning . Human memory is not a database. It has structure. It forgets. It reinforces what matters. It summarizes patterns. It turns scattered experiences into reusable judgment. That is the idea behind DNA Memory . GitHub: https://github.com/AIPMAndy/dna-memory The problem If you have worked with AI assistants or autonomous agents for a while, you have probably seen the same failure mode: the agent stores too much low-value information old context accumulates without prioritization repeated mistakes are not converted into durable lessons user preferences are remembered inconsistently "memory" becomes a dump, not an evolving system Most memory layers are built like logs. Very few are built like cognition. What DNA Memory tries to do differently DNA Memory is a lightweight memory evolution system for ag