10 articles tagged Memory.
The core chapter of the series — what Project Brain is, why it is the right shape for the problem, and how it differs from context injection, RAG, and long conversation history.
A pillar series on why AI systems forget, why software engineering exposes this limitation most severely, and how CreateLixir's Project Brain gives every project a persistent, structured memory.
Every new AI session begins from zero. This chapter looks at the practical, engineering-wide cost of that reset — for founders, for teams, and for the codebase itself.
The closing chapter — where persistent memory in AI is heading over the next decade, and what a mature memory layer will make possible that today's software cannot.
A tour of the layers of memory Project Brain holds — identity, product, target users, architecture, design system, decisions, constraints, risks, and knowledge — and why each of them matters.
Modern AI does not fail to remember because it is careless. It fails to remember because remembering, in the way humans do it, is not part of how these systems are built.
The synthesis chapter — what changes about AI-assisted engineering once persistent memory is in place, and why it is the missing primitive for autonomous AI teams.
Software is a body of accumulated knowledge, not just code. This chapter looks at what a project actually is — the architecture, decisions, constraints, and invariants that make it more than the sum of its files.
Retrieval-augmented generation gets you far. A structured knowledge graph over your project's identity, decisions, and architecture gets you further.
Every serious AI application converges on the same requirement — memory that survives sessions, teammates, and models. Here's how CreateLixir does it.