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Memory

Memory is the fifth pillar of Lytos: Memory.

AI agents are stateless — they forget everything between sessions. Memory gives them persistent knowledge about your project, stored in files you own.

memory/
├── MEMORY.md # Index — read every session
└── cortex/ # Specialized zones — loaded on demand
├── architecture.md
├── patterns.md
├── bugs.md
├── sprints.md
├── frontend.md
├── backend.md
└── business.md

Read at every session. Contains a table of contents pointing to cortex files, plus a short living summary of the project’s current state.

The agent reads the index, identifies which cortex files are relevant to the current task, and loads only those.

Each cortex file covers a domain:

FileContentLoad when…
architecture.mdTech choices, structure decisionsAny structural task
patterns.mdCode patterns that work wellCode review, new features
bugs.mdRecurring problems and solutionsDebugging, fixes
sprints.mdSprint history and retrospectivesPlanning
frontend.mdUI/UX decisions, component patternsFrontend tasks
backend.mdAPI decisions, data model choicesBackend tasks
business.mdDomain knowledge, business rulesAny domain-related task
  • Architecture decisions and their rationale
  • Patterns that work well in this project
  • Recurring bugs and their root causes
  • Domain-specific knowledge the AI needs
  • Code snippets (they live in the code)
  • Git history (use git log)
  • Temporary task details (use the issue board)

“Quality doesn’t come from the prompt. It comes from context.”

Without memory, the AI makes the same mistakes twice. It suggests patterns you’ve already rejected. It doesn’t know that you tried Redis and switched to PostgreSQL for good reasons.

Memory is what makes Lytos sovereign — your project knowledge lives in files you own, not in a vendor’s conversation history.