Your First Memory¶
This guide walks you through capturing, finding, and recalling your first atom. By the end you'll understand what Lattice actually does with what you tell it.
Step 1: Capture a fact¶
With the daemon running, open the web UI at localhost:7337 or use the terminal:
You'll see a confirmation: captured: 1 new.
Step 2: Look at the atom on disk¶
You'll find a .md file — something like a1b2c3d4.md. Open it:
---
id: a1b2c3d4
kind: goal
subject: reading list
content: Wants to read "Thinking, Fast and Slow" by Daniel Kahneman.
observed_at: 2025-11-14T09:12:00Z
source_id: lc-cli
quality_score: 1.0
tier: stm
---
Wants to read "Thinking, Fast and Slow" by Daniel Kahneman.
Lattice didn't just save the raw text. It extracted:
- kind —
goal(a thing you want to do) - subject —
reading list(what this atom is "about") - content — a clean restatement of the fact
Step 3: Capture a few more atoms¶
The recall system works best with a few atoms to link together.
uv run lc "I read about 20 pages a day on average"
uv run lc "I prefer non-fiction over fiction"
uv run lc "My current book is Meditations by Marcus Aurelius"
Step 4: Ask a question¶
Open the web UI and type:
Lattice will:
- Search your atoms (BM25 + graph BFS)
- Find atoms about current book, reading list, reading pace, genre preference
- Synthesize a prose answer with numbered citations like
[1],[2]
The answer should mention Meditations as your current book and suggest Thinking Fast and Slow as next, grounded in what you actually told it.
Step 5: Check the graph¶
The graph links all your reading-related atoms by subject:
Returns atom_count: 4 — four atoms, all linked to the reading list subject node in the graph.
What just happened¶
your text
↓ segmented (source type = lc-cli)
↓ LLM extraction → {kind, subject, content, observed_at}
↓ atom written to ~/.lattice/
↓ graph updated: atom_has_subject edge → subject:reading list
↓ BM25 index rebuilt
your question
↓ BM25 seeds: "reading list", "book", "non-fiction"
↓ graph BFS: subject:reading list → all 4 atoms
↓ LLM synthesis: prose answer with [1][2][3] citations
↓ web UI renders answer + source chips
Next steps¶
- MCP Setup — give Claude Code access to your memories
- Concepts: Atoms — understand all atom fields
- Telegram Setup — capture from your phone