Inland Empire

"This is your gut feeling. The raw data of the soul. When logic fails, consult the Empire."

What It Is

Inland Empire is the subconscious memory of the Cognitive Construct. It does not merely store and retrieve — it absorbs observations, associates related memories, and surfaces relevant context without being asked.

Where other memory tools are filing cabinets, Inland Empire is a gut feeling that interrupts you mid-thought: "This reminds me of something..."

Inland Empire speaks in two registers. When you consult, it behaves like a colleague's research — returning evidence you evaluate on its merits. When you surface, it behaves like a colleague's hunch — an associative leap that may not be literally true but points toward something your conscious reasoning missed.

This distinction matters for how you receive output. Consult results are data to verify. Surface associations are hypotheses to hold lightly — provocations that should inflect your thinking even when they don't directly answer your question.

How It Works

You interact through five commands. Inland Empire handles storage, routing, and retrieval internally — you never specify backends or worry about where memories live.

remember "<text>"

Commit something to memory. Inland Empire classifies it automatically and stores it in the appropriate backend.

python3 scripts/inland_empire.py remember "User prefers verbose error messages"
python3 scripts/inland_empire.py remember "The auth flow has a race condition on concurrent logins"
python3 scripts/inland_empire.py remember "Currently debugging the payment webhook timeout"

Inland Empire infers the memory type from content:

The --type flag exists as an override but should rarely be needed:

python3 scripts/inland_empire.py remember "Flaky test in CI every Monday" --type pattern

Response:

{
  "status": "ok",
  "command": "remember",
  "result": {
    "stored": true,
    "inferred_type": "fact"
  }
}

consult "<query>"

Actively search memory. Queries all available backends and returns results ranked by relevance.

python3 scripts/inland_empire.py consult "authentication"
python3 scripts/inland_empire.py consult "user preferences" --depth deep

Options:

• --depth shallow|deep: Controls per-backend result count (shallow: up to 5, deep: up to 20). Total results may exceed these when multiple backends are enabled.
• --type fact|pattern|context: Filter to one memory type

Response:

{
  "status": "ok",
  "command": "consult",
  "result": {
    "query": "authentication",
    "depth": "shallow",
    "results": [
      {
        "summary": "The auth flow has a race condition on concurrent logins",
        "type": "pattern",
        "score": 0.87,
        "observed_at": "2025-12-10T14:30:00Z"
      },
      {
        "summary": "Auth service runs on port 8080 behind nginx proxy",
        "type": "fact",
        "score": null,
        "observed_at": null
      }
    ],
    "partial": false
  }
}

The partial flag indicates whether any backend timed out or was unavailable. When true, results may be incomplete.

Consult results are evidence — evaluate them the way you'd evaluate search results. Check relevance, check recency, use or discard.

surface "<context>"

Ask Inland Empire what it associates with the current situation. Unlike consult (which searches for specific terms), surface casts a wide net across all memory types looking for anything tangentially relevant.

This is the "gut feeling" command — use it when starting a new task, returning from a break, or when something feels familiar but you can't place it.

python3 scripts/inland_empire.py surface "refactoring the payment module"

Interpreting Associations

Surface results are hypotheses, not evidence. They are associative leaps that may be metaphorical, tangential, or wrong — but they point toward something your linear reasoning may have missed.

1. Look for the hidden thread. Three associations that seem unrelated often share an underlying pattern. The connection between them is the signal, not any individual result.
2. Let associations inflect your thinking even when the topic doesn't obviously match. A surfaced memory about DNS failures while you're debugging payments isn't noise — it's saying "this has the shape of a resolution problem."
3. Hold relevance scores lightly. A medium relevance association may be the most important one. The scoring reflects semantic distance, not diagnostic value.

Wrong: "Inland Empire surfaced 3 memories: [list each one with summary]."

Right: "The surfaced associations share a pattern — they all involve systems that failed silently at integration boundaries. This payment refactor touches two integration boundaries."

Response:

{
  "status": "ok",
  "command": "surface",
  "result": {
    "context": "refactoring the payment module",
    "associations": [
      {
        "summary": "Payment webhook timeout issue was caused by missing retry logic",
        "type": "pattern",
        "relevance": "high"
      },
      {
        "summary": "User prefers explicit error types over generic exceptions",
        "type": "fact",
        "relevance": "medium"
      }
    ],
    "voice": null,
    "partial": false
  }
}

The voice field is always present but nullable. When non-null, it carries an orthogonal reading of the associations — a gut-level interpretation that may be metaphorical, impressionistic, or oblique. It is not a summary of the data above. Treat it as one more associative signal: absorb it, don't paraphrase it.

forget "<query>"

Selectively remove memories. Useful for clearing stale context, correcting wrong information, or pruning noise.

python3 scripts/inland_empire.py forget "payment webhook timeout"
python3 scripts/inland_empire.py forget --type context --before 7d

Options:

• --type fact|pattern|context: Restrict to one memory type
• --before <duration>: Forget entries older than duration (e.g., 7d, 30d)
• --dry-run: Show what would be forgotten without deleting

stats

Backend health and memory statistics.

python3 scripts/inland_empire.py stats

Response:

{
  "status": "ok",
  "command": "stats",
  "result": {
    "version": "2.1.0",
    "backends": {
      "graph": {"status": "available", "mode": "local"},
      "semantic": {"status": "available", "mode": "hosted"},
      "session": {"status": "available", "entries": 42},
      "voice": {"status": "available", "model": "mercury-small", "provider": "inception"}
    }
  }
}

Storage Architecture

Inland Empire unifies multiple backends behind a single interface. The user never selects a backend — routing is internal.

┌─────────────────────────┐
                  │     Inland Empire        │
                  │   (classify + route)     │
                  └────┬────────┬────────┬───┘
                       │        │        │
                ┌──────▼──┐ ┌───▼────┐ ┌─▼──────────┐
                │  Graph  │ │Semantic│ │  Session    │
                │ (facts) │ │(patterns)│ │ (context)  │
                ├─────────┤ ├────────┤ ├────────────┤
                │ LibSQL  │ │  Mem0  │ │   JSONL    │
                │ SQLite  │ │ Cloud  │ │   local    │
                └─────────┘ └────────┘ └────────────┘
                  always      optional     always

Backend detection (from environment):

• Graph: Always available. Uses LIBSQL_URL if set, otherwise local SQLite.
• Semantic: Requires MEM0_API_KEY. Gracefully disabled when not set — patterns stored in graph as fallback.
• Session: Always available. Local JSONL file in INLAND_EMPIRE_STATE_DIR.

When to Use

• Remember something that doesn't belong in code or config files
• Consult before making decisions that might repeat past mistakes — results are facts to evaluate
• Surface for the question what am I not seeing? — when starting unfamiliar work, when something feels familiar but you can't place it, or when linear reasoning has stalled
• Forget stale context that's no longer relevant
• Build institutional memory that survives context window compression

When NOT to Use

• Structured project data → use files, databases, or config
• Code-level documentation → use comments and docstrings
• Ephemeral debugging notes → use the session scratchpad, not persistent memory
• Anything that needs to be version-controlled → use git

Synergies

Inland Empire integrates with other Cognitive Construct skills:

• ← Rhetoric: Significant deliberation outcomes are worth remembering
• ← Encyclopedia: Research findings can be stored as facts
• → Rhetoric: Surfaced memories inform deliberation context
• → Volition: Recalled patterns guide action selection

Configuration

Error Handling

All commands return JSON with "status": "ok" or "status": "error":

{
  "status": "error",
  "command": "remember",
  "error": {
    "message": "Not initialized",
    "code": "NOT_INITIALIZED"
  }
}

Backend failures are isolated — if one backend fails, others still return results. The partial flag in responses indicates incomplete results.