Competitive intelligence that accumulates

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The scenario

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Step 1 — Record signals with the date they happened

client.record(
    space_id="competitors",
    content="Competitor X moved to usage-based pricing at $0.80 per thousand calls.",
    timestamp="2026-06-02T00:00:00Z",
    metadata={"source": "pricing-page", "competitor": "X"},
)

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Step 2 — Ask what changed over a window

print(client.reason(
    space_id="competitors",
    query="How has Competitor X's pricing and positioning moved since June?",
))

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Step 3 — See who and what keeps coming up

graph = client.get_graph(space_id="competitors", min_count=3)
for node in graph["nodes"][:10]:
    print(node["label"], node["mention_count"])

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Evals

1. Record ten dated signals across six months, including two that contradict each other.
2. Ask what changed. A good answer notes the contradiction rather than picking one silently.
3. Re-ask with occurred_after set to the midpoint. The answer should narrow.
4. Check get_graph surfaces the competitor names you actually recorded, and not a long tail of noise — if it does, your memories are too chatty and want tighter extraction settings.

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Guardrails

• Edges are co-occurrence, not typed relationships. The graph tells you two entities appear together and how often; it does not say one acquired the other. Do not present it as though it does.
• Contradictions are signal, not error. When a newer fact supersedes an older one, correct it explicitly with a reason rather than deleting the old one — the change is the intelligence.
• A source that stops reporting looks the same as nothing happening. Memory cannot tell you about the press release nobody fed it.

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