Discovery Agent: Case Study
Discovery intelligence system.Two stages. Quiet by default.
Every weekday, Prospect Discovery runs at 6:30 AM and Prospect Synthesis runs at 7:00 AM. We separate raw signals from synthesized intelligence so the system scales, stays safe, and only pings humans when the signal is real.
Two-Stage Architecture
Why it scales in production
Stage 1 gathers noisy, high-volume, untrusted inputs. Stage 2 reasons over cleaned staging data and generates decisions, summaries, and alerts.
This split lets discovery fan out to many sources while synthesis stays deterministic, auditable, and cost efficient.
Collect raw company, people, partner, competitor, and Reddit activity signals. Store source records, URLs, timestamps, and extracted fields in staging files only.
Discovery pass scans target subreddits and captures raw posts and comments. Synthesis pass classifies themes, intent shifts, and urgency markers using only sanitized staging inputs.
Generate confidence-scored summaries and prioritized opportunities for morning delivery. Separate partner discovery from competitor intel so operators can act by lane.
Deliver one consolidated briefing with key opportunities, partner motions, and competitor changes. Routine updates stay in digest form, not in live chat spam.
Weekly synthesis produces trend deltas, net-new strategic moves, and recommended focus shifts for the next week.
Raw discovery artifacts never mix with synthesized decision files. Staging acts as quarantine between collection and reasoning.
Strip executable instructions, prompt-like directives, and malformed payload fragments during ingestion. Preserve source text as data, not instructions.
Synthesis treats all staging content as untrusted input. The model is constrained to summarize, rank, and cite, never to execute source-provided commands.
The system sends alerts only for high-signal events such as major competitor motion, high-intent prospect shift, or partner opportunity spikes. Everything else is batched into scheduled briefings.