Chris Olson
9131e83c08
Exa harvester: - EXA_CATEGORY=news (default) restricts to news articles, excluding evergreen careers/marketing landing pages that were producing irrelevant signals. - Event-focused query (acquisition/earnings/launch/leadership), dropped hiring/career terms that pulled recruiting pages. - Domain scoping now OFF by default (broad-web news about the account beats first-party careers pages); add EXA_EXCLUDE_DOMAINS and loop --domain-filter. LLM layer: - Remove the mock reasoner entirely (no provider => loop refuses to run). - On HTTP 429, WAIT (LLM_RATELIMIT_WAIT_SECONDS, default 900s; honors Retry-After) and retry up to LLM_RATELIMIT_MAX_RETRIES (24) instead of degrading to mock output. - If the LLM is ultimately unavailable for an account, skip it and leave its signals unconsumed (retried next run) — never fabricate briefs. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Prospecting Agent Loop
A closed-loop, account-intelligence system for enterprise sales prospecting: it monitors a list of target accounts, harvests business signals (news/web today; LinkedIn, job postings, and filings to come), evaluates them against a structured Capability Library of sellable products, and routes scored, signal-grounded opportunity briefs to the right rep — with rep feedback flowing back into scoring.
Contents
sales-prospecting-agent-loop.md— the full design document (architecture, agent loop phases, scoring, feedback loop, roadmap).sales-agent/— the runnable MVP. Seesales-agent/README.mdfor setup and usage.
Status (MVP)
- End-to-end loop runs: harvest → normalize/dedup → relevance filter → synthesize → score → deliver → feedback → recalibrate.
- Capability Library seeded with 40 real Broadcom + VMware capabilities.
- News connector: live Exa.ai with hard request ceilings (free-plan safe).
- LLM reasoning: provider-agnostic (Gemini or Anthropic), with an offline mock fallback so the pipeline runs without a key.
- Pilot accounts: 7 real companies wired in (~200 to follow).
Secrets live in sales-agent/.env (gitignored). See sales-agent/.env.example.
Quick start
cd sales-agent
cp .env.example .env # add your keys (Exa, Gemini/Anthropic)
python3 run.py loop # run the loop
python3 run.py digest # per-rep daily digest