Chris Olson
c2854ba163
- LLM: Anthropic Sonnet 5 (effort=low) via OAuth Bearer (Claude Code keychain token, expiry-aware); NVIDIA/LM Studio endpoints kept commented for switch-back. - Entitlements: scripts/import_entitlements.py joins ACL export to accounts by normalized parent name (324/342 matched; ID column Excel-corrupted), maps products->capabilities via data/product_capability_map.json. Raw ACL csv and entitlements.json are gitignored (confidential); accounts.json carries derived currentProducts + ownedCapabilityIds. Owned capabilities tag briefs EXPANSION. - Renewals: local renewal-proximity score boost (window 365d, max +0.10) + 'renewals' report; briefs/digests show RENEWAL WINDOW context. - Batch runs: loop --limit/--rep with persistent cursor (strategic + stale-first). - Digests: per-rep HTML export; timestamped digest_<date>_<time>.md kept forever. - Account narrative memory fed into relevance/synthesis; synthesis maintains it. - Signal quality gate drops PR fluff pre-LLM; SEC EDGAR filings connector. - Citation verification: talking points must cite [S#] signals or are dropped. - Brief filenames use account-name slug; whitespace report + installed-base view. - USAGE.md: full command/flag/env reference. Co-Authored-By: Claude Fable 5 <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