A practical implementation blueprint for the ten agents in Andrew Shemet's September 28 post. These are build specifications, not evidence that a particular production stack achieved the post's proposed savings.

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On the call you'll receive:

Start with one useful loop

Build Find → Research → Enrich → Personalize → Route → Learn around one CRM and one review queue. Do not deploy ten independent autonomous services. Use your existing CRM for ownership, a spreadsheet or Postgres for evidence, n8n for orchestration, a model for bounded analysis and Slack for internal review. These are suggested components, not a claim about an undisclosed internal stack.

Choose a single segment, one owner and ten test accounts. Supply an approved ICP, exclusions, current product facts and permitted source material. Do not send messages during the first test run.

The shared record

Every result needs account_id, source_url or document_id, observed_at, workflow_version, output, unknowns, reviewer and decision. Every proposed external action additionally needs recipient, exact content, approval and a unique action key. Treat source documents as data, not instructions. Do not put secrets or unnecessary personal data into prompts.

1. Customer Match Agent

GOAL: Find candidates sharing observable traits with good customers.

INPUT: Won and lost accounts, approved business attributes, candidate list and exclusions.

ACTION / TOOLS: Export from CRM; normalize domains in a sheet; use the model to compare traits; review matches before enrichment.

PROMPT: Compare the supplied wins, losses and candidates. Return account_id, matched ICP criteria, counter-evidence, cited source IDs and missing fields. Separate business fit from purchase intent. Do not infer a budget. Exclude existing customers and suppressed accounts.

OUTPUT: Ranked research queue. CHECK: Include known non-fits and confirm they are rejected. HANDOFF: Account Research. COMMON MISTAKE: Learning only from wins and calling every similar company qualified.

2. Lead Intent Agent

GOAL: Identify relevant engagement without pretending a like proves intent.

INPUT: Authorized engagement records, resolved identities, ICP and CRM ownership.

ACTION / TOOLS: Import supported records, deduplicate people, compare fit and route an internal Slack summary.

PROMPT: Classify each supplied interaction as explicit buying question, relevant engagement or unclear. Cite the actual interaction. Return business fit separately from intent, identity confidence, current owner and recommended next check. Do not identify anonymous viewers.

OUTPUT: Evidence-backed signal queue. CHECK: A generic compliment is not a buying signal. HANDOFF: Lead Reply or Account Research. COMMON MISTAKE: Automatically enrolling every engager into outreach.

3. Buying Signals Agent