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Notes from the data layer

Agent-driven GTM · written as we build it

Latest · enrichment

Keeping Enriched Fields Fresh in an Autonomous Outbound Loop

Autonomous outbound agents run at five times the throughput of a human SDR — which means stale enrichment data compounds into system-level failures, not…

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  1. How to Enrich a Contact List for Your AI Agent

    AI agents acting on bad enrichment data don't catch errors — they scale them. This post breaks down the seed-to-intelligence pipeline your AI agent…

  2. The Best B2B Enrichment API for Autonomous Agents (And Why Failure Rate Beats Throughput)

    Autonomous agents fail at machine speed when enrichment data is wrong — and most B2B enrichment APIs were designed for humans in the loop, not agent…

  3. Company and Contact Data with Citations and Confidence Scores — What the abm.dev API Actually Returns

    The abm.dev API returns company and contact enrichment data with field-level citations and confidence scores, aggregated from ten providers into…

  4. MCP Enrichment: Giving Your AI Agent a Verified Data Layer It Can Call Over MCP

    AI agents fail when they act on unverified enrichment data at machine speed — bad emails, stale titles, confidence-free fields passed as ground truth.…

  5. Introducing abm.dev — the ABM data layer your AI agents can call

    Launch announcement: abm.dev is an agent-first ABM enrichment API. Open beta, $20 free credits.