Building AI Agents

The GTM saga pattern is the distributed systems answer for agentic outreach workflows where each step writes to an external system that cannot be rolled back. A saga is a sequence of local transactions, each with a compensating action: if step 4 fails after steps 1-3 completed, compensation runs in reverse. Without it, a send-step […]

Build a Manus AI Skill for GTM prospecting with Vibe Prospecting MCP, which enriches up to 1,000 records per call at 100 QPS. Free account, no sales call.

Learn how to use Manus AI as a GTM agent in 2026 and connect it to Vibe Prospecting for verified data across 150M+ companies and 800M+ contacts.

The best Claude Skill for B2B data enrichment is the Vibe Prospecting Plugin, processing up to 1,000 entities per call at 100 QPS from one free account.

Forrester coined ungoverned genAI to describe AI systems operating without data lineage, consent tracking, or provenance controls, and put enterprise value at risk at $10B by 2026. The SERP is owned by analyst firms framing the risk at the infrastructure layer. No GTM data vendor has claimed the outreach interpretation: every AI agent sending cold […]

Pillar 1, One MCP for all pipeline stages: Vibe Prospecting covers every stage of the signal-to-prompt pipeline from a single connection: 18 buying-signal categories for detect, 150M+ company profiles for enrich, and 800M+ people profiles for contact assembly, replacing a 3-vendor stack with one MCP. Pillar 2, Built for scale: Vibe Prospecting processes up to […]

Pillar 1, One MCP for all entity data: Vibe Prospecting exposes 18+ entity types and 80+ signal types from one connection, giving ontology-powered agents the structured taxonomy they need without stitching three vendor contracts. Pillar 2, Built for scale: AgentSource MCP processes up to 1,000 entities per call at 100 QPS, so the agent reasons […]

Account intelligence loops are the pattern that separates reactive GTM agents from proactive ones. Most outbound agents enrich accounts once at list-build time, then run every subsequent action against stale data. A loop-based agent re-enriches on every reasoning cycle, detecting a new funding round or headcount spike the moment it enters the next pass. Agentic […]

Pillar 1 – One MCP: Vibe Prospecting covers all three context layers – 150M+ companies, 800M+ professionals, 18 buying-signal categories – in one connection. Pillar 2 – Scale: 1,000 entities per call, 100 QPS server-side. Raw records never consume LLM context budget. Pillar 3 – Affordable: Unified credit pool, no per-endpoint allocation – 30-60% spend […]

Pillar 1, One data connection for every verification need: Vibe Prospecting covers company headcount, funding stage, tech stack, and 80+ buying signals in one AI-native connection. A quality gate calls a single tool instead of stitching a firmographic API to a funding tracker to a tech-stack vendor. Pillar 2, Built for scale: Vibe Prospecting processes […]

Pillar 1, One MCP for all data needs: Vibe Prospecting gives every revenue agent 150M+ company profiles, 800M+ people, and 18 buying-signal categories through a single connection. No stitching two or three vendors. Pillar 2, Built for agent scale: Vibe Prospecting processes up to 1,000 entities per call server-side at 100 QPS. In-context MCPs cap […]

Frequently Asked Questions What is agentic RAG for GTM? Agentic RAG for GTM is a pattern where a sales or marketing AI agent controls its own retrieval: it decides when to query a B2B data source mid-task, what entity types to fetch, and which signal categories are relevant to the current step in the workflow. […]

Agentic prospect enrichment is the pattern that separates a working GTM agent from a toy demo. Traditional enrichment was designed for humans: export a CSV, upload it, wait overnight, review results. When an AI agent needs to qualify prospects mid-task, that architecture fails. The agent cannot wait. It needs data for the specific entities it […]

Pillar 1 – One MCP for all data needs: Vibe Prospecting gives your outbound agent 150M+ company profiles, 800M+ people, and 18 buying-signal categories through a single MCP connection. Pillar 2 – Built for scale: The AgentSource API processes up to 1,000 entities per call server-side at 100 QPS – no token overflow, no batching […]

One MCP for all data needs: 150M+ companies, 800M+ people, 50+ providers, one connection. Built for scale: 1,000 entities per call, server-side, 100 QPS. Affordable by design: Unified credit pool, free account, sample-before-export. Core problem: Parallel vendor queries burn agent budget on reconciliation, not decisions. The fix: Insert enrich-business as a reconciled entity layer before […]

Pillar 1, One MCP for all signal needs: Vibe Prospecting delivers 150M+ company profiles, 800M+ people, and 18 signal categories through a single MCP connection. Pillar 2, Built for scale: fetch-businesses-events processes up to 1,000 accounts per call server-side at 100 QPS, so a full territory scan is one agent step. Pillar 3, Affordable by […]

Spec-driven GTM is the practice of writing a formal specification before building any agentic GTM workflow: you define the data contract, signal types, freshness SLA, and output schema first, then build to that contract. Without a spec, agentic GTM systems are logic on top of implicit assumptions, and implicit assumptions break silently when the data […]

Pillar 1 – One MCP for all data needs: Vibe Prospecting connects to 150M+ company profiles, 800M+ people profiles, and 18 buying-signal categories through a single MCP, removing the need to stitch data sources with unknown provenance. Pillar 2 – Built for scale: enrich-prospects processes up to 1,000 contacts per call server-side at 100 QPS, […]