Launchify (sometimes styled Launchyfi) describes an “AI go-to-market engineer”: an agentic layer that can plan, run, and optimize a startup’s GTM motion from a chat-style prompt interface, instead of hiring a dedicated GTM engineer or stitching together an agency plus a chaotic toolchain. The emphasis is operating the revenue engine end-to-end, with specialist agents that connect to your stack and execute repeatable plays while founders stay focused on product and customer discovery. https://launchyfi.com/
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The workflow starts with deep CRM integration, treating the CRM as the source of truth for first-party pipeline data. Launchify analyzes historical deals to infer your actual ICP (not the aspirational one), then expands into firmographics like vertical, company size, and revenue bands. It also builds persona-level buyer maps (Head of Support, CMO, VP Sales, etc.), capturing pain points, motivations, KPIs, and common objections so targeting and messaging are grounded in proof.
From there, execution is framed as orchestration across sales-tech primitives: prospecting, enrichment, sequencing, and multichannel outreach. In practice that means automating lead discovery, attaching contact data, and running outbound via email plus LinkedIn automation, with guardrails around deliverability limits and LinkedIn throttling. The product focus in this clip is B2B SaaS outbound rather than paid acquisition, so signal-led segmentation and pipeline hygiene become the raw material for the agent.
Zooming out, the interview frames GTM engineering as a shift away from spray-and-pray volume toward a measurable system that continuously refines ICP and adapts to market signals. This was filmed at Web Summit Lisbon 2025, where the team talked about building in stealth, opening a waitlist, and onboarding startups in cohorts after the event at the booth.
For technical founders, the most useful lens is RevOps plus automation: clean objects, consistent stage definitions, and tight feedback loops determine whether an AI agent can create pipeline rather than activity. The evaluation is straightforward—conversion by persona, win-rate by segment, pipeline velocity, and CAC payback—while keeping human review for compliance, consent, and brand voice so execution stays aligned with intent and value.
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