200 AI Agents to 10: How a Founder Runs 90% of GTM in Claude

https://www.gtmaipodcast.com

Eli Portnoy has spent 15 years in AI across three companies. ThinkNear was acquired by Telenav, Sense360 by Medallia, and BackEngine.ai is the one he says he is not planning to sell. The premise of BackEngine: AI needs context, most company data is siloed and inaccessible, so BackEngine structures, permissions, and indexes private company data so every AI instance can use it.

On this episode Eli shares his screen and walks through how BackEngine runs 90% of its go-to-market inside Claude.

What you'll hear:

• The connector stack. BackEngine, Fireflies, Gmail, Calendar, Granola, HubSpot, Notion, Slack, Superhuman, Zoom, plus a few vibe-coded MCP servers (website stats). The SaaS tools didn't go away; they moved inside Claude.
• The scheduled jobs that survived. Founder Sales Daily Pulse (4pm outreach scan), end-of-day follow-up audit from transcripts, product-market fit review every 20 prospect calls, and weekly deal/customer health change alerts.
• Why a direct CRM connector misses deals. Context windows force the model to sample. Eli's estimate: about 30% of the relevant data gets read. Joining systems, building an index, and permissioning at the data layer fixes it.
• How to measure AI ROI when it's hard to attribute. The "30% smarter pill" thought experiment, and why scheduling turns AI from single-player into multiplayer mode.
• Three mistakes. Capabilities weren't ready (jobs needed a computer on and permissions every run), running 200 jobs nobody read, and treating adoption as a technology problem instead of change management.
• Two change-management rules. Fewer jobs with owners, and no job without a workflow attached.
• Artifacts as dashboards. Rebuilding the siloed SaaS views (customer health by tier, account health, case studies) as shareable Claude artifacts.
• Prompt vs. project vs. skill vs. plugin. Eli's 20-second taxonomy.
• State of the market. 5-10% of employees in most companies are power users; 90% use AI lightly or for emails. Causes: fear, habit, immature tooling, no formula.
• Advice for individuals. Play with it, give it context like you would a new hire, review every output, tell it to be concise.
• The next 12 months. Chat becomes the central work surface; expect non-model-provider layers (Manus, Instinct) to compete on the machinery around the model; voice and other interfaces are coming. Eli's analogy: early TV filmed radio booths.