Stacked GTM

Cliff Simon, CEO & Founder of Polaris Ops, walks Andy and Noah through structuring GTM engineering across the full lead-to-cash cycle. From uncovering six months of AI Apex slop in a client's Salesforce org to crafting custom signal plays that outperform off-the-shelf data, Cliff shares what he's learned across 20+ engagements in 14 months.Topics discussed:Build versus buy decisions for GTM engineering projectsTotal cost of ownership for AI-built GTM systemsStructuring context layers with knowledge graphs and memoryPositioning GTM engineers inside centralized RevOps teamsCleaning up AI-generated Apex slop in Salesforce instancesCrafting custom signals that outperform commodity data vendorsRunning five go-to-market plays that reinforce each otherMicro SaaS as a future path for GTM engineers

Amanda Kahlow founded 6sense. Her new company, 1mind, deploys AI "Superhumans" that orchestrate roughly 15 agents to solution, demo, and close across the full buyer lifecycle, replacing the traditional SDR-to-AE-to-SE handoff chain.Amanda shares how her Superhuman "Nigel" joined a live meeting, held 31% of the talk time, and helped close a $262,000 deal in 11 days. She breaks down why solving for growth over efficiency changes how you build and staff your entire GTM org.Topics discussed:Orchestrating 15 agents per Superhuman across buyer lifecycleClosing a $262,000 deal in 11 days with AIShifting GTM from seller control to buyer controlUsing Superhumans for post-call sales coachingBuilding outbound without creating a bad buying experiencePricing Superhumans at the cost of a humanMeasuring deal cycle compression and ACV growthDeploying personalized Superhumans across ABM campaigns

Philip Cooper, Chief Customer Officer, Agentforce Sales at Salesforce, explains how the CRM is being rebuilt around agents, ambient data capture, and headless architecture. With the Momentum acquisition powering a self-driving CRM and MCP exposure decoupling sellers from the UI, Philip lays out what happens when the system of record starts updating itself.Philip walks Noah and Andy through why the semantic layer still matters for consistent definitions, how Slack is becoming the bidirectional system of work where sellers forecast and invoke agents, and how revenue leaders can delegate business outcomes to orchestrated agent workflows.Topics discussed:Positioning Agentforce as a horizontal capability layer across cloudsAuto-updating CRM through Momentum's conversation captureExposing Salesforce headlessly through MCP for agent integrationUsing memory fragments to surface undiscovered deal insightsLayering a semantic layer on unstructured data for consistent KPIsTurning Slack into a bidirectional system of work with CRMOrchestrating revenue outcomes by delegating to multi-agent workflowsShifting the build vs. buy calculus with opinionated agent deployment

A mining safety company needed to find prospects, and no pre-built tool existed for that niche. Jai Toor at Deepline pointed a coding agent at the problem. It found a Reddit ML model, combined it with hiring signals, and delivered qualified contacts in under 30 minutes.Jai walks through Deepline's developer-first approach to GTM data infrastructure, from waterfall enrichment to deploying deterministic code-based workflows. He shares how close-lost analysis surfaces niche buying signals specific to each company.Topics discussed:Building code-native GTM infrastructure designed for coding agentsUsing waterfall enrichment across multiple data providers programmaticallyDiscovering niche buying signals through close-lost regression analysisDeploying deterministic plays from iterative agent testingAdopting pay-as-you-go pricing inspired by OpenRouter's modelCentralizing data while decentralizing agent-based rep interfacesGenerating org charts from multiple data sources at $7 eachPredicting cold call answer rates with ML-driven scoring models

Austin Hughes, Co-Founder and CEO of Unify, joined Noah and Andy to make the case that offer based outbound is quietly beating the classic ask for a meeting.Austin walks through why Unify skipped Inbound entirely, how offer based outbound is beating classic meeting asks, and why he still believes reps need to own their own prospecting decisions even as agents take over the grunt work. Topics discussed:- Building offer based outbound instead of meeting asks- Why Unify skipped Inbound as a use case entirely- Letting reps buy in individually before Rev Ops gets involved- Owning a company wide context graph in the data warehouse- Why AE demand surprised Unify more than SDR demand- Why teams now want predictability and cost over frontier models- Advice for hiring the first two outbound reps- Why rep agency still matters as automation increases