AI-Native GTM Architecture

Applied methods for embedding AI into real business architectures, exposing where systems break, where they hold, and the risks in between.

AI-ASSISTED CREATION

Held February 12, 2026 • Event Ended

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Event Overview

One goal. Infinite operating models.

Architecture can work against AI. With 95% of AI deployments failing, architecture is the determining factor in whether AI creates value or erodes it.

The 2026 challenge is defining what AI-native GTM architecture actually is: a discrete function or a system-level operating construct that integrates agentic scaling, distribution, AI-native workflows, and agent swarms. Does it operate independently, or as a holistic architecture connecting the business end to end? And is it owned by a CXO role or governed as a distinct capability through mechanisms such as architectural review boards that evaluate and approve AI investments rather than leaving design to individual teams?

AI Practice Sessions focus on applied methods for integrating AI into real GTM architectures. The sessions examine where AI initiatives fail, where they succeed, and why, enabling leaders to compare approaches and clearly understand the risks they choose to take.

System Architecture

Understand where AI belongs in GTM systems, how it connects functions end to end, and why tool-first deployments fail at scale.

Failure Patterns

See where AI GTM architectures broke, stalled, or scaled and the architectural decisions that determined each outcome.

Operating Models

Compare AI-native GTM operating models and determine which structure fits your maturity, governance requirements, and growth ambition.

System Architecture

Understand where AI belongs in GTM systems, how it connects functions end to end, and why tool-first deployments fail at scale.

Failure Patterns

See where AI GTM architectures broke, stalled, or scaled and the architectural decisions that determined each outcome.

Operating Models

Compare AI-native GTM operating models and determine which structure fits your maturity, governance requirements, and growth ambition.

Event Preview

Get a firsthand look at how AI-native GTM architectures operate in practice—where agentic systems scale, where architectures break, and how governance determines outcomes.

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Agenda

Recordings

Access recordings of all ten intensive, 30-minute sessions.

Session 1

8:30 am PT

Why Your AI GTM Stack Will Fail (And How to Fix It)

Session 2

9:00 am PT

Operationalizing Revenue Decisions with AI

Session 3

9:30 am PT

Retention as Architecture: Governing AI Where Revenue Is Actually Lost

Session 4

10:00 am PT

AI Teammates in the Revenue Workflow

Session 5

10:30 am PT

Building an AI Workforce for GTM Execution

Session 6

11:00 am PT

Drive Expansion With AI (Without Breaking Your CS Stack)

Session 7

11:30 am PT

Building and Validating Research Agents in GTM

Session 8

12:00 pm PT

100× Your Campaign Launches Using Claude Code

8:30 am PT

Applied AI Framework

Why Your AI GTM Stack Will Fail (And How to Fix It)

Most companies bolt AI agents onto broken architecture and wonder why nothing works. Amos shares what he learned building Swan AI’s autonomous GTM engine – the 3 architectural decisions that separate the 5% who create value from the 95% who erode it.

Presented by

CEO & Co-Founder, Swan AI

Amos Bar-Joseph

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

9:00 am PT

Applied AI Framework

Operationalizing Revenue Decisions with AI

This session looks at how AI is used inside GTM systems to explain deal movement, surface risk early, and support consistent decisions across Sales, RevOps, Marketing, and Finance. A practical view of how teams analyze CRM, calls, email, and activity data together—showing not just what is happening in pipeline, but why.

Presented by

Co-Founder & CEO, Von

Sahil Aggarwal

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

9:30 am PT

Applied AI Framework

From Workflows to Judgement: Designing AI-Native Customer Success

Most GTM and Customer Success systems were designed to automate execution – workflows, playbooks, and predefined journeys.
That approach works when customers behave as expected. It breaks when they don’t.
In this session, we’ll explore what it really means to design AI-native Customer Success – where agents don’t just execute steps, but own outcomes.

We’ll cover:

Why workflow- and journey-based CS architectures hit a ceiling at scale
Where traditional GTM stacks break under adaptive, real-time decision-making
What changes when you automate judgement (instinct + execution), not just tasks
How outcome-owned agents continuously evaluate, adapt, and replan for each customer
Where human-in-the-loop controls are critical to trust, governance, and scale

This is a practical look at moving from static workflows to adaptive, outcome-driven Digital CS — and what that shift means for GRR, NRR, and modern GTM architecture.

Presented by

VP, Customer Growth, Hook

Natasha Evans

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Founding GTM, Hook

Sam Champion

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

10:00 am PT

Applied AI Framework

AI Teammates in the Revenue Workflow

This session examines how AI is embedded directly into sales workflows before, during, and after customer interactions. Using real examples, it looks at how reasoning models, shared context, and system integration support live selling moments, improve deal quality, and scale execution without fragmenting GTM operations.

Presented by

VP of Solutions, Vivun

Brett Crane

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CMO, Vivun

Jarod Greene

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

10:30 am PT

Applied AI Framework

Building an AI Workforce for GTM Execution

This session looks at how GTM teams build AI workers that run real workflows. It covers how no-code agents are defined in plain language, connected to systems and data, and deployed across sales, marketing, and operations to increase capacity, standardize execution, and support repeatable GTM processes. If you’re expected to lead AI efforts in 2026, this is where you start. Get a proven playbook from an AI leader who’s already navigated the roadblocks you’re about to hit.

Presented by

Head of Marketing, EverWorker

Ameya Deshmukh

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

11:00 am PT

Applied AI Framework

Drive Expansion With AI (Without Breaking Your CS Stack)

Customer Success is now accountable for revenue, not just relationships. But AI only creates value when it’s architected into the system, not bolted on.

This session shows how embedding expansion intelligence directly into existing CS workflows (using customer data, historical success patterns, and proven plays) surfaces where growth is most likely and guides action without adding tools or friction. Attendees will learn how an architecture-first AI approach helps CS teams drive repeatable expansion revenue while preserving efficiency and trust.

Presented by

Senior Product Manager, Staircase AI, Gainsight

Brady Bluhm

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

11:30 am PT

Applied AI Framework

Building and Validating Research Agents in GTM

This session demonstrates how GTM teams build research agents to gather, validate, and standardize information at scale. It covers agent setup, accuracy checks, and output design, with examples of how research agents support prospecting, enrichment, and RevOps workflows without creating inconsistency or noise.

Presented by

Co-Founder, The Kiln

Patrick Spychalski

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

12:00 pm PT

Applied AI Framework

100× Your Campaign Launches Using Claude Code

Capture and operationalize your GTM context with AI. Claude functions as an execution engineer by holding, reusing, and applying context across launches. In this session, you will:

Configure Claude with your company’s real GTM context
Identify the highest-fit segments within your actual TAM
Generate messaging grounded in your own data and signals
Compound campaign launch speed by reusing and evolving context across launches

By the end of this session, you’ll be able to run campaigns with an order-of-magnitude increase in execution efficiency and materially higher output quality than traditional SDR-led workflows.

Presented by

Founder of Blueprint GTM

Jordan Crawford

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Top Questions

Explore the most compelling questions that resonated with the HSE community.

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Join the HSE Slack

A private executive network where GTM leaders, CXOs, VCs, and analysts share operating models, validate AI-native architectures, and turn innovation into deployable GTM systems.

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Meet AI Practice Sessions Partners

AI Practice Sessions Highlights

Explore how forward-thinking organizations operationalized AI – scaling agentic workflows, deploying multi-agent systems, and reimagining GTM.

Power-Law User Acquisition in the Age of AI

Superhumans for AI-Led Growth (AI-LG)

The One-Person GTM Org

The Strategic Signal Squad

Precision GTM: The RevOps Lever Stack

The GTM Content Engine Method

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Reimagine Your GTM Architecture

Work 1:1 with operators who have designed, governed, and scaled AI-native GTM architectures, examining the structural choices that determine where AI compounds value, where it breaks systems, and how execution fragments or coheres.

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AI-Native GTM Architecture

One goal. Infinite operating models.

Recordings

Join the HSE Slack

Sponsors

AI Practice Sessions Highlights

Reimagine Your GTM Architecture