OpenGTM
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About
OpenGTM functions as a specialized AI and Go-To-Market (GTM) research lab and product studio designed to help organizations transition into AI-native operations. At its core is PRISMA, a unified GTM ontology that serves as a foundational barcode for business growth activities. Unlike traditional dashboards that simply visualize data, this system decomposes, codifies, and recombines messy GTM signals, plays, and content into precise, machine-operable components. This structured framework allows companies to move beyond surface-level automation toward deep, agent-first execution where AI systems handle the operational load of sales and marketing. The platform operates on the principle of GTM SuperIntelligence, a framework that treats data, companies, and AI agents as a shared intelligence layer. This approach enables multi-company reasoning, where agents can analyze patterns and benchmarks across thousands of organizations to make more informed decisions. The tool is designed to facilitate agent-first environments, where AI agents act as the primary executors of GTM strategy while human team members focus on high-level vision, creative strategy, and relationship management. By providing a shared language between humans and machines, the ontology ensures consistency across disparate software systems. OpenGTM is primarily aimed at forward-thinking GTM leaders, AI architects, and organizational designers who are looking to rebuild their growth stacks from the ground up for the AI era. It is particularly relevant for companies that find traditional CRM and marketing automation tools insufficient for managing complex, agent-led workflows. The suite includes not just the PRISMA product, but also an open-source research lab and transformation services intended to guide legacy organizations through the cultural and technical shifts required for AI-native growth. What distinguishes OpenGTM from standard sales technology is its focus on the underlying architecture of business logic. Rather than offering another siloed tool, it provides the interoperable backbone that allows other software and AI agents to communicate and execute effectively. With its combination of academic-style research and practical transformation frameworks, it positions itself as a strategic partner for firms aiming to outgrow the repetitive drudgery of manual sales and marketing grinds.
Pros & Cons
Provides a structured ontology (PRISMA) to make GTM data machine-operable.
Focuses on agent-first execution to reduce manual repetitive sales drudgery.
Supports reasoning across datasets from multiple companies for better benchmarking.
Offers open-source research and resources through its dedicated GTM lab.
Includes a comprehensive GTM jobs index for professionals in the AI-native space.
High barrier to entry due to the complex nature of GTM ontologies and frameworks.
Specific pricing details are not publicly listed and require direct inquiry.
Many core resources, like the SuperIntelligence book, are still in a pre-release phase.
Requires a significant organizational shift toward AI-native operations to be effective.
Use Cases
GTM Architects can use the PRISMA ontology to codify messy sales signals into a structured format for AI agents to execute.
Sales Operations Managers can transition their teams from manual repetitive tasks to high-level strategic roles by implementing agent-first workflows.
Enterprise Leaders can leverage the multi-company reasoning capabilities to benchmark their performance against thousands of other organizations.
HR and Recruitment Teams can utilize the GTM Jobs Index to find or list roles specifically tailored for AI-native growth environments.
Platform
Task
Features
• strategic gtm podcast
• gtm jobs index
• gtm superintelligence framework
• open source gtm research
• ai-native org transformation
• multi-company data reasoning
• agent-first execution framework
• prisma gtm ontology
FAQs
What is the PRISMA ontology?
PRISMA is a structured framework that defines concepts and relationships within the GTM domain to create a shared language between humans and machines. It allows companies to decompose and codify messy GTM signals into precise, machine-operable components.
How does an agent-first approach differ from traditional GTM?
An agent-first company treats AI agents as the primary executors of GTM activities rather than just secondary add-ons. In this model, humans focus on vision and strategy while agents handle the operational load and scale of execution.
Does OpenGTM replace human workers?
No, it aims to elevate humans out of repetitive execution and into creative, strategic, and human-first roles. The goal is to automate the drudgery of manual GTM tasks so people can focus on high-value activities like relationship building.
What is GTM SuperIntelligence?
GTM SuperIntelligence is a framework where companies, data, and agents operate as a shared intelligence layer. It allows for advanced reasoning, prediction, and coordination of GTM decisions across the entire enterprise and across multiple organizations.
When will the GTM SuperIntelligence book be available?
The book is scheduled for release on November 28th, though OpenGTM members can access preview chapters and research excerpts earlier. It serves as a comprehensive guide for how agents should navigate the go-to-market landscape.
Pricing Plans
Membership
Unknown Price• PRISMA Ontology Access
• Early Book Access
• Research Excerpts
• GTM Transformation Guides
• Community Access
• Multi-company Reasoning
Job Opportunities
GM, Transformer
Structure scattered go-to-market data into a machine-operable ontology to enable agent-first operations and eliminate repetitive manual sales and marketing tasks.
Experience Requirements:
Builders who have led large-scale enterprise transformations in AI, digital, or GTM functions
Systems thinkers comfortable blending consulting, productization, and change management
Executives who thrive at the edge of advisory and execution
Leaders fluent in the language of enterprise buyers, transformation playbooks, and AI strategy
Responsibilities:
Leads OpenGTM’s enterprise transformation arm
Owns the entire transformation lifecycle: from diagnosis and design to implementation and adoption
Translates OpenGTM’s ontologies, frameworks, and agent protocols into real-world outcomes
Sets revenue strategy and oversees delivery
Builds the partner ecosystem
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GM, Research Lab
Structure scattered go-to-market data into a machine-operable ontology to enable agent-first operations and eliminate repetitive manual sales and marketing tasks.
Experience Requirements:
Leaders with experience running research organizations or data-driven strategy teams
Individuals who see GTM as a science
Deeply curious, multidisciplinary thinkers fluent in AI, economics, and market systems
Comfortable managing hybrid teams of humans, models, and agents producing open knowledge
Responsibilities:
Oversees the institution’s open-source GTM research agenda
Drives the roadmap for how OpenGTM codifies market knowledge
Ensures the Lab functions as both an R&D engine and a public institution
Leads a distributed network of researchers, AI systems, and contributors
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VP, Agent Relations
Structure scattered go-to-market data into a machine-operable ontology to enable agent-first operations and eliminate repetitive manual sales and marketing tasks.
Experience Requirements:
Executives who’ve built and scaled developer, partner, or marketplace ecosystems
Skilled communicators who can design policy, infrastructure, and trust frameworks
People who think in systems but lead with empathy
Leaders who understand both AI lifecycle management and human network operations
Responsibilities:
Leads the strategy, infrastructure, and community that power OpenGTM’s network
Defines the standards for agent onboarding, compliance, ethics, and interoperability
Acts as the connective tissue between technology, agents, and companies
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