Why GTM OS?

We’re on the precipice of a new era as we put AI to work. AI isn’t just another tool, it’s our opportunity to rethink how Go To Market operates. At Poexis, we are building the Agentic Operating System for GTM: to deliver faster, more efficient growth at scale.

This article kicks off a three-part series on what we’re building, why it matters, and how early adopters are already using it:

• Part 1: Why and Why Now
  The systemic GTM pain points we’ve faced, where early AI efforts fall short, and why this moment demands a new operating model.

• Part 2: Deep-dive: What and How’s it Different
  How the GTM OS works under the hood, what makes it “an operating system”, and how it differs from other approaches in this space.

• Part 3: Use Cases and What’s Next
  Real-world examples from our early customers seeing results, and a look at what’s coming next.

The GTM Crisis

There is no sugar coating it - GTM is in a deep crisis.

Sales & Marketing has long been not only the biggest driver of OpEx, but also the most inefficient. Spend is increasing, yet seller productivity and quota attainment have barely improved in decades. It’s also notoriously ineffective. Buyers are overwhelmed by noise - blasted with content that lacks empathy or relevance. Emerging from the great COVID pullback, many industry analysts had noted the SaaS math will break unless GTM teams can grow faster, more efficiently. And it’s getting worse.

According to the Benchmarkit B2B SaaS Performance Metrics Benchmarks:

• Growth is stalling across the board - for the third year in a row
• New Customer Acquisition Costs are rising: In 2024, it shot up by 14% - the median is now $2.00 per $1.00 of new ARR acquired
• At the same time, marketing budgets are increasing - with very few teams tracking efficiency, let alone improving it

Stalling with AI

For decades, GTM technology has promised a growth flywheel - a GTM engine that compounds. We’ve seen waves of GTM technology innovation: from CRMs and MAP in the early 2000s to Sales Engagement, Revenue Intelligence and now AI.

While there’s been early success for Gen AI in use cases like content generation and research, deeper transformation around faster more efficient growth has yet to materialize.

For instance, according to the McKinsey 2025 Global Survey on AI:

• Only 21% of companies are seeing a decrease in Sales & Marketing costs of more than 10%;
• Only 8% are seeing a revenue increase of more than 10%

That’s a sobering return for all the investment and hype. Most GTM organizations are still stuck in first gear and leaders are asking the right questions: Will Agentic AI deliver - or just spin harder in first gear, kicking up more noise than results?

The answer of course is - it depends on how we put AI to work.

Economic historians have long noted a pattern: transformative technologies like electricity, computers or AI - only yield impact when they trigger new ways of working - not when they’re simply bolted onto legacy systems or deployed as tools on the periphery.

Consider electric motors at the dawn of the 20th century. Factories didn’t see real productivity gains until they restructured workflows around electric power, rather than simply replacing steam engines one-for-one.

Agentic AI - demands the same rethink. It’s not about adding co-pilots or one off agents bolted onto legacy GTM motions or sprawling tech stacks. What is needed is a new operating model - one where agents coordinate, reason, and act with precision at scale across silos and throughout the funnel.

Designing a new way to GTM

Like many builders, we were thrilled to experiment with BERT, GPT 3, and other LLMs around the turn of this decade. However, as B2B operators who spent two decades in software, it was also clear that this moment demanded a new way to operate.

We were fortunate to engage with and learn from Sales & Marketing leaders across dozens of companies on what a new AI-native GTM operating model should look like. Three core principles emerged:

1. Operate as one GTM
   Sales, Marketing, Product, CS, and Partners must move in sync - aligned by shared data, shared goals, and shared execution. Silos slow down. Coordination compounds.

2. Reason with data to act with precision
   Need to combine structured and unstructured data, and real-time signals to drive timely, intelligent action - focusing where fit and intent are real, and acting while the moment is hot.

3. Optimize for net outcomes, not just activity
   Don’t measure just content generated, tasks automated or work performed - its the outcomes that ultimately matter.

Agentic OS for GTM

The Agentic Operating System is the foundation of how GTM works in the AI era. As a system of intelligence and execution, it orchestrates demand at scale. It coordinates agents to sense signals 24x7, reason about them, undertake actions across channels to drive outcomes.

It does the heavy lifting - so your sales & marketing teams don’t have to

• Scale agents and compute on demand
• Enforce controls and policies on agents and data
• Provide collaborative design surfaces for agents and humans
• Guarantee reliability and determinism where it’s required
• Ensure end to end visibility on agents, usage and actions

Just like an OS on your phone or server, GTM OS runs multiple agentic applications, and you can build your own agents or workflows to extend what’s available out of the box.

Ultimately, what’s most interesting about an Agentic OS isn’t about what it is, or how it does what it does - it’s all about what it makes possible.

For instance, one of our customers used it to roll out an ABX program 500x faster, achieving a 1750% ROI. Another one is using it to accelerate partner co-sell motion with a 24x7 partner co-sell assistant and an orchestrated demand generation campaign. More on that and other use cases in Part 3.

What’s in a name?

Poexis is a portmanteau of two words in Greek and Latin,

• Poiesis (Greek): To bring to life, to create
• Praxis (Latin): To act, to execute

Together they capture our mission: bringing to life a new way to GTM powered by Agentic AI.

Next week, we’ll dive deeper into how the GTM OS works and what makes it fundamentally different from other approaches.