The 3 Laws of Go-to-Market Strategy from Clay’s Varun Anand

Everyone’s talking about AI agents and workflow automation, but at INBOUND 2025, Varun Anand, co-founder of Clay, brought the conversation back to what really drives growth: go-to-market strategy.

Only this time, he reframed the fundamentals through a new lens as: The Three Laws of GTM Physics.

What actually powers sustainable, scalable growth in the AI age? Turns out, it’s about adopting a new operating system for how you grow. If you're leading a startup, owning revenue, or shaping B2B strategy, this framework will help you build a growth engine for speed, differentiation, and scale.

Let’s break it down.

The Three Laws of Go-To-Market Physics

Law #1: Find Your Unique Advantage

"You win when you know something about your customers that no one else does," Anand stressed.

He calls this concept go-to-market alpha: a unique, actionable insight that lets you reach the right customer at exactly the right time.

Most companies rely on what he references as commodity targeting. They're sending generic messages at generic times, with no real understanding of urgency or context. To stand out, you need sharper signals and specific data points that reveal when a customer truly needs what you offer.

Take Anand’s example: if he were running a cookie business in New York, a key signal might be the moment private equity acquires Levain Bakery. Why? Because PE buyouts often lead to cost-cutting that erodes product quality, creating an opening to win over disappointed customers.

Your job is finding your version of that signal.

“Each time you refine your targeting to beat your competitors with something like this, you're obeying that first law.” — Varun Anand

Law #2: No Creative Advantage Lasts Forever

AI tools can compress campaign timelines, but they also make it easier for competitors to copy your playbook. AI accelerates that lifecycle.

Anand compared it to the career arc of Taylor Swift: constant reinvention is what keeps her ahead. In marketing terms, that means new channels, new positioning, new campaign formats. Especially in AI-saturated channels like LinkedIn, email, and SEO, GTM leaders need to continuously evolve.

The winners constantly reinvent themselves with iterative speed that keeps them ahead.

“No creative advantage is going to last forever because as you scale up a strategy, other people will copy it and then it will stop working.” — Varun Anand

Law #3: Iteration Speed Determines Who Wins

Success comes to those who experiment, learn, and adapt faster than everyone else. Anand shared some examples of what this looks like in practice:

Canva's GTM team monitors social media posts to identify off-brand content, then reaches out to design heads with proof of the problem and a solution. They're not asking if you have a problem, but showing you that you do (along with a way to fix it).
A logistics staffing company used satellite imagery and AI to count parking spots at warehouses which became the best predictor of warehouse size when traditional data didn’t exist.
A medical practice software company analyzes insurance payment code changes every 90 days and alerts practices the morning changes go live, with detailed impact breakdowns and templated letters for insurance companies.

"It's confident, it's creative, it's quick and it's timely." — Varun Anand

Ask Better Questions. Find Hidden Signals.

"What do I know about my best customers that no one else does? That is going to be your best predictor for go-to-market success than anything else," Anand commented.

Start by asking:

What is your best sales rep doing that others aren't?
Which customers keep wanting to expand?
Where are your prospects having conversations?
What's the common thread in your support queue?

These answers reveal "hidden signals", or the insights scattered across your company that become golden when you systematize them.

Three Approaches to AI-Powered GTM

AI can do a lot. But what’s the right way to apply it to go-to-market? Anand broke down the three most common approaches

Approach #1: AI Automates Everything: AI SDR companies promise full automation, but the technology isn't there yet. Plus, it's a black box without flexibility.

Approach #2: AI Improves Every Rep Incrementally: GTM copilots help, but improvements are incremental and training is heavy.

Approach #3: Build Better Workflows (The Winner): Centralize manual research into one ops team that builds systems to auto-detect when customers have burning needs. This approach makes reps better and enables your best reps to do things they never could before.

At Clay, Anand shared that reps started building personalized apps for customers instead of doing manual research. "One person with the right approach can make 50 reps way more effective," he highlighted.

Enter the GTM Engineer

The most successful companies today are treating go-to-market like a product function, complete with:

Product managers
Engineers
Revenue operations specialists

Traditional assembly-line GTM structures (SDRs → AEs → RevOps) lead to standardization that kills innovation. Instead, put GTM engineers at the center, working with sales and marketing to test ideas, build systems, and scale what works.

“We’d like to call them GTM engineers… the role has just exploded since we coined it two years ago.” — Varun Anand

Even three-person startups can adopt this mindset. One person can wear the GTM engineer hat, all they need is to have the experimentation mindset.

There is No Silver Bullet

Anand didn't offer one super-powered tactic because there isn't one. AI will improve, tools will evolve, but the physics remain: creative advantages don't last forever.

You can't be wedded to one tool, workflow, or approach because go-to-market isn’t a one-time launch. It’s an always-on system. Invest in your ability to ask the right questions, move fast, and keep experimenting.

Watch Anand's full session below: