For years, B2B revenue teams survived on a simple formula.

More reps, more sequences, more “pipeline.”

The classic playbook.

The safe playbook.

The playbook everyone swears they hate but still quietly clings to like a security blanket.

Then Michael Heiberg walked in and asked a very inconvenient question:

“I just closed this customer. Why can’t I clone that to the next 10 or 20?”

That single thought launched Ocean.io, reshaped how lookalikes work in B2B, and is now feeding the rise of AI SDRs, automated demos, and a future where sales and marketing roles start melting into one operational super-function.

Welcome to the calm, casual apocalypse of go to market.

Michael is incredibly matter of fact about it:

An AI pilot that can run 20 demos a day, learn from every single one, and improve as it goes is simply more attractive than a human rep doing the same repetitive loop.

No theatrics.

No “this will empower teams” corporate fluff.

Just: AI learns faster, scales instantly, and handles pattern-based tasks better.

And he’s right.

If the job is repetitive, AI is going to eat it.

Michael didn’t just stumble into this. His background is SAP, Oracle, supply chain, and later investing. The common thread was obvious:

He always wanted a way to “clone” his best customers.

In B2C, lookalike audiences were old news.

In B2B, everything was still stuck in the stone age.

Industry codes. Keyword hacks. Title searches that break if someone writes “Head of Stuff” instead of VP.

So his team built something different:

vectorizing landing pages, normalizing job titles, and representing companies mathematically.

It was bleeding edge.

Even ElasticSearch didn’t support the vectoring he needed at first.

They released their first version in 2020.

It was rocket science duct taped to a search engine.

But once the market caught up, it clicked instantly.

Michael’s frustration is simple: bad data creates busywork.

And busywork creates bloated SDR teams.

In his world, contact data is commodity.

The real power is intelligent datasets in context.

If you can precisely identify who matters, everything downstream becomes cleaner: outreach, personalization, inbound routing, scoring, targeting.

AI SDRs aren’t coming. They’re already working.

Michael sees the change clearly:

AI SDRs will take the top of the funnel.

Automated agents will run the demos.

More agents will negotiate, draft contracts, and map decision makers.

AEs will be involved only when nuance is required.

The rest becomes orchestration.

He predicts 80 percent of the repetitive work goes away, and the remaining human roles look nothing like today’s job descriptions.

That’s not doom and gloom.

It’s just acknowledging reality:

Automation excels at scale and consistency, and B2B finally has the data infrastructure to support it.

This is where Michael drops the bomb:

He thinks the old divide between sales and marketing dissolves.

Not metaphorically. Literally.

He sees the COO or CRO becoming the center of the GTM universe, overseeing a unified flow instead of two siloed teams arguing over attribution.

MQLs? He thinks they’re disappearing.

CMOs? He thinks many are in trouble.

GTM becomes one continuous automated system with humans stepping in only where nuance or judgment is required.

Whether you agree or not, it’s consistent with what’s happening across up-and-coming AI driven orgs.

Michael does not sugarcoat his feelings about legacy CRMs.

To him, they are glorified spreadsheets.

The intelligence will live on top of them, not inside them.

Ocean feeds normalized lookalike datasets, clusters, and ICP scoring directly into systems like Salesforce.

Not simple enrichment.

Not bulk upload chaos.

Actual clustering of closed deals, dynamic ICP recalculation, and automated lead scoring based on real similarity, not checkbox point systems.

Again, this matches the internal Ocean use case: dynamic ICP clustering and AI scoring.

Michael believes the next frontier is micro campaigning.

Not blasting 100,000 people.

Not “personalized” mail merges.

Instead:

Thousands of tiny, highly relevant campaigns generated automatically.

This requires high quality normalized data, not pretty interfaces or clever subject lines.

It’s also the reason AI SDR companies are scrambling to fix their underlying data science.

One thing he’s crystal clear about:

Ocean is not just a search tool.

Their PLG experience is simply how people discover the accuracy.

The real engine is the API powering Clay, Jibly, JV AI, Explorium, and a wave of next-gen GTM tools.

This is exactly aligned with your internal doc:

The API is the core revenue driver, embedded into 50+ applications.

So what does this all add up to?

Here’s how he sees the next 18 to 24 months unfolding, in his own words:

• SDR teams shrink dramatically
• GTM engineers rise
• Revenue organizations become fully orchestrated
• AI handles wide parts of the funnel
• CRO becomes the center of GTM
• CMOs face pressure as MQLs lose relevance
• CRM intelligence moves to external layers
• Micro campaigning replaces mass campaigning
• Recruitment gets rebuilt through vectorized matching
• Prompt based targeting (MCP) becomes standard
• AI demo pilots outperform human reps within months

That’s the roadmap he’s running toward.

Michael says his personal “flow state” comes from embracing constant change.

Pivoting often. Learning quickly. Staying on his toes.

It’s the same mindset he believes GTM teams need if they want to survive the next wave of automation.

Because in his view, the future is simple:

If repetitive work is part of your revenue motion, AI will take it.

If precision matters, intelligent data will decide who wins.

And if you’re still arguing about MQLs, you’re already behind.