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The Great GTM Correction
When we started the AI GTM WTF podcast, I had one question.
How is AI actually changing the way we build revenue engines — not in theory, but in practice?
Seven episodes later, that question has flipped.
AI didn’t reinvent GTM.
It revealed how broken GTM already was.
Every guest — founders, operators, and revenue leaders — echoed the same frustration:
we’re drowning in tools, dashboards, and noise, but starving for design.
From Brendan Short from the Signal to Matt Green at Sales Assembly, from Anirudh Madhavan at Outcome Driven to Amos Joseph at Swan, the through line was impossible to miss.
“We’re not scaling effort anymore. We’re scaling design.” — Matt Green
This edition isn’t a recap.
It’s a diagnosis.
The seven patterns that define the new GTM operating system — and what they reveal about where the next decade of sales, data, and AI is heading.
The Shift We’re Seeing:
Across seven conversations, one pattern became impossible to ignore.
The motion that built modern SaaS — more reps, more sequences, more meetings — has hit its ceiling.
AI didn’t kill it. It exposed it.
The new motion isn’t about volume.
It’s about voltage — fewer inputs, higher output, cleaner systems.
Brendan, Anirudh, Nilan, David, Jim, Almost, and Matt all said it in different ways:
we’re leaving the busy GTM era and entering the designed GTM era.
“The future GTM team won’t be bigger,” one of them told me.
“It’ll just be smarter by design.”
This is the undercurrent running through every pattern that follows.
AI isn’t replacing sales.
It’s rewiring how sales is built.
Pattern 1 · Data Before Dreams
Anirudh Madhavan opened his episode with a warning:
“AI fails before it begins because it sits on a broken data layer.”
Most teams feed AI garbage and expect brilliance.
Your CRM isn’t the problem. Your data design is.
Fix your inputs before you build your stack.
Tools he lives by: HubSpot, Salesforce, Make, Perplexity, Instantly, Smartlead.“AI helps with speed,” he said, “not direction.”
Pattern 2 · Pipeline as Product
Nilan Chaudhuri treats pipeline like code.
“If your ACV is 10K, you need 100 opportunities for $1M pipeline.
The math is simple. Keeping it clean isn’t.”
His process: define ICP → build infrastructure → test messaging → measure inputs.
He calls it “pipeline physics.”
Tools: Instantly, OneStartOne, Clay, LeadIQ, Reggie, Lavender, ChatGPT
Pattern 3 · Signals over Volume
Brendan Short saw the end of brute-force outbound coming.
The playbook is now signal-driven — tracking funding rounds, job changes, and product updates to contact the right person at the right moment.
Tools: Clay, Symbl, Momentum, CommonRoom, Unify.
Outbound isn’t about sending more.
It’s about sending smarter.“We don’t test for opens,” he said.
“We test for reactions.”
Pattern 4 · Measure Impact, Not Motion
David Wilkins Ex-Cognism dismantled the religion of activity metrics.
“No one cares how many meetings your team books.
They care what percentage turn into revenue.”
He replaced call counts with pipeline contribution and efficiency per rep.
Managers stopped coaching effort and started coaching outcomes.
Tools: Clay, Kernel, UserGems, FullEnrich, Hyperbound, ChatGPT, Cognism.
Those dashboards become feedback loops—small weekly adjustments that compound into predictable growth..
Pattern 5 · Delegate Intelligently
At PandaDoc, Jim Petrolla did a time audit and realized half his week was admin.
“Delegate to AI anything that doesn’t need empathy.”
He automated pre-call prep, post-call summaries, and inbox management.
AI didn’t replace him — it returned his time to selling.
Tools: ChatGPT, Fyxer, Gamma.
Pattern 6 · Scale by Subtraction
Amos Joseph is building Swan with three people serving 200 customers.
“Headcount is not scale. Output is.”
His north star: autonomous businesses, not automated ones.
He measures efficiency as ARR per employee and obsesses over design before hiring.
AI removes friction. Design multiplies impact.
Pattern 7 · The Human Moat
Matt Green sees the other side of the curve.
“AI will never replace curiosity or trust.”
His front-row view of hundreds of B2B orgs revealed the same truth:
Technology can replace tasks, but not connection.
The best reps of the AI era are builders and listeners.
The Common Thread
Design before deployment.
Measure inputs you control.
Clean data beats clever prompts.
AI amplifies clarity, not chaos.
Scale less, learn faster.
AI GTM WTF POV
After seven episodes, one lesson is obvious.
The winners aren’t the loudest — they’re the cleanest.
GTM is no longer a hustle.
It’s a design discipline.
The best operators now think like product managers —
mapping inputs, designing loops, and aligning humans and AI around a single principle:
clarity compounds.
If you’re still chasing pipeline instead of designing it,
you’re not building a business.
You’re building a gamble.
Watch the full conversation with these operators—
🎧 Listen on Spotify
📺 Watch on YouTube
💌 Subscribe to newsletter.nevara.ai
No AI SDR fairytales.
Just the future of GTM.
— Rahul 👋
AI GTM WTF isn’t here to celebrate the hype cycle. We’re here to arm you with what actually moves revenue.
If this hit, forward it to one operator who’s drowning in “AI strategy” decks and needs the signal, not the noise.
No AI SDR fairytales. Just the future of GTM.
Sincerely,
Rahul 👋