Why Nobody Wants Your Product, The Marketer of The Future, and The Post-AI Org Chart

Works in progress.

Good morning

In today's edition, among other things:

• Why Nobody Wants Your Product?

• The CTO’s Role in Early GTM Success

• The Post-AI Org Chart

• The Marketer of The Future

• How People Use AI?

• You're Not Busy, You're Emotionally Overwhelmed

• How Shopping Will Work In The Age of AI

Onwards!

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Why Nobody Wants Your Product?

Customers don’t wake up thinking about your product. They wake up thinking about their own survival—revenue, costs, compliance, staff headaches. Your job isn’t to sell software; it’s to solve a problem urgent enough that someone diverts scarce time, money, and attention away from everything else.

This is why so many startups fail despite looking “logical” on paper. A better UI or a lower cost is not demand. The only thing that matters is whether you’re addressing a discrete, top-of-mind “job to be done” that your buyer already feels.

Three typical conditions to look for:

1. Urgency: The “hair-on-fire” problem. Without urgency, your ROI case doesn’t matter. One company built great retention software for retailers; customers agreed it added value, but it wasn’t even a top-five problem. Adoption stalled.

2. Repeatability: Can you find multiple customers in the same vertical with the same urgent need? Founder-led selling validates whether demand survives beyond friendly intros. Customer interviews don’t count until someone pays.

3. Scalability: Can you grow from some satisfied customers into many, with renewals and referrals lowering acquisition costs? Without this pull, growth is too expensive to sustain.

Urgency gets you in the door, repeatability keeps you busy, scalability makes you durable.

Founders often believe they’re in the business of building products. They’re not. They’re in the business of reducing pain. If the pain isn’t felt deeply and broadly, the product doesn’t matter.

Nobody wants your product. They want their problem to go away. The faster you accept that, the quicker you find fit.

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The CTO’s Role in Early GTM Success

Startups usually imagine GTM as a sales problem. In reality, the first unfair advantage often hides inside the codebase. The CTO’s early involvement in go-to-market isn’t a distraction from building — it’s how you build a repeatable growth engine from day one.

Unfortunately, most of the time it’s an underdelivered effort.

Technical founders bring rigor to what is often treated as “art.” Bowery Capital notes that CTOs can enrich datasets in Google Sheets with AI, identify the right ICPs, and filter by industry, size, and behaviors. Instead of guessing who to sell to, you’re running structured experiments.

• Clean ICPs mean fewer wasted conversations.

• Repeatable enrichment workflows mean pipeline is a system, not a one-off.

• Every test creates data that improves the next iteration.

If you’re doing it.

If yes, then technical speed turns into GTM agility: faster hypotheses, cleaner prospects, tighter loops. If you’re constantly waiting on deliverables, you move too slow.

It’s a myth that GTM is just “sales and marketing.” The best early motions blend product and market in real time.

• Engineers can automate enrichment, CRM updates, and outreach sequencing — saving reps from drowning in data entry.

• They design tests the way they debug code: controlled, measurable, repeatable.

• Most importantly, they translate features into value propositions prospects actually care about.

When they’re involved in GTM discussions, they can refine messaging and provide feedback to improve product-market fit.

That bridge between product and market often decides whether the first customers stick.

An often essential RevOps hire might take weeks to figure out how to link data sources and debug enrichment logic. A CTO can build the workflow in hours.

This turns them into the first true growth hacker: not the one sending cold emails, but the one architecting the system so the team can run faster with less friction.

In early GTM, leverage comes from systems, not scripts.

There are of course risks:

• Distraction risk: Pulling the CTO too deep into GTM can slow product velocity. The balance is making them the architect, not the SDR.

• Scaling risk: What works with a technical founder running Sheets may break once volume scales. You’ll need to hire for repeatability.

• Cultural risk: If engineers see GTM as “not their job,” the collaboration never sticks. Founders must set the tone.

The unknown: how far AI-native GTM systems can scale before hitting the limits of context, cost, and reliability.

Early on, the best advantage is your CTO turning technical intuition into a data-driven, repeatable revenue system. Why else ship anything?

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The Post-AI Org Chart

The org chart is the most invisible piece of software in a company. It encodes how decisions flow, what’s getting built, who gets promoted, and where bottlenecks form. But AI is rewriting that codebase. The AI-native organization won’t look like a pyramid — it will look more like a cylinder, where humans and agents share management layers in new ratios.