Why GTM is becoming more strategically important in the AI era
- There are often "10 players pursuing the same market opportunity."
- Technical differentiation is only at the margins, so go-to-market becomes the strategic wedge.
- Customers buy based on the experience of being sold to.
- When tech is similar, a unique, human, and personalized buying journey becomes the deciding factor.
- Companies know they need AI but do not know exactly what to change.
- GTM teams must act like consultants, not just order-takers.
The rise of the GTM Engineer
The Go-to-Market Engineer (GTME) is a technical role that brings engineering and AI agents into the sales process.
- Breaks down GTM workflows and encodes them into AI agents.
- Shadows high-performing humans (for example SDRs) to learn research and writing workflows, then builds agents to replicate that work.
- Example: Vercel moved from 10 SDRs handling inbound leads to one human managing an AI agent, while maintaining similar conversion rates.
- Often comes from sales engineering or technical backgrounds (for example front-end devs who moved into sales).
- Understands both code and sales.
A primer on segmentation
- Size (SMB, mid-market, enterprise) is just the starting point.
- Growth potential
- For consumption businesses (for example Stripe, Vercel), a small company growing 200% YoY can be more valuable than a large one growing 8%.
- Business model
- B2B vs B2C vs marketplace changes what products they need.
- For example, a marketplace needs very different payments infra than a SaaS platform.
- Technical signals
- Vercel uses Crux scores (Google traffic data) and workload types (E‑commerce vs Crypto, etc.).
- E‑commerce sites that rely on speed for revenue are a distinct segment from internal dashboards.
- Start with about three attributes so the team can actually operationalize.
- If you segment on too many dimensions, a small sales team cannot execute.
Building a sales org engineers and PMs respect
Friction with engineering usually comes from sales lacking depth or making asks without product understanding.
- “If I put you in front of 10 engineers, it should take them 10 minutes to figure out you are not a product manager.”
- A world-class GTM org is an extension of R&D.
- Sales talks to far more customers per week than PM or research, so they are a huge source of product insight.
- To earn respect, sales must filter feedback well.
- Distinguish between:
- Objections that should be handled in the sales motion, vs.
- Legitimate roadmap gaps.
The changing build vs buy calculus for GTM tools
In the AI era, the bias is shifting toward building internal tools instead of buying SaaS for every micro-problem.
- Vercel built a lead-handling agent in six weeks with one engineer at ~30% allocation.
- Running cost ≈ $1,000/year, versus > $1M/year in salary for the headcount it replaced.
- AI agents are best when they have access to your content, workflows, and data.
- Off-the-shelf tools rarely embed this deep context.
- Teams suffer from buying “20 different things” for narrow use cases.
- CIOs and engineering leaders increasingly become builders of internal software, not just buyers.
Why most customers buy to avoid pain, not chase upside
- Roughly 80% of customers buy to avoid pain or reduce risk.
- Only about 20% buy primarily to capture upside.
- Enterprise buyers treat software choices as career bets.
- A failed deployment risks reputation and missed revenue targets.
- The sale is often about de-risking the decision for them.
- Startups often over-index on visionary upside.
- To sell into enterprise, highlight how you help them avoid falling behind, missing targets, or hurting their brand, as much as how you help them win.