To build effective GTM automation, hire people who understand both the technology and the sales process. Vercel found success by transitioning its technical sales engineers—who were already former developers—into GTM Engineer roles. This ensures automated workflows are grounded in proven, real-world sales best practices.
Instead of hiring a 'Chief AI Officer' or an agency, the most successful GTM AI deployments empower existing top performers. Pair your best SDR, marketer, or RevOps person with AI tools, and let them learn and innovate together. This internal expertise is more valuable than any external consultant.
Don't expect an AI agent to invent a successful sales process. First, have your human team identify and document what works—effective emails, scripts, and objection handling. Then, train the AI on this proven playbook to execute it flawlessly and at scale. The AI is a scaling tool, not a strategist from day one.
Vercel COO Jean Grosser's litmus test for a great salesperson is that engineers shouldn't be able to tell they aren't a PM for at least 10 minutes. This requires deep product knowledge, enabling sales to act as an R&D function by translating customer feedback into valuable product signals.
While consolidating tools seems efficient, using specialized, best-in-class AI agents for each GTM function (one for outbound, one for inbound) yields superior results. The depth and focus of specialized tools enable more powerful and nuanced use cases, justifying the management overhead of multiple systems.
With AI agents automating raw code generation, an engineer's role is evolving beyond pure implementation. To stay valuable, engineers must now cultivate a deep understanding of business context and product taste to know *what* to build and *why*, not just *how*.
Unlike older sales tools, AI agents shouldn't be handed to individual SDRs to manage. This approach leads to failure. Instead, centralize the strategy: a core team must own agent training, contact routing, and performance tuning to ensure a consistent and effective GTM motion across the entire organization.
In the AI era, marketing and growth roles are splitting into two distinct archetypes: the 'tastemaker' who has exceptional creative taste and intuition, and the 'engineer' who can technically analyze and orchestrate complex systems. Being average at both is no longer a viable path to success.
You can't delegate AI tool implementation to your sales team or a generalist RevOps person. Success requires a dedicated, technical owner in-house—a 'GTM engineer' or 'AI nerd.' This person must be capable of building complex campaigns and working closely with the vendor's team to train and deploy the agent effectively.
This emerging role applies engineering and AI to GTM functions, building agents to automate tasks like lead qualification and personalized outreach. This dramatically increases efficiency, allowing one person, with an AI agent, to do the work of ten.
Contrary to the belief that PMs are the earliest tech adopters, go-to-market functions (sales, marketing, support) are leading agent adoption. Their work involves frequently recurring, pattern-based tasks that are a perfect fit for automation, putting them ahead of the curve.