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.
Don't just replace human tasks with AI. Deploy AI agents to handle leads your sales team ignores, like small deals or low-scored prospects. This untapped segment, as SaaStr found with a 15% ticket revenue lift, represents significant growth potential by filling a gap in your GTM process that humans create themselves.
Vercel's CTO Malte Ubl suggests a simple method for finding valuable internal automation tasks: ask people, "What do you hate most about your job?" This uncovers tedious work that requires some human judgment, making it a perfect sweet spot for the capabilities of current-generation AI agents.
Top-performing engineering teams are evolving from hands-on coding to a managerial role. Their primary job is to define tasks, kick off multiple AI agents in parallel, review plans, and approve the final output, rather than implementing the details themselves.
Stop thinking of sales, marketing, and support as separate functions with separate tools. AI agents are blurring these lines. A support interaction becomes a lead gen opportunity, and a marketing email can be sent by a 'sales' tool. Prepare for a unified go-to-market operational model.
Instead of focusing on foundational models, software engineers should target the creation of AI "agents." These are automated workflows designed to handle specific, repetitive business chores within departments like customer support, sales, or HR. This is where companies see immediate value and are willing to invest.
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.
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.
By building a custom AI agent for inbound lead qualification, Vercel reduced its inbound SDR team from ten people to one. The agent, which cost only $1,000 per year to run, maintained conversion rates while decreasing response time and number of touches needed.
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.