While it's tempting to build custom AI sales agents, the rapid pace of innovation means any internal solution will likely become obsolete in months. Unless you are a company like Vercel with dedicated engineers passionate about the problem, it's far better to buy an off-the-shelf tool.
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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.
Customers are hesitant to trust a black-box AI with critical operations. The winning business model is to sell a complete outcome or service, using AI internally for a massive efficiency advantage while keeping humans in the loop for quality and trust.
In the fast-evolving AI space, Vercel's AISDK deliberately remained low-level. CTO Malte Ubl explains that because "we know absolutely nothing" about future AI app patterns, providing a flexible, minimal toolkit was superior to competitors' rigid, high-level frameworks that made incorrect assumptions about user needs.
AI agent tools require significant training and iteration. Success depends less on software features and more on the vendor's commitment to implementation. Prioritize vendors offering a dedicated "forward-deployed engineer" who will actively help you train and deploy the agent.
Individual sellers can use free tools like Google's NotebookLM to build their own specialized AI agents now. By uploading books, articles, and podcasts on topics like prospecting or upselling, they create a personal knowledge base to get instant, tailored answers and stay ahead of the curve.
Dylan Field is skeptical that disposable, AI-generated apps will replace complex SaaS products. Real business software must handle countless edge cases, scale with teams, and support shared workflows—a level of complexity and institutional knowledge that today's agents are far from mastering.
Visual AI tools like Agent Builder empower non-technical teams (e.g., support, sales) to build, modify, and instantly publish agent workflows. This removes the dependency on engineering for deployment, allowing business teams to iterate on AI logic and customer-facing interactions much faster.
Unlike startups facing existential pressure, enterprise buyers can benefit from being late adopters of AI. The technology is improving at an exponential rate, meaning a tool deployed in a year will be significantly more capable than today's version, justifying a 'wait and see' approach.
Large companies integrate AI through three primary methods: buying third-party vendor solutions (e.g., Harvey for legal), building custom internal tools to improve efficiency, or embedding AI directly into their customer-facing products. Understanding these pathways is critical for any B2B AI startup's go-to-market strategy.
