While AI threatens to reduce software seats in support and sales, it's having the opposite effect on engineering and product. AI tools are increasing developer output, leading to the creation of more software and stabilizing team sizes, making them a resilient customer segment for SaaS.
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AI tools are blurring the lines between roles like product management, UX design, and development. A single skilled individual can now leverage AI to handle tasks that previously required a three-person team, dramatically increasing individual productivity and changing organizational structures.
The most significant and immediate productivity leap from AI is happening in software development, with some teams reporting 10-20x faster progress. This isn't just an efficiency boost; it's forcing a fundamental re-evaluation of the structure and roles within product, engineering, and design organizations.
AI tools are blurring the lines between roles. Vercel SVP Aparna Sinha notes that product managers can now build and test working products, not just prototypes. This allows for hyper-efficient, small teams—sometimes just one person—to achieve the output of a full squad.
Instead of traditional IT departments, companies are forming small, cross-functional teams with a senior engineer, a subject matter expert, and a marketer. Empowered by AI, these agile groups can build new products in a week that previously took teams of 20 people six months, radically changing organizational structure.
Despite revenue growth, Salesforce is not expanding its engineering team. Marc Benioff states that tools like Claude Code and Cursor have made his existing 15,000 engineers so much more productive that he can keep headcount flat. In contrast, he is hiring 20% more account executives to manage customer relationships.
AI lowers the economic bar for building software, increasing the total market for development. Companies will need more high-leverage engineers to compete, creating a schism between those who adopt AI tools and those who fall behind and become obsolete.
AI tools reduce the communication overhead and lengthy handoffs that traditionally separated product and engineering. By streamlining the path from idea to code, AI makes the combined Chief Product and Technology Officer (CPTO) role more viable, enabling a single leader to manage both functions effectively.
AI coding tools are a massive force multiplier for senior engineers, acting like a team of capable-but-naive graduates. The engineer's role shifts to high-level architecture and course-correction, enabling them to build, ship, and maintain entire products without hiring a team.
The idea that AI will enable billion-dollar companies with tiny teams is a myth. Increased productivity from AI raises the competitive bar and opens up more opportunities, compelling ambitious companies to hire more people to build more product and win.
Mike Cannon-Brookes argues that AI makes developers more efficient, but since the demand for new technology is effectively unlimited, companies will simply build more. This will lead to a net increase in hiring for engineering talent, not a reduction.
