Get your free personalized podcast brief
We scan new podcasts and send you the top 5 insights daily.
AI is dramatically accelerating engineering output, shifting the primary organizational bottleneck from development to high-quality decision-making. As a result, the traditional 1 PM to 7+ engineers ratio is reversing, with some teams moving to ratios of 1 PM to 2-3 engineers to focus on providing the necessary context and strategic direction.
Related Insights
AI will handle more coding, design, and analytics, empowering a single product manager to direct the work previously done by a large engineering team. This blurs traditional roles and fundamentally changes team composition, making PMs more autonomous and outcome-focused.
AI tools are rapidly increasing developer output. If product managers don't adopt similar AI-native tools to accelerate their own workflows—like product judgment, research, and planning—they will become the primary constraint on the entire development lifecycle.
As AI coding agents make engineers more productive, the development bottleneck eases. The new constraint becomes product management—understanding user needs and business impact. This shift will necessitate a higher ratio of product managers to engineers to effectively guide the accelerated development cycle.
With AI compressing development cycles, competitive advantage no longer lies in engineering output. Instead, it shifts to the speed and quality of strategic decision-making. The CPO's primary job evolves from managing feature backlogs to making calculated, high-velocity bets on what to build next.
As AI tools dramatically increase engineering leverage (2-3x), the traditional 5-engineer, 1-PM, 1-designer team structure breaks. The PM and designer become bottlenecks, struggling to manage what is effectively a 15-20 person engineering team's output, forcing a rethink of team ratios and roles.
As AI tools accelerate engineering output, the limiting factor in product development is no longer coding speed but the quality of product discovery and strategy. This increases the demand for effective product managers who can feed the more efficient engineering pipeline.
When AI drastically increases engineering efficiency, the critical challenge is no longer shipping speed. The focus must shift to high-quality strategic planning and outcome-driven decision-making to ensure the abundant engineering resources are building the right products.
By empowering individuals with AI tools, Freshworks has seen a dramatic shift in team composition. The ratio of product managers to engineers has collapsed from a traditional 1:20 to nearly 1:1, enabling smaller, faster, and more autonomous teams.
Contrary to fears of fewer PMs, AI-driven development efficiency will increase the need for strategic guidance. This shifts the bottleneck to product strategy, requiring tighter PM alignment and potentially leading to smaller, more senior teams with ratios as low as one PM for every two developers.
As AI makes building cheaper, the bottleneck shifts from engineering execution to product discovery and judgment. This could invert the traditional 1:5 PM-to-engineer ratio, creating a future where more product managers are needed per engineer to focus on co-creation, ideation, and defining what to build.
