Even though AI enables PMs to code, it's an inefficient use of their time. Since code creation is cheap and product strategy is the new bottleneck, PMs should focus entirely on product work, not engineering tasks.

The opportunity cost of building custom internal AI can be massive. By the time a multi-million dollar project is complete, off-the-shelf tools like ChatGPT are often far more capable, dynamic, and cost-effective, rendering the custom solution outdated on arrival.

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

Founders can get lost building complex AI systems and automations. This can become a trap, a "procrastination machine," that feels productive but doesn't contribute to the primary goal of generating revenue. Always ask if the AI work is actually making the business money.

The primary value of AI app builders isn't just for MVPs, but for creating disposable, single-purpose internal tools. For example, automatically generating personalized client summary decks from intake forms, replacing the need for a full-time employee.

AI coding assistants reduce development time from days to just minutes or hours. This makes building custom tools to save a few minutes daily a highly valuable investment, as the payback period for the time spent building is now incredibly short.

With AI, building custom internal tools for shallow, high-customization needs (like HR or payroll) is now cheaper and faster than buying and integrating third-party SaaS. This challenges the traditional 'buy vs. build' calculus for standard business functions.

Building proprietary internal tools is a 'dumb thing to do when you're small, but it's the smartest thing to do as you scale.' Deel's CEO advises waiting until the company is on a clear path with strong, profitable growth. At that point, investing in custom infrastructure like a proprietary ticketing system becomes a strategic advantage that unlocks significant long-term efficiency.

Off-the-shelf SaaS products often fail to accommodate a company's specific workflows. Building custom internal tools with AI allows teams to create solutions precisely matched to their culture and cadence (like design reviews), leading to higher adoption and impact.