With AI commoditizing the ability to build, the key differentiator is "taste"—the ability to discern what problems are worth solving and what ideas are wasteful. Building faster with AI is useless if you're building the wrong things. True success comes from what you decide *not* to do.

AI has dramatically reduced development cost, turning many engineering decisions into "two-way doors." Unlike irreversible strategic choices, code can be built and changed quickly. PMs should thus focus deep thinking on truly irreversible "one-way door" decisions, rather than on engineering time estimates for reversible work.

With AI, the initial effort to explore an idea—like writing the first draft of a spec or building a janky prototype—is now effectively free. This drastically lowers the cost of exploration, but the last 10% of refinement and quality assurance remains the hardest and most critical part.

AI tools are dramatically lowering the cost of implementation and "rote building." The value shifts, making the most expensive and critical part of product creation the design phase: deeply understanding the user pain point, exercising good judgment, and having product taste.

AI tools dramatically speed up code implementation, making engineering velocity less of a constraint. The new challenge becomes the slower, more considered process of deciding *what* to build, placing a premium on strategic design thinking and choosing when to be deliberate.

The current excitement around AI is fueling a “build it yourself” trend, echoing past tech cycles. This approach often overlooks the significant long-term costs of maintenance, versioning, security, and 24/7 support, which previously led companies to abandon homegrown systems for specialized vendors.

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.

Since AI agents dramatically lower the cost of building solutions, the premium on getting it perfect the first time diminishes. The new competitive advantage lies in quickly launching and iterating on multiple solutions based on real-world outcomes, rather than engaging in exhaustive upfront planning.

The idea that building with AI is cheap is a dangerous oversimplification. While initial creation is fast, leaders are realizing the immense long-term costs of maintenance, unwinding mistakes, and integrating with legacy systems are substantial and often dangerously overlooked.