Large enterprises navigate a critical paradox with new technology like AI. Moving too slowly cedes the market and leads to irrelevance. However, moving too quickly without clear direction or a focus on feasibility results in wasting millions of dollars on failed initiatives.

When asked to modify or rewrite functionality, LLMs often attempt to preserve compatibility with previous versions, even on greenfield projects. This defensive behavior can lead to overly complex code and technical debt. Developers must explicitly state that backward compatibility is not a requirement.

Instead of a full rewrite, identify the specific pain points of a legacy system (e.g., a command-line UX) and solve them with minimal development. This delivers immediate value, reduces risk, and validates the market need for a larger investment later, preventing a costly failure.

In fast-moving industries like AI, achieving product-market fit is not a final destination. It's a temporary state that only applies to the current 'chapter' of the market. Founders must accept that their platform will need to evolve significantly and be rebuilt for the next chapter to maintain relevance and leadership.

While no-code can help validate an idea, it inevitably leads to a growth-killing stall. Founders will hit a platform limitation that forces them to stand still for 3-6 months to rewrite the entire codebase from scratch. This sacrifices critical early-stage feature velocity and market responsiveness.

Engineers may advocate for modernizing a functional legacy system not for business needs, but to add popular new frameworks to their resumes. This 'RDD' leads to wasted budget on projects that don't deliver real customer value, a phenomenon labeled Resume-Driven Development.

In the age of AI, perfection is the enemy of progress. Because foundation models improve so rapidly, it is a strategic mistake to spend months optimizing a feature from 80% to 95% effectiveness. The next model release will likely provide a greater leap in performance, making that optimization effort obsolete.

Saying yes to numerous individual client features creates a 'complexity tax'. This hidden cost manifests as a bloated codebase, increased bugs, and high maintenance overhead, consuming engineering capacity and crippling the ability to innovate on the core product.

Finance departments often push for system rewrites based on fixed 3-5 year depreciation schedules. Once software is fully amortized and has a book value of zero, accounting principles create pressure to invest in a new system to put a new asset on the books, regardless of the old system's functionality.