Great perspective. One point I'd add is that the real cost of an AI project isn't the initial development bill, it's the long-term cost of maintenance, scalability, and technical debt. That's why evaluating a partner's engineering practices, architecture, and product thinking is just as important as comparing quotes.

Companies like GeekyAnts are a good example of this approach. Their focus on AI-powered product engineering, scalable architecture, and long-term maintainability shows how investing in quality upfront can reduce costs over the lifecycle of a product. Choosing a partner that prioritizes business outcomes over simply delivering code often leads to a much stronger return on investment.