LLM Lessons learned the hard way. TL;DR Building AI-first experiences is actually really freaking difficult

Title: The Realities of Developing AI-Centric Applications: Lessons from the Field

In the rapidly evolving landscape of artificial intelligence, creating AI-powered experiences is far more challenging than it might appear on the surface. Recently, I came across an insightful article that explores the hurdles involved in building an AI-driven personal fitness coach, offering a candid look at what it takes to develop with these systems today.

One key takeaway is that integrating AI as the core component of an application demands extensive custom tooling. Without this, your AI agent may end up being either overly simplistic or prohibitively expensive to operate— unless you’re willing to perform some serious cost-management gymnastics. For developers aiming to stay ahead, investing in the right infrastructure now can provide a significant advantage over the coming decade, well before AI solutions become commoditized.

Despite the buzz around ‘vibe coding’ AI experiences effortlessly, the reality is quite different. Building a basic demo with AI is straightforward, but transforming that demo into a reliable, high-quality product remains a major challenge. The main reason? The intuition and problem-solving skills that you’ve honed over years of software development don’t necessarily translate well in an AI context.

If you’re considering diving into AI-centric development, be prepared for a steep learning curve. Gaining a solid understanding of the essential tooling and infrastructure is essential—not just for initial success, but for enduring growth in this fast-changing field.

For a deeper dive into these challenges and insights from seasoned developers, check out the full article here: http://brd.bz/84ffc991.