Lessons from the Field: What Early AI Customers Care About
AI Fanfare vs. What Customers Really Want
When I first started building enterprise AI products in 2023, I quickly learned that customers did not care about the latest tools or models. Instead, just like in my earlier work building SaaS products, they were focused on outcomes. What processes can this product automate? What problems that my business is facing can be solved by using this tool?
Now as I’m helping founders build AI products through Hyperfocus AI, I’ve discovered that the needs remain the same, and it’s up to us as tech leaders to cut through the endless stream of news and find what will actually be useful for customers. Here’s what I’ve seen matter most based on those crucial first customer conversations.
Lesson 1: Reliability Over the Latest Toolsets
Customers don’t care if you’re using GPT-4, llama.cpp, or anything else—they want something that works when they need it. When generative AI first became mainstream, I was excited by the idea of fine-tuning models for specific use cases. But I found that the development effort didn’t deliver enough value to justify the cost, so I shelved the work.
Instead, we focused on building a retrieval system that delivered consistent, accurate answers with far less complexity—and learned that reliability earns trust faster than novelty.
Lesson 2: Clear, Useful UI > Magical AI Moments
Customers remember if they can actually use your product, not if the AI surprises them once with a clever response. Recently, when I was working with an early stage startup, their users’ top feedback was simple: they wanted to easily upload and reference documents. Until we nailed ease of use, no other features mattered.
That experience reinforced that even at the earliest stage of a company and product, clarity is key—customers must immediately see how to get value from a product from the first time they use it. The advanced features can wait.
Lesson 3: Transparency Builds Trust
In highly regulated domains like healthcare and legal, customers want to see where answers come from—citations, sources, fallback logic. Recently, I spoke with a healthcare professional where this came up repeatedly, and showing grounded citations became a glaring necessity.
When building in sensitive spaces, make transparency non-negotiable. Don’t hide what’s under the hood; let customers see it.
What This Means for Founders
Customers care less about your tech stack, and more about whether your product fits into their world, solves their problems, and earns their trust. If you’re an early-stage founder wrestling with these questions, let’s connect. At Hyperfocus AI, we help teams turn AI ideas into products customers are excited to use.