Integrating AI into your product without overcomplicating it
Most products don’t need an AI strategy. They need one or two places where a model genuinely removes work for the user. Finding those places, and building them carefully, beats bolting a chatbot onto everything.
Start with a boring, expensive task
The best AI features we’ve shipped didn’t start with “let’s add AI”. They started with a task people already hated: reading long documents, categorising support tickets, writing the same product description for the hundredth time. If a task is repetitive, text-heavy and tolerant of an occasional correction, it’s a good candidate.
If you can’t describe the task in one sentence, the feature isn’t ready to build.
Keep a human in the loop
Models are confident even when they’re wrong. Design for that. Show suggestions rather than silent actions, make the source visible, and make it effortless to accept, edit or reject. A feature that saves 80% of the effort and asks for a quick review is far more trustworthy than one that tries to save 100%.
The goal isn’t to look intelligent. It’s to make the next step faster.
Treat it like any other dependency
- Log inputs and outputs so you can see what actually happens in production
- Set budgets and timeouts. A slow answer is often worse than no answer
- Keep prompts and model choices in configuration, not scattered through the code
- Have a fallback for when the provider is down
Done this way, AI stops being a gimmick and becomes what it should be: a quiet feature that makes the product feel faster and smarter.