AI-Driven Product Development
Shipping AI features into real products — not demos that never leave the branch.
AI-driven product development means shipping AI features into a product your customers already use, rather than building a separate demo. In practice that is integration work: embedding GPT-4, Claude, or custom LLMs into an existing Laravel or Node stack, with the validation, fallbacks, and cost controls a production feature needs. I have shipped AI features for 20+ clients across 100+ projects in 7+ years.
When this helps
- An AI feature was prototyped months ago and still has not shipped.
- The team can build the feature but is unsure how to make it reliable.
- AI output is inconsistent, and there is no fallback when it is wrong.
- Nobody is sure what the feature will cost per user at scale.
What the work includes
Feature scoping
Deciding which parts of the product genuinely benefit from a model, and which are better served by ordinary code. Not every feature should be AI.
Stack integration
Building into your existing Laravel or Node application rather than bolting on a separate service that has to be maintained twice.
Structured output
Using JSON schema and function calling so the application can validate, retry, and degrade gracefully instead of trusting free text.
Fallback behaviour
Defining what the product does when the model is slow, wrong, or unavailable — decided deliberately rather than discovered in production.
Cost modelling
Knowing the per-user cost of the feature before launch, not after the first invoice.
Measurable impact
Agreeing the business metric the feature is meant to move, and reporting against it.
Related work
Questions
Which stacks do you work in?
Primarily Laravel and Node, with React, Next.js, React Native, and Flutter on the front end. The AI work integrates into the stack you already run rather than requiring a rewrite.
GPT-4, Claude, or a custom model?
It depends on the task, the latency you can tolerate, and the cost per call. Most products end up using different models for different jobs rather than one model everywhere.
How long before an AI feature is in production?
It varies with scope, but the common blocker is not build time — it is the absence of evals and fallbacks, which is what keeps prototypes stuck short of launch.
Do you work with pre-launch startups?
Yes. I work with funded founders across the UK, EU, US, and MENA, at both pre-launch and scaling stages.
Want to talk it through?
Tell me what you are building and where it is stuck. I work remotely with founders across the UK, EU, US, and MENA, in hours that fit your timezone.
Get in touch →