When we tell clients that we use AI in our development process, the first reaction is usually one of two things: excitement or concern. The excited ones want to know how much cheaper it makes things. The concerned ones want to know if quality is going to suffer.
The honest answer to both: it depends on how you use it.
What AI Is Actually Good At
We use AI tooling throughout our workflow, but we're deliberate about where it adds value and where it doesn't.
Scaffolding and boilerplate. Setting up a new Next.js project with TypeScript, Tailwind, ESLint, and proper folder structure is tedious and repetitive. AI handles it in seconds. We review the output, but we're not writing it by hand.
Component generation. "Give me a responsive pricing table with three tiers" is a solved problem. AI generates a solid starting point in about 30 seconds. We customize it from there. The total time is a fraction of what it would be starting from scratch.
Documentation and copy drafts. Placeholder content, README files, inline code comments — AI handles the first draft. Humans refine it.
Debugging. When something's broken, AI is surprisingly good at spotting patterns in error messages and suggesting fixes. It's not always right, but it narrows the search space quickly.
What AI Is Not Good At
This is the part people sometimes miss when they picture "AI-built websites."
Product decisions. AI doesn't know your business, your users, or what actually needs to be true about your product. Decisions about information architecture, user flows, and what features to build require human judgment.
Visual design. AI can generate components, but making a site look good — making it feel right for a particular brand and audience — requires taste that current models don't have in a reliable way. We design with human eyes.
Custom logic. Any non-trivial business logic — custom pricing calculators, complex form validation, third-party API integrations — needs careful engineering review. AI-generated code in these areas is a starting point, not a solution.
Quality assurance. We don't ship AI-generated code without review. Every component gets read, tested, and approved by a human engineer before it goes to production.
The Result in Practice
For a typical marketing site, AI tooling roughly doubles our throughput on implementation tasks. That means we can:
- Build more for the same budget
- Turn around projects faster
- Spend more time on the parts that actually differentiate the work: strategy, design, and custom engineering
We're not building AI-slop websites where the output goes straight from prompt to production. We're using AI the way a good carpenter uses a power saw: it does the repetitive cutting so you can focus on the joinery.
What This Means for Pricing
Our pricing reflects real market rates, not a discount for AI usage. The efficiency we gain from AI tooling goes into better quality, faster delivery, and more thorough work on each project — not just cheaper prices.
If you want a fast, high-quality website built by a team that takes the craft seriously, let's talk.