AI Makes Building Websites Faster. Deciding What to Build Still Takes Work.

For years, a familiar arrangement shaped the relationship between businesses and agencies.

The client explained what they wanted and why. The agency figured out how to build it.

That division was never perfect. Good agencies have always asked questions, challenged assumptions, and helped shape the strategy. But much of the project’s time and cost still went into production: designing layouts, writing code, connecting systems, and turning an idea into a working website.

AI is changing that balance.

A business owner can describe an idea and get a working prototype. A marketer can generate landing pages. A developer can build features in a fraction of the time they once required.

The cost of getting something onto a screen is falling. The work of deciding whether it belongs there remains.

That shift has consequences for businesses buying websites and for agencies building them.

The bottleneck is moving

Tamas Mezei explores a related problem in “More Agents, Same Mythical Month” on Broken Robot. His argument concerns software teams and AI agents: increasing the capacity to produce code does not automatically increase the capacity to decide, coordinate, and verify.

For website projects, we see a similar implication.

When production takes weeks, there is time between decisions. People can review a layout while developers build another section. Content questions get resolved while integrations are underway.

When a first version appears in an afternoon, unresolved questions arrive much sooner.

Which audience matters most? Which service should lead? Who approves the messaging? What happens after someone submits the form? Does the new website preserve the search visibility the business already earned?

AI can accelerate the build while those questions remain unanswered.

The project may still take time. But a greater share of that time now sits in decisions, communication, and review.

“Tell us what you want” is becoming an incomplete service

At Inbound Studio, we’ve worked within that familiar model too: customers bring their goals and requests, and we help translate them into working technology.

But as AI becomes more capable of figuring out the how, agencies need to take greater responsibility for helping define the what and why.

That doesn’t mean taking business decisions away from the client. It means helping clients examine a request before investing in it.

Consider a business that asks for a customer portal.

AI can help generate the login screen, dashboard, and document library. Those are useful capabilities. But the request still needs investigation.

Are customers struggling to find documents? Are they calling for project updates? Do they need to approve estimates? Does the business already own software that could handle the problem?

Those answers might lead to a portal. They might lead to a better email workflow, an existing CRM feature, or a much smaller improvement.

The agency’s contribution starts with helping the business make that choice.

AI can help with strategy, too

It would be convenient for agencies to declare that AI handles execution while humans retain strategy.

That division is already too simple.

AI can help analyze customer feedback, compare approaches, identify gaps, and suggest priorities. It can turn a vague idea into questions worth discussing. Used thoughtfully, it can improve the planning conversation as well as the production work.

But those recommendations still need business context and evaluation.

A plausible suggestion may depend on customer behavior that hasn’t been verified. A technically sensible feature may create work that nobody on staff can maintain. A compelling page may promise something the business cannot consistently deliver.

Someone must connect the recommendation to reality, choose the tradeoffs, and take responsibility for the decision.

That is why an AI strategy roadmap should connect business goals, workflows, ownership, and measures of success before implementation expands.

Faster production can create more work to review

Imagine asking for three homepage concepts.

Previously, producing those concepts represented a meaningful investment. Today, AI might generate ten variations quickly.

That is valuable when the variations help answer a specific question. It becomes exhausting when nobody has agreed on the criteria for choosing.

One stakeholder prefers the photography. Another likes the headline. A third wants a different audience emphasized. The team asks for more options, and the review cycle grows.

The production cost fell. The decision became more complicated.

Google’s 2025 DORA research describes AI as amplifying existing organizational strengths and weaknesses. Its findings emphasize clear workflows, alignment, and strong feedback systems alongside the tools themselves.

The implication for agency work is practical: as we generate more quickly, we need a clearer way to evaluate what we generate.

Before producing another variation, agree on what the page needs to accomplish.

Communication needs to become more useful

This shift could easily become an excuse for more meetings.

It should push us toward better communication instead.

A useful project brief makes a few things explicit:

• The business problem: What is happening today that needs to improve?
• The audience: Whose needs should guide the decisions?
• The desired result: What should people understand or do differently?
• The constraints: Which systems, content, budget limits, and operating realities matter?
• The decision owner: Who can resolve conflicting feedback?
• The acceptance criteria: What must be true before this is ready to launch?

These answers don’t need to fill a giant requirements document. They need to be clear enough that the client, agency, and AI tools are working toward the same result.

A prototype can help discover those answers, too. Sometimes people understand what they need only after seeing an early version.

The goal is to use that version to learn, make a decision, and move forward.

Human review remains part of building

A convincing demonstration can make a project feel almost finished.

Then someone needs to check whether the forms reach the right person, the mobile navigation works, the content is accurate, and customers can complete the intended task.

For a website rebuild, someone also needs to check redirects, important existing pages, analytics, and integrations. For an online store, checkout and order handling need testing. For a customer portal, access permissions need careful verification.

AI can assist with much of this work. Automated tests can catch problems consistently and quickly.

But people still need to define the expected behavior, assess the evidence, and resolve exceptions.

Some review can happen immediately. Other learning requires watching real customers use the site or giving staff time to work with a new process.

Faster code generation changes the schedule. It doesn’t make every part of delivery instantaneous.

Agencies need to make the gains visible

Clients should benefit when agencies become faster.

If AI reduces production effort, agencies need to be candid about that change and show where their work creates value.

That might mean delivering a smaller project sooner, testing an idea before committing to a full build, or spending more attention on integration and validation.

It also means making strategic work concrete. A client should be able to see the priorities, decisions, working prototype, test results, and plan for measuring performance.

“Strategy” should produce something useful.

Our AI consulting and solutions work brings together problem definition, planning, implementation, and ongoing improvement because those activities depend on one another.

The quality of the decision shapes the value of the build.

Start with the result you want to change

If you’re planning a website, automation, or custom business tool, bring your ideas. Bring the prototype you made with AI. Bring the features you’re excited about.

Then connect them to a result.

“We need more qualified inquiries.”

“Our staff spends too much time answering status questions.”

“Customers struggle to find the right product.”

Those statements give a project direction. They make it possible to compare solutions, choose a sensible first step, and evaluate whether the work helped.

AI gives businesses extraordinary new capacity to build. Agencies have an opportunity to help that capacity produce something worth owning.

At Inbound Studio, that means helping clients decide what deserves to be built, using the best tools to build it efficiently, and reviewing the result against the business need that started the project.

Have an idea or an AI-built prototype you want to move forward? Let’s talk about what it needs to accomplish.