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AI Agent Development

Agents that do the work,
not just talk about it.

An AI agent is a model given tools and the autonomy to use them: it takes actions, completes multi-step tasks, and works inside your real systems. That is far harder than a chatbot and far more valuable. We build production agents on Claude, grounded and guard-railed, owned by you.

01
Tool use
The agent calls real functions and APIs to act.
02
Grounded in data
It acts on your facts, via retrieval, not guesses.
03
Multi-step tasks
It plans and completes work, not one-shot replies.
04
Guardrails
Constrained so autonomy does not become risk.
05
Built on Claude
Anthropic models, production stack, owned by you.

What an agent is

More than a model.
A model with hands.

An agent is a language model plus three things: tools it can call to act in the real world, grounding in your data so it acts on facts, and guardrails so it acts safely. The model is the brain; the engineering around it is what makes it an agent rather than a chat window.

01The difference
02The build
03When it's worth it

The difference

Why an agent is not a chatbot

The word agent gets used loosely, so it is worth being precise. A chatbot takes a message and returns a message. An agent takes a goal and takes actions toward it, calling tools, querying systems, performing steps, until the task is done. The leap from responding to acting is the entire point, and it is where almost all the real engineering sits.

That leap is also where the risk sits. A chatbot that says something wrong is awkward. An agent that does something wrong has consequences, because it took a real action in a real system. So building agents well is as much about constraint as capability: giving the agent exactly the tools it needs, grounding its decisions in real data, and bounding what it is allowed to do.

We have built this for real. The Claude-powered layer in sellyourboat.io, our own venture, does agentic work on the broker side, helping manage listings and the admin around them, not just answering questions. Building an agent that acts safely inside a live platform with real inventory and real users is a different discipline from wiring up a chat box, and it is the one we work in.

The build

Tools, grounding, and guardrails

Building an agent starts with the tools. An agent is defined by what it can do, so the first work is designing the set of functions it can call, querying a database, hitting an API, updating a record, and the interfaces that let it use them reliably. Too few tools and it is useless; too many or too loose and it is dangerous. The tool design is the product design.

Grounding comes next. An agent making decisions on hallucinated facts is worse than no agent, so it has to act on your real data, through retrieval, not on the model's vague recollection. This is where agent development and RAG overlap: the agent retrieves the truth, then acts on it. Without grounding, autonomy is just confident error at speed.

Then guardrails, the least glamorous and most important part. What is the agent allowed to do without a human? Where does it stop and ask? How do you log and review its actions? These constraints are what make an agent safe to put in front of real users and real data. We build them in from the start, because we run an agent in production and know what happens without them.

When it's worth it

Where agents earn their cost

Agents are not the answer to everything, and an honest studio will tell you when a simpler build is better. An agent earns its complexity when the task is genuinely multi-step, when it needs to act across systems, and when automating that action saves real time or unlocks something a static feature could not. For a simple lookup or a single answer, a plain AI feature is cheaper and more reliable.

Where agents shine is in workflows: the repetitive, multi-step operational work that sits between systems and eats a team's time. An agent that can take a goal and work through the steps, querying, deciding, acting, can replace a process, not just a search box. That is where the value justifies the build.

We scope this honestly. If your idea needs a true agent, we build one, on Claude, grounded and guard-railed, owned by you, in eight weeks. If it needs something simpler, we tell you, because selling you more complexity than the problem warrants is how AI projects fail. The goal is the right build, not the most impressive-sounding one.

FAQ

Questions, answered straight.

What is AI agent development?

Building an AI system that takes actions, not just answers. An agent is a model given tools it can call, grounding in your data so it acts on facts, and guardrails so it acts safely, then the autonomy to complete multi-step tasks. The engineering is in the tools, grounding, and constraints, not the model itself.

How is an agent different from a chatbot?

A chatbot takes a message and returns a message. An agent takes a goal and takes actions toward it, calling tools, querying systems, performing steps until the task is done. The leap from responding to acting is the whole point, and where the engineering and the risk both live.

Have you built an AI agent before?

Yes. The Claude-powered layer in sellyourboat.io, our own venture, does agentic work on the broker side, helping manage listings and admin inside a live platform with real inventory and users. Building an agent that acts safely in production is the discipline we work in, not one we are reading about.

What does an AI agent cost to build?

From 16,000 GBP for a focused agent, 30,000 GBP for a larger build with multiple tools, user types, and integrations. Both fixed price, both eight weeks. Model inference cost, the per-call API spend, is passed through to you at cost, never marked up.

Are AI agents safe to put in production?

Only if built with guardrails, which is most of the work. We constrain what the agent can do without a human, ground its decisions in real data, and log its actions for review. An agent that acts wrong has real consequences, so safe autonomy is engineered in deliberately, not assumed.

Do I always need an agent, or sometimes something simpler?

Often something simpler. An agent earns its complexity for genuinely multi-step work across systems. For a single lookup or answer, a plain AI feature is cheaper and more reliable. We scope honestly and tell you when you do not need the more complex build.

Ready

Build an agent
that actually acts.

Tell us the workflow you want an agent to own. We will scope it, build it on Claude with the right tools and guardrails, and ship it in eight weeks.

Book a scoping call →

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