AI Agent Build
Decide what to build, and whether to build an agent at all.
The agent blueprint before the build: requirements and use cases, the workflow-vs-agent decision made deliberately, and an architecture covering model, tools, instructions, and memory, so you build the right thing rather than a brittle one.
Book an initial consultation Start with an AI Readiness Audit
Before we build, what exactly should this agent do, what tools does it need, and is an agent even the right shape?
The most expensive agent mistakes are made before any code: building an autonomous agent where a workflow would do, or building one with no clear job, tools, or boundaries. This project makes those decisions deliberately, defining the work, choosing agent or workflow on the evidence, and architecting the agent at the right altitude, specific enough to steer, flexible enough to avoid brittle logic.
What's included
Requirements and use case
The job to be done, inputs, boundaries, and success criteria, defined before anything is built.
Workflow-vs-agent decision
An explicit choice between a predefined pipeline and an LLM-directed loop, made on the evidence rather than the hype.
Agent architecture
Model choice, tool set, instructions, memory and state approach, and the agent-computer interface.
System-prompt and tool plan
A system-prompt and tool-design plan at the right altitude: specific enough to steer, flexible enough to avoid brittleness.
How it works
- 1
Define the job
We capture requirements, inputs, boundaries, and success criteria for the work.
- 2
Choose the shape
We apply the workflow-vs-agent decision so you build the right pattern.
- 3
Architect
We design the model, tools, memory, and interface, and hand the build a blueprint.
What you walk away with
- A requirements and use-case definition with success criteria
- An explicit, evidence-based workflow-vs-agent decision
- An agent architecture: model, tools, instructions, and memory
- A system-prompt and tool plan at the right altitude
Frequently asked
- Can we skip design and just build the agent?
- You can if you have an approved blueprint. Without one, agents tend to be over-built and brittle. Design is the cheapest place to decide whether you even need an agent.
- What if design concludes we don't need an agent?
- Then it has paid for itself. Often the right answer is a workflow or an assistant, and recommending the simplest thing that works is exactly the point of doing design first.
Design the agent before you build it
Book a consultation to define the job, make the agent-vs-workflow call, and architect the right system.
Book an initial consultation Start with an AI Readiness Audit
Where this leads next
Agent Build & Deployment
The build executes this blueprint: tools, memory, MCP integration, and production deployment.
Explore the project