Getting Dirty Hands: Kicking off your no code build on AgentSuite

You’ve already learned the basics. Now it’s time for you to build a working AI agent without writing a line of code, and this article walks through the whole build.  

The tool is AgentForge, the no code ai agent builder inside AgentSuite: you describe what you know and what you want the agent to do, in plain language, and AgentForge shapes it into an agent you can test, refine, and later publish.  

The skill you bring is your own knowledge and judgment, the thing you already have. 

How to access AgentForge? 

The path is short. Sign in at VeWorld.ai, your portal to the agent economy running on VeChain, and create your ‘creator profile’. That profile is how AgentTrust assigns your agents their creator-tied identities, hashed on blockchain, helping to build customer trust. From the homepage after you’ve finished creating a profile, select ‘Create an agent’, and AgentForge opens ready to build. 

The beauty of this platform is you don’t need any technical knowledge to build your first agent.  

What does the workspace look like? 

The AgentForge workspace is organized around a few simple areas that you fill in simply and conversationally, with the platform supporting the rest. Identity and purpose is where you name your agent and say what it is for. Knowledge and tools is where you give it what it needs: what it knows, and what it can act on. Service and behavior is where you set how it responds and what it promises customers. And Preview is where you put it through its paces before it meets the world. 

What should you name your agent? 

Start by making a new agent and giving it a clear, purposeful name, because the name is the first thing a customer reads on AgentMarket, the marketplace where your agent will eventually be hired.  

A name like UK Small Business Tax Helper tells a customer exactly what they are hiring; TaxBot 3000 does not. Aim for plain and specific over clever.  

You can refine it later, but a purposeful name now keeps the build focused on one clear job, which is the single biggest predictor of an agent that works. 

How do you give it a goal it can act on? 

A good goal is narrow and testable: you should be able to look at a result and say whether the agent met it. Help people with money is not a goal an agent can act on. Answer UK sole trader tax questions and flag when a professional is needed is.  

The tighter the goal, the better the agent performs and the easier it is to describe honestly when you list it. If you find yourself writing several goals, that is usually a sign you have several agents. The narrowest idea is the best place to begin experimenting. 

Which tools and knowledge does it need? 

An agent is only as capable as what it can draw on, so this step gives it its knowledge (what it knows) and its tools (what it can do), such as looking something up, doing a calculation, or reaching an outside service. Add only what the goal needs.  

A tax question agent needs current rules and a way to reference them; it does not need a calendar or a weather lookup. Every tool you add is something you will later have to trust and test, so a lean set focused on the goal is easier to make reliable, and easier for a customer to understand. 

Where should it pause for a human?

Autonomy is a dial, not a switch, and now you are the one setting it for a real agent. Decide where your agent can act freely and where it should stop and check.  

A research agent can gather and summarize on its own. An agent that spends money, sends messages on someone's behalf, or gives regulated advice should pause at the point of consequence.  

Sensible checkpoints are what let a customer trust the agent with real work, and they become part of the service level you promise when you publish. 

How do you test before you trust? 

Never publish an agent you have not watched work. AgentForge lets you run your agent safely before any customer sees it. Give it the real questions a customer would ask, including the awkward ones, and read past the answer to what it did to get there: which tools it used, where it hesitated, where it went wrong.  

You are checking two things: does it meet the goal, and does it behave at the checkpoints you set.  

Testing is where most of the quality comes from, so spend time here before you think about publishing, which is exactly where this series goes next. 

You’re set! 

Congrats, your first agent is ready to meet the world, answer their questions, and make your knowledge exponential. Yes, it really can be that easy. 

Keep experimenting and iterating your agent as time goes by – eventually, users will be able to actively hire agents, while you get paid for them doing so. The better quality, the greater the repeat engagement – so dedicate some time to really pouring in your expertise and knowledge.