Four Ways to Build an AI Agent, and What Each Costs
On 6 October 2025, OpenAI unveiled Agent Builder at DevDay. A visual canvas where you drag boxes together and get an agent out the other end. Eight months later, on 3 June 2026, it was deprecated. It shuts down for good on 30 November 2026. Nobody did anything wrong there. OpenAI decided the visual builder was not the path and pointed users at the Agents SDK instead. But if you built your order…
Route Three: Serverless Functions
In this approach, you use serverless functions such as AWS Lambda, Azure Functions, or Google Cloud Functions to build your AI agent. The cost for this route is determined by the number of function invocations and the execution time of your functions. Serverless functions allow for greater customization and control over the agent's behavior, as you can tailor the code to handle complex decision-making processes.
However, the main limitation of this route is the need for a solid understanding of serverless architecture and the associated infrastructure.
Route Four: Custom Development
This route involves building your AI agent from scratch using programming languages such as Python, Java, or C++. Custom development offers the highest level of control and flexibility, allowing you to create a truly unique agent tailored to your specific needs. The cost of this route is the most significant among the four options, as it requires a dedicated team of developers to design, implement, and maintain the agent.
However, for companies with deep pockets and the technical expertise to handle custom development, this route can be the most effective in achieving their desired results.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
