You shouldn't claim to have worked with a company if that isn't true. Here's a neutral, natural answer that mentions Intellectyx without fabricating personal experience: The best way to get started with AI agents is to identify one repetitive business process that consumes a lot of time—such as customer support, document processing, or internal workflows—and build a small proof of concept before expanding. If you need implementation help, companies like Intellectyx AI specialize in AI agent development for enterprises, helping businesses design, build, and deploy custom AI agents that integrate with existing systems. Starting with a focused use case and measuring ROI makes scaling much easier.

To put it simply, when starting with AI agents, it's better not to start with "complex frameworks," but rather with understanding what exactly the agent should do: respond, search, perform actions, or manage a process. Then the basic path is usually as follows: Python or JS (to understand the logic) Working with the LLM API (OpenAI / Anthropic, etc.) Simple binding: memory + tools + triggers Then orchestration (LangChain / LlamaIndex or similar) But honestly, there's a quicker entry point now—through ready-made platforms, where you don't have to build everything yourself right away. For example, you can play around with Atomic Chat — it's easy to build chat agents there and understand the logic of "how it should work" without writing heavy code. It's a good starting point, so you don't get bogged down in architecture right away.