I want to automate my morning routine by having an AI agent browse specific industry sites and send me a Slack summary. I’ve looked at LangChain and CrewAI, but they seem a bit complex for a beginner. Is there an easier way to build an autonomous agent for this?
3 answers
For a beginner, I would steer clear of "raw" LangChain coding at first. Instead, check out a tool called "Relevance AI" or "MindOS." They provide a visual interface for building agents where you can just drag a "Search Web" block and connect it to an "LLM Summary" block. This allows you to understand the logic of "Agentic Workflows"—how an agent decides what to click—without getting stuck in Python syntax. Once you’ve built a few visual agents, moving to a framework like CrewAI will make much more sense because you'll already understand how "tools" and "tasks" interact.
Does using a visual builder like Relevance AI limit your ability to customize the prompt or the "memory" of the agent compared to writing it out in a Python script?
You can actually do a lot of this just using the "Web Search" plugin within ChatGPT Plus and a custom instruction. It’s not a "standalone" agent, but it’s the easiest starting point.
Craig is right for a one-off task, but if you want it to run every morning at 8 AM automatically, you’ll definitely need a dedicated platform like Angela suggested.
Jeffrey, that’s the classic trade-off. Visual builders give you about 80% of what you need, including basic memory and prompt tuning. But if you want the agent to "remember" a specific user's preference over months of data, or if you need to integrate a very niche database, you'll eventually hit a wall. That's usually the point where most people start learning the Python SDKs to get that extra 20% of performance and customization.