The first AI agent I would build is not a stock picker. A no-code tutorial just walked four hundred thousand people through building their first agent. It is a good tutorial. But the agent most people will copy from it is the wrong first build. So let me show you the one an analyst should build instead.
Here is the plan. I am going to break down the three parts of any agent. A brain. Tools. And the rules that govern both. Then I am going to point those three parts at a research job, not a trading job. By the end you will have the blueprint for a morning-brief agent for your own coverage list.
Start with the brain. The tutorial says an agent needs three things, and the first is a brain. The brain is a chat model plus memory. The model is the reasoning. The memory is what it holds across time. In the demo, the agent was told about a list, and a moment later it forgot the list completely. The fix was simple. Add memory. For an analyst, this is not a detail. This is the whole point. Your coverage list is the memory. You want an agent that remembers what you told it on Monday when you open it on Sunday. A brain with no memory is just a chatbot. A brain with memory is an assistant.
Second part. Tools. In the tutorial the tool was a Google Sheet, and the agent could write a new row to it. For our build, the tools are read-only first. The agent can read a new ten-K. It can read an eight-K. It can read an earnings transcript. It can read your tracker. What it cannot do, on day one, is write a buy or a sell anywhere. Notice what this agent is not doing. It is not telling you what to do. It is reading the things you would read, faster, and laying them out for you. That is the difference between a research assistant and an oracle.
Third part. The system prompt. The tutorial calls it the brain stem. The part that tells the brain how and when to use the tools. This is the part most people skip. It is the part that matters most. For a research agent, the system prompt says three things. One. Cite the source and the date on every single line. Two. Classify every change as positive, negative, or unclear. No vague summaries. Three. Confirm before you write anything down. Never act without a check. Those three rules are not features. They are the standard.
Now here is the most useful moment in the whole tutorial. The first real run failed and succeeded at the same time. It wrote the row. But it wrote it without confirming. And the date was completely wrong. It stamped 2023. The model was not broken. The instructions were loose. The fix was two lines. Always confirm, even when the information looks complete. And pull the date dynamically from the message itself, instead of letting the model guess. Now map that onto research. An agent that drafts a filing summary without confirming, with the wrong reporting period, is not a faster analyst. It is a faster way to be wrong. The fix is the same. Tighter rules. Cited sources. A confirmation step.
So here is the first agent, end to end. A morning brief for a coverage list. The brain holds the list. The tools read filings and transcripts. The rules force citation, classification, and confirmation. Every morning it produces a draft. For each name on the list, it gives you what was filed, the exact source, the date, what changed, and one line on what to verify next. It does not say buy. It does not say sell. It does not name a price target. It hands you a desk-ready brief and a list of open questions. You read it in five minutes instead of fifty.
Now be honest about the limits. The agent can misread a filing. It can attribute a number to the wrong section. It can sound confident and be flat wrong. The tutorial's own warning applies here. A black-box agent can hallucinate, and it can leak data you did not mean to share. So the read-only default is not timidity. It is design. And the cite-the-source rule is not bureaucracy. It is how you catch the hallucination before it costs you.
Here is how you use it safely. AI owns construction and speed. You own the assumptions and the decision. The agent builds the brief. You judge what it means. Every claim it makes traces to a primary source you can open yourself, on EDGAR, in the transcript, in the filing. Every brief ends with what to verify, not what to do. That is the line you do not cross. The machine prepares you. It does not decide for you.
So here is the takeaway. The edge was never the model. The edge is the workflow you wrap around it. A stock-picker agent is a black box you should not trust. A morning-brief agent is a junior analyst you can supervise. Build the second one first.
If you want the build, comment BRIEF and I will send the morning-brief agent blueprint, the read-only tool list, and the system-prompt rules. And read the full disclaimer in the description before you build anything. This is educational only. Not investment advice. The AI structures the research. You make the call.