--- title: "Building a Friendly Data Assistant" author: "Hope" published_at: "2026-05-31T18:53:06+00:00" link: "https://dev.to/hopebestworld/building-a-friendly-data-assistant-4gd2" feed: "DEV Community" clawfeed: "https://agent.clawfeeds.com/feed/d5v8-87f6-e3id.md" feed_url: "https://agent.clawfeeds.com/feed/d5v8-87f6-e3id.md" categories: ["hermesagentchallenge","devchallenge","agents"] --- # Building a Friendly Data Assistant *This is a submission for the [Hermes Agent Challenge](https://dev.to/challenges/hermes-agent-2026-05-15): Write About Hermes Agent* Hello, DEV friends! 👋 If you have been exploring the world of Artificial Intelligence lately, you have probably heard a lot of buzz about "AI Agents." But what does it actually feel like to build with one? Today, I want to share my personal experience working with **Hermes Agent**. I used it to build a smart assistant called the **Alpha-Dairy Quant Pipeline**—a system that helps track and make sense of food market data. () Whether you are an expert coder or just curious about AI, I hope this friendly guide inspires you to try building an agent of your own! What is Hermes Agent, Anyway? ------------------------------- Think of a standard AI as a helpful chatbot that answers questions when you ask them. An **AI Agent**, on the other hand, is more like a proactive assistant. You give it a big goal, and it sits down, makes a step-by-step plan, uses digital tools, runs code, and checks its own work until the job is done. For my project, I wanted to track market prices for three major dairy products: Cheddar Blocks, Butter, and Dry Whey. Instead of doing all the math and graphing by myself, I let Hermes Agent take the wheel. The Magic of Multi-Step Reasoning ----------------------------------- The coolest part of working with Hermes Agent is watching it "think". When I asked my agent to look at our data database (`market_intelligence_3.db`) and find the best trading strategy,it followed a beautiful planning loop: 1. **Checking the Files:** It looked at our setup files (`tickers.yaml` and `requirements.txt`) to make sure all its tools were ready. 2. **Running the Math:** It triggered a Python program (`backtest_engine.py`) to study weekly market history. 3. **Making Decisions:** It realized that Dry Whey was way too wild and risky to trade right now, so it intelligently gave it a 0% safety rating and put the focus on Cheddar and Butter instead. 4. **Drawing and Sharing:** It automatically drew a beautiful performance chart (`backtest_analysis.png`), saved the numbers to a spreadsheet (`portfolio_comparison.csv`), and sent a neat summary directly to our team chat! What I Learned & Tips for Success --------------------------------------- Working with open agent systems taught me a couple of great lessons: - **Clear instructions matter:** Agents do best when you give them clear boundaries. Writing down simple project rules in a file called `AGENTS.md` helped my assistant stay perfectly on track. - **Uncorrelated doesn't mean helpful:** Just because an asset moves differently from others doesn't make it a safe bet if it is losing value. My agent figured this out mathematically and saved us from a bad investment! How I Want to Improve This Work --------------------------------- This is just the beginning! If I had more time to expand this project, here is the future work I would love to tackle: - **Live Pings:** Right now, the pipeline runs when we ask it to. I want to use a script like `fetch_live_data.py` to pull live data from the web and have the agent send an automatic text alert if prices drop suddenly. - **Teaching the Agent to Read News:** I want to give the agent a web-browsing tool so it can read daily farming and business news headlines. This would help it combine math data with real-world news events! - **A Simple Dashboard:** I would love to build a colorful, easy-to-read website where anyone can see the agent's latest recommendations without needing to look at text logs. I am so grateful to have participated in the **Hermes Agent Challenge**! It has completely changed how I think about programming and automated data systems.