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DZone.com Feed Recent posts on DZone.com Designing Tool-Calling AI Agents That Survive Production: A LangGraph Approach Jul 7th 2026, 14:00 by Shubham Gupta Most agent demos work beautifully on stage and fall apart the first week in production. The reason is almost always the same: the demo treats tool-calling as a happy path, and production is nothing but edge cases. A tool times out. A model hallucinates an argument.  The agent loops on itself and burns through your token budget. After shipping a few of these systems, I have learned that the durable design question is not "can the agent call a tool" but "what happens when the tool call goes wrong." ‍ Building a Mortgage Agent With FRED Data, FastAPI, and LLM Tool Calling Jul 7th 2026, 13:00 by Sushma Kukkadapu If you have ever tried to build a “mortgage rates today” feature, you have probably landed on the same fork in the road I did. Consumer finance sites publish attractive numbers, but those pages are editorial HTML, not APIs. Layout changes break scrapers, terms of use are unclear, and it is hard to explain what statistic you are actually showing. For a developer project meant to be forked on GitHub, that path is a dead end. I wanted something smaller and more honest: national 30-year and 15-year fixed benchmarks from a source economists already cite, plus a separate surface where first-time buyers could ask basic questions without handing over sensitive data. The result is US Homes Mortgage Agent, an open-source FastAPI application with two clear jobs. One page shows macro rates and a chart. Another page hosts a conversational assistant that is grounded in the same data and in plain Python math. ‍ An XGBoost Property Valuation Postmortem: Leakage, Overfitting, and SHAP Surprises Jul 7th 2026, 12:00 by Tejas Ashok I spent the last few months building a property valuation engine for Orlando. The goal was to beat a basic baseline (median price per square foot) using XGBoost. My v1 model looked good on paper until I looked under the hood. It had fatal flaws that the standard metrics could not surface. This is a postmortem on how a high R-square (R²) fooled me, how Optuna forced me to rethink my hyperparameter space, and why hyper-local real estate data will eat you alive if you treat it like a Kaggle dataset. ‍ ‍ You are receiving this email because you subscribed to this feed at blogtrottr.com. By using Blogtrottr, you agree to our terms. If you no longer wish to receive these emails, you can unsubscribe from this feed, edit this subscription, or manage all your subscriptions.