Building Long-Running Claude Managed Agents: Why State Matters More Than Compute
Author(s): Divy Yadav Originally published on Towards AI. Photo from AI At 9:03 am on a Tuesday, my research agent said hello and stared at an empty /workspace/. Six hours of analysis from the night before. Gone. The cloned repository. The installed …
Understanding Reinforcement Learning — A Primer
Author(s): Ayo Akinkugbe Originally published on Towards AI. Understanding Reinforcement Learning — A Primer Photo by Girl with red hat on Unsplash Introduction: Learning by Trial and Error Imagine teaching a dog to fetch a ball. You don’t hand the dog a …
Harness Engineering Explained: The One Layer Behind Every AI Agent That Actually Works
Author(s): Divy Yadav Originally published on Towards AI. Most AI agents are built with the smart part but not the safe part. Here is what the missing layer is, why it exists, and what breaks without it. A company built an AI …
The Math Behind “The House Always Wins”
Author(s): Fern Originally published on Towards AI. The Math Behind “The House Always Wins” Link: https://unsplash.com/photos/red-casino-neon-sign-turned-on-bYtIpXnzsQM Casino probabilities are not guesses. They are calculated by listing every possible outcome, assigning each outcome its correct probability, and then checking which outcomes lead to …
Linear Trees: What If Every Decision-Tree Leaf Had Its Own Linear Model?
Author(s): Fern Originally published on Towards AI. Linear Trees: What If Every Decision-Tree Leaf Had Its Own Linear Model? Link: https://unsplash.com/photos/a-computer-screen-with-a-bunch-of-code-on-it-ieic5Tq8YMk As data scientists, our machine learning toolkits often force us into a frustrating ultimatum, making us choose between two entirely different …
RAG Evaluation 101: What to Measure (and What Not to)
Author(s): Anubhav Originally published on Towards AI. Five questions, five papers, five things your RAG eval is probably getting wrong. If you have built a RAG, you have asked yourself the question: is this thing actually any good? After the lead paragraph, …
I Tried 100+ Claude Skills. These 6 Actually Changed How I Work.
Author(s): Divy Yadav Originally published on Towards AI. After testing more than 100 Claude Code skills, only six became part of my daily workflow. Here is what each one does. I built more than 100 Claude Code skills. Photo from AIThe author …
5 Python Frameworks That Put You Ahead of 90% of AI Beginners
Author(s): Divy Yadav Originally published on Towards AI. Not a list to memorize. The 5 real gaps that decide whether your AI project ships, or dies on your laptop. A beginner spent three weekends building an AI app that summarized PDFs. It …
Vibe Machine Learning: Using GenAI for ML, AI and R&D
Author(s): Artem Shelamanov Originally published on Towards AI. Vibe Machine Learning: Using GenAI for ML, AI and R&D The rise of AI tools has affected many people across different areas of IT. But the field that has been affected the most is, …
Building AI Agents Part 3C: Why Your Framework Choice Will Make or Break Your Production System
Author(s): Raj kumar Originally published on Towards AI. Why the framework that worked in your prototype will stall your production system The fintech team I mentioned in Part 3B (Testing and Evaluation Strategies for Production AI Agents) had built something impressive. Their …
Claude Code for Data Science Projects
Author(s): Rashmi Originally published on Towards AI. Why data science needs a different playbook Data science work has a structural problem that ordinary software engineering doesn’t: the artifact that matters most — the dataset — usually can’t live in context, can’t be …
Self-Hosting Airflow at Home: Automating Stock Price Data Collection
Author(s): FS Stance Originally published on Towards AI. Self-Hosting Airflow at Home: Automating Stock Price Data Collection One of the main goals of creating my home lab is to gain a deeper understanding of Machine Learning Operations (MLOps) and how to productionalize …
China’s Coding Model, Kimi K2.7 Code, is 6x Cheaper Than Claude. It also Grades Its Own Homework
Author(s): Kashif Mehmood Originally published on Towards AI. China’s Coding Model, Kimi K2.7 Code, is 6x Cheaper Than Claude. It also Grades Its Own Homework China’s best open-weight coder is here; it’s a fraction of the cost, and you cannot independently verify …
My EfficientNet Scored Worse Than Logistic Regression, Here’s What Changed…
Author(s): Pavankumar More Originally published on Towards AI. My EfficientNet Scored Worse Than Logistic Regression, Here’s What Changed… I spent several weeks on the Messy Mashup Kaggle competition, a music genre classification challenge where the test data sounds like someone threw ten …
Bagging vs Boosting: The Complete Beginner’s Guide to Ensemble Learning in Machine Learning
Author(s): Sai Bhargav Rallapalli Originally published on Towards AI. From decision trees to Random Forest and XGBoost — everything explained simply, with real-life analogies, examples, and code. You’ve probably heard the saying: “Two heads are better than one.” After the introduction, the …
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