Headroom: The Netflix Tool That Makes AI Agents 10x Cheaper
Author(s): Kushal Banda Originally published on Towards AI. Headroom: The Netflix Tool That Makes AI Agents 10x Cheaper Run a coding agent for an hour and check what it actually sent to the model. Full log dumps from a failed CI run. …
5 AI Security Certifications Available in 2026
Author(s): Mike Chung Originally published on Towards AI. 5 AI Security Certifications Available in 2026 Photo by Dan Nelson on Unsplash As AI is becoming more integrated in our workflows, it’s only a matter of time before AI Security also becomes mainstream. …
Engineering a Multi-Agent AI Platform — Part 7: Circuit Breakers for LLM Systems
Author(s): Muhammad Abiodun SULAIMAN Originally published on Towards AI. Engineering a Multi-Agent AI Platform — Part 7: Circuit Breakers for LLM Systems This is Part 7 of a series on engineering AI systems that learn in production. Part 3 briefly covered a …
Vercel's New Coding Agent Takes Away Your MCP Tool List. It Sends the Same 15 Schemas.
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. fx declares seventeen built-in tools, and a full turn with a subagent host carries fifteen function schemas. I measured a stock four-server MCP setup at 37 tools and 22,226 bytes …
Z.ai’s Models Found 2,436 Vulnerabilities. The Weights Aren’t the Bottleneck — Your Patch Pipeline Is
Author(s): Decoding AI Originally published on Towards AI. 2,436 findings is a discovery number. Nothing in it is a remediation number. There is a particular kind of silence that follows a very productive week. On August 14, 2026, the AI lab Z.ai …
Claude’s Protein Design Hit Rate Was 26.8%. One Target Returned 0 for 90.
Author(s): Decoding AI Originally published on Towards AI. We refit Anthropic’s published per-target protein design counts on Aug 25, 2026. Ninety designs went into the wet lab against maltose-binding protein. Ninety came back with nothing. That is the part of the story …
LLM-as-a-Judge: How to Build Reliable AI Evaluation Systems
Author(s): Rohan Mistry Originally published on Towards AI. Calibrate your judge. Detect its biases. Trust your scores. Your LLM judge might be lying to you. After introducing the problem of uncalibrated LLM evaluators, the article explains what LLM-as-a-judge actually is (a model …
Eye of the Infra — What is a Batch and an Epoch?
Author(s): Sai Kaushik Ponnekanti Originally published on Towards AI. Firstly, In the previous article, we founded a startup whose mission is to stop people from losing their life savings to fraudulent emails.. One thing we left out is that we forgot to …
Beyond a Single Model: Mastering Ensemble Learning in ML
Author(s): Naveen Originally published on Towards AI. Discover how combining multiple machine learning models — using techniques like bagging, boosting, and stacking — can dramatically improve prediction accuracy and create more robust, production-ready systems. Instead of relying on a single, fallible model, …
Knowledge Graphs vs. Vector DBs: Which One Should You Use?
Author(s): Naveen Originally published on Towards AI. Stop choosing between structured knowledge and semantic search. Learn when to use Knowledge Graphs for explicit facts and Vector Databases for implicit similarity to build smarter, more reliable AI systems. Explore the architectural tradeoff between …
Qwen Code Ditched Google 10 Months Ago. Why Do 1,110 Files Still Say “Copyright Google”?
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. I checked every one of them against every blob Google’s Gemini CLI has ever committed. The header is still literally true for 58. I was reading Qwen Code’s source last …
ContextFusion: The Context Brain Your LLM Apps Are Missing
Author(s): Rohan R Originally published on Towards AI. A deep dive for users who want results and developers who want control TL;DR (For the Impatient) Normal users: Install context-portfolio-optimizer, run cpo compile ./your-docs --budget 4000, and stop overpaying for tokens. Developers: Middleware …
Finding the Right Answers from Thousands of Documents: A Smarter RAG Approach
Author(s): Shrinidhi Atmakur Originally published on Towards AI. Finding the Right Answers from Thousands of Documents: A Smarter RAG Approach Introduction RAG is often presented as a simple, three-step architecture: put documents into a vector database, convert the user’s question into an …
Learning Agentic AI: Agentic Loop with State
Author(s): Haixi Li Originally published on Towards AI. Lesson 3 So far, our loop has been reactive — the model calls a tool, gets a result, and reacts. But it has no memory of why it’s doing what it’s doing beyond what’s …
The Hidden Pattern Behind Most Legacy CRM Failures
Author(s): Eshita Nandy Originally published on Towards AI. A decade of Oracle Siebel and legacy CRM work revealed one hidden pattern behind most enterprise system failures. Three years ago, I joined what was supposed to be a routine troubleshooting call. A business …
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