Apple Is Suing OpenAI. An Engineer Wrote “LOL, I Can Still Access the Server.” That Quote Is Now in a Federal Lawsuit.
Author(s): Dr Swarneendu AI Originally published on Towards AI. Apple Is Suing OpenAI. An Engineer Wrote “LOL, I Can Still Access the Server.” That Quote Is Now in a Federal Lawsuit. Over 400 former Apple engineers now work at OpenAI. Two are …
I Tried to Break an AI’s Security — Here’s Everything I Learned as a Complete Beginner
Author(s): Neha Khan • AI & Software Engineer Originally published on Towards AI. Part 1 of my AI Security Engineering learning journey A few weeks ago, I decided I wanted to move from full-stack development into AI Security Engineering. The problem? I …
Agent Harness Engineering vs. Loop Engineering vs. Graph Engineering
Author(s): ML Point Originally published on Towards AI. A practical guide to the three architecture layers people keep mixing together The confusion is understandable. All three ideas sit around the same model, all three influence reliability, and all three can contain “loops.” …
🦀 Building AI Agents in Rust – part 10
Author(s): Enzo Lombardi Originally published on Towards AI. A provider with no socket Every provider Eugene has spoken to so far, going all the way back to Part 6, ends the same way: a URL, a header, a JSON body over HTTP. …
AI, Machine Learning, Deep Learning, GenAI, and Agentic AI — What’s Actually the Difference?
Author(s): Revati Pawar Originally published on Towards AI. AI, Machine Learning, Deep Learning, GenAI, and Agentic AI — What’s Actually the Difference? Everyone uses these terms, yet almost nobody explains what they mean. Here’s the clearest breakdown — with real examples from …
![Optimizing LLM Token Costs in Production: A Practical Engineering Playbook [Part 3]](https://miro.medium.com/v2/resize:fit:700/1*K6V2x8CJ8JUoaLlA1aFXVA.png "Optimizing LLM Token Costs in Production: A Practical Engineering Playbook [Part 3]")
Optimizing LLM Token Costs in Production: A Practical Engineering Playbook [Part 3]
Author(s): Garvit Agarwal Originally published on Towards AI. Optimizing LLM Token Costs in Production: A Practical Engineering Playbook [Part 3] In Part 2, we focused on optimizing how requests are constructed before they reach the language model. We explored how techniques like …
Building Intelligent Feedback Systems: A Deep Dive into Conditional Agentic Workflows with LangGraph
Author(s): Sandip Palit Originally published on Towards AI. Building Intelligent Feedback Systems: A Deep Dive into Conditional Agentic Workflows with LangGraph The landscape of Artificial Intelligence has shifted dramatically over the past couple of years. We are no longer simply chatting with …
Kimi K3 Beat Fable 5 and GPT-5.6 Sol at Frontend Code — Then I Found the 51% Hallucination Rate
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. Kimi K3 Beat Fable 5 and GPT-5.6 Sol at Frontend Code — Then I Found the 51% Hallucination Rate On July 16, Moonshot AI shipped Kimi K3 — a 2.8-trillion-parameter …
I Helped 50,000 People Set Up Claude Code. Here’s What I Didn’t Tell Them
Author(s): Anubhav Originally published on Towards AI. The setup was the easy 20%. Six months in, here’s what actually breaks, memory that rots without a warning, connectors that say “Connected” and aren’t, and subagents that report success for work they never did. …
Harnesses: Eager vs. Just-in-Time
Author(s): Jordan Carson Originally published on Towards AI. Harnesses: Eager vs. Just-in-Time Read the article for free here. Created using matplotlib, more on this later. I’ve been building my own coding harness, and the thing I kept obsessing over was the first …
I Replaced One $15-Per-Million-Token Frontier Model With Five Cheap Ones Arguing With Each Other. It Won.
Author(s): Adi Insights and Innovations Originally published on Towards AI. The biggest quiet trend in AI right now isn’t a bigger model. It’s five small ones voting on the answer instead — and it’s already outperforming solo frontier calls in production. Here’s …
OpenSearch Optimizations for Production RAG, Part 2: Lexical Retrieval
Author(s): Srini Dwarakanathan Originally published on Towards AI. OpenSearch Optimizations for Production RAG, Part 2: Lexical Retrieval This is Part 2 of a series on optimizing OpenSearch for production RAG. Part 1 covered semantic retrieval, meaning vector search with Approximate and exact …
#3 Claude Loops: Design the Tool Loop
Author(s): Sage Holloway 🍓 Originally published on Towards AI. #3 Claude Loops: Design the Tool Loop How to expose the right tools, hide the dangerous ones, and use permissions so Claude Code can act without wandering. Claude Loops: Design the Tool Loop …
Why AI-Built Apps Pass Every Test and Still Break in Front of Users
Author(s): Mikhail Shytsko Originally published on Towards AI. Why AI-Built Apps Pass Every Test and Still Break in Front of Users Your coding agent builds the whole app and gets the suite passing in an afternoon. But those tests ran against a …
I Replaced My $400/Month Claude API Bill With GLM-5.2 + vLLM Here’s the Exact Playbook
Author(s): allglenn Originally published on Towards AI. GLM-5.2 + vLLM Here’s the Exact Playbook Last month, three separate engineers on my team opened Slack at 6 AM asking the same question: why did our AI spend spike from $290 to $440 in …
Recent Posts
