Author(s): Ray Hu Originally published on Towards AI. Three retries, one alert, and the request is gone. A DLQ took us to 0.1%. Here’s a moment every backend engineer who has shipped an LLM feature will recognize. The article explains a common …

Author(s): Enzo Lombardi Originally published on Towards AI. How MTP, DFlash, DFlash 2, and DSpark each attack the same bottleneck Text generation is embarrassingly serial. To produce token number 200 a transformer needs token 199, which needs 198, and so on back …

Author(s): Neo Leo Originally published on Towards AI. Physical AI vs. Agentic AI I remember the exact moment I got confused about this. I was sitting in a webinar, half-listening, when a speaker said “our physical AI agents” in the same sentence …

Author(s): Sandip Palit Originally published on Towards AI. Why Microsoft Fabric Disaster Recovery Fails, And How to Architect Around It When we embark on the journey of modernizing our enterprise data estates, we are often drawn to the alluring promise of fully …

Author(s): Enzo Lombardi Originally published on Towards AI. Or Why What You Recently Read About AI Watermarking Is Probably Wrong Most explanations of AI watermarking describe something that does not exist. They talk about hidden Unicode characters smuggled between words, or invisible …

Author(s): Krishnan Srinivasan Originally published on Towards AI. Powered by AI_TRANSCRIBE, turning recorded support calls into a structured, queryable feedback table. A call center runs on a routine most of us know without ever having worked one. A customer calls in. An …

Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. Why this landed now I counted every string NVIDIA’s new agent router matches on. There are 113 of them. Exactly one is ever tested against your prompt rather than against …

Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. Claude Code Runs the Real Ponytail. Cursor and 11 Others Settle for 2,593 Bytes. Ponytail’s own portability doc lists 22 coding agents. I parsed it and counted: only 9 of …

Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. Y Combinator Ditched All But One Claude Code Tool for 16 of Its Own Y Combinator open-sourced the agent harness it runs its own company on. I read the adapter …

Author(s): Rizwanhoda Originally published on Towards AI. NVIDIA’s new NOOA framework collapses prompts, tools, and state into a single class and it might make you rethink your entire agent stack AI agents have gotten weirdly complicated. After introducing why “simple” agents quickly …

Author(s): Diogo Santos Originally published on Towards AI. A small declarative language that compiles agent intent into a governed plan — and proves, after the fact, that the run stayed inside its rules. You wired up an LLM agent. It can read …

Author(s): Diogo Santos Originally published on Towards AI. A deterministic, human-gated tool that turns your agent’s real failures into reviewed AGENTS.md, Claude, and Copilot instructions — no LLM in the loop. Your coding agent reviewed a pull request last Tuesday. It read …

Author(s): Vektor Memory Originally published on Towards AI. Custom code generated image Like this: The model would normally pick any of: [‘signature’, ‘mark’, ‘trace’, ‘fingerprint’]watermark nudges it to pick: signature score of the word actually used: 87score of a word that lost: …

Author(s): Caden Lippie Originally published on Towards AI. Creating a Multilayer Perceptron from Scratch A perceptron is a fundamental component of artificial neural networks. Inspired by the neurons in our brains*, these perceptrons make decisions and “learn” by iterating to minimize errors. …

Author(s): Caden Lippie Originally published on Towards AI. Creating a Transformer from Scratch Originally introduced in the 2017 paper “Attention is All You Need” (Vaswani et al., 2017), transformers form the structure for most modern large language models, including ChatGPT and Claude. …