The Two Things Every Reliable Agent Needs
Author(s): Shenggang Li Originally published on Towards AI. Memory-first design + anti-Goodhart scoreboards for systems that don’t optimize proxies. Let me guess how your “agent” demo went. Photo by zero take on UnsplashThis article discusses the essential components for creating reliable AI …
Copilot vs. “Private AGI”: When Human–LLM Collaboration Is Enough (and When It Isn’t)
Author(s): Shenggang Li Originally published on Towards AI. A practical framework — with data, a little math, and field-tested workflows — for experts deciding between interactive LLM work and autonomous agent/AGI-style systems. A quiet confusion sits under most “AI at work” debates: …
4 Retrieval Strategies: Why Most RAG Systems Fail at Retrieval (Not Generation)
Author(s): Divy Yadav Originally published on Towards AI. Retrieval Strategies for Building a Robust, Production-Ready RAG System Retriever is the heart of any Rag based Systsem, and also the most critical point of failure too. Photo by GeminiThe article discusses several crucial …
Inside the Mamba-MoE Engine of Nemotron 3
Author(s): Kyouma45 Originally published on Towards AI. TL;DR The Models: The family includes Nano, Super, and Ultra.The Architecture: A Hybrid Mamba-Transformer Mixture-of-Experts (MoE) design that replaces most attention layers with Mamba-2 layers for high throughput. Key Innovations: LatentMoE: A new expert routing …
The Illusion of Thinking: Why Do Even Advanced AI Models Fail at Simple Puzzles?
Author(s): Gaurav Shrivastav Originally published on Towards AI. A deep dive into a new paper that uses the Tower of Hanoi puzzle to reveal a surprising “collapse point” in Large Reasoning Models. Recent AI models, often called Large Reasoning Models (LRMs), have …
MCP Inspector Unlocks a New Way to Develop
Author(s): Nagaraj Originally published on Towards AI. Stop Debugging MCP Servers with Console Logs I opened MCP Inspector for the first time at 2 AM. Source : AuthorThe article discusses the MCP Inspector tool, highlighting its advantages over traditional debugging methods using …
Hola-Dermat: Personalized Skincare Agentic AI Assistant, Powered by Qdrant + Perplexity + CrewAI
Author(s): Niranjan Akella Originally published on Towards AI. “Finding the right skincare product is like finding a needle in a haystack… except the haystack is the entire internet, and you’re not even sure what a needle looks like.” Illustration from MIRRAR + …
Choosing AI Agent Architecture for Enterprise Systems: Shallow vs ReAct vs Deep
Author(s): Mandar Panse Originally published on Towards AI. Understanding different execution patterns in modern LLM-powered agents Important note: These aren’t “types of AI agents” in the classical sense (like reflex agents, goal-based agents, etc.). Instead, these are architectural patterns — different ways …
Why Most RAGs Stay POCs — How to Take Your Data Pipelines to Production.
Author(s): Jeremy Arancio Originally published on Towards AI. A walkthrough to architect scalable and maintainable document indexing pipelines for RAG systems with Databricks Asset Bundles Since the release of ChatGPT, companies have discovered that if you provide entreprise knowledge into prompts, LLMs …
The Rise of Supervised Bounded Autonomy: Agentic AI in 2026
Author(s): Wahidur Rahman Originally published on Towards AI. How enterprises are moving from AI pilots to autonomous systems that deliver measurable business outcomes The world of enterprise AI is undergoing a fundamental transformation. We’re witnessing a decisive shift from “Human-in-the-loop” (HITL) assistance …
The AI Price War: How Chinese LLMs Just Changed Everything
Author(s): Wahidur Rahman Originally published on Towards AI. Why your next AI deployment might cost 30× less than you think The AI landscape just experienced a tectonic shift, and most people missed it. While Western tech giants were busy charging premium prices …
The AI Coding Paradox: Why Writing Software Just Got Easier While the Ecosystem Became Fragile
Author(s): Gowtham Boyina Originally published on Towards AI. New research suggests vibe coding could collapse open source by severing the engagement loop that sustains maintainers — unless we redesign how OSS gets funded I’ve watched the adoption curves for AI coding tools …
VL-JEPA: What Happens When AI Learns to Think Before It Speaks
Author(s): Yash Mohite Originally published on Towards AI. Understanding VL-JEPA and its approach to embedding-based vision–language modeling Modern vision language models can describe images, answer questions, and interpret videos with impressive fluency. Yet they all share an unusual habit: they talk constantly. …
From Spatial Navigation to Spectral Filtering
Author(s): Erez Azaria Originally published on Towards AI. Image generated by Author using AI In the world of machine learning, one of the most enigmatic and elusive concepts is “latent space”, the semantic hyperspace in which a large language model operates. Most …
Understanding Computer Systems: From Silicon to Software
Author(s): Ganesh Bajaj Originally published on Towards AI. A Guide to SoC, Firmware, Drivers, Kernel, and Operating Systems Every time you tap your smartphone screen, click a mouse, or save a document, an intricate dance occurs between hardware and software. Yet for …
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