LAI #110: Fixing Context Rot and Rethinking How Agents Reason
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts, This week, we’re looking at why agent systems drift, confuse themselves, or quietly break when tasks get long. I unpack the real cause of “random” agent degradation: context …
From Brains to Agents: My Journey Building LLM Systems That Act
Author(s): Jofia Jose Prakash Originally published on Towards AI. How I moved from “answers” to “actions” with retrieval, tools, and agent loops Large‑language models (LLMs) are born as generalist engines of static, albeit powerful, brains. Static in the sense that while their …
Stop Wasting PDFs — Build a RAG That Actually Understands Them
Author(s): Robi Kumar Tomar Originally published on Towards AI. Turn messy PDFs into reliable, auditable answers — a production-ready RAG pipeline with OCR, heading-aware chunking, FAISS, cross-encoder reranking, and strict LLM prompts Image Source : Google Gemini TL;DR — for skimmers Problem: …
Learning CUDA From First Principles
Author(s): Ayoub Nainia Originally published on Towards AI. Being a PhD student working on AI and NLP, I’ve spent quite some time using PyTorch and other high-level frameworks that abstract away the GPU. But recent discussions about whether I should learn CUDA …
The Context Advantage: How Palantir AIP Operates the Modern Enterprise
Author(s): Sainath Palla Originally published on Towards AI. Over the last couple of years, most conversations about AI have focused on model size, speed, or how many parameters a system can fit into memory. These are useful metrics, but they do not …
The Context Window Paradox: Engineering Trade-offs in Modern LLM Architecture
Author(s): Shashwata Bhattacharjee Originally published on Towards AI. Introduction: Beyond the Marketing Numbers The AI industry has entered a curious arms race. Anthropic announces 200K tokens. Google counters with 1M. Meta teases 10M. Each announcement generates headlines, yet beneath this numerical escalation …
The 390x Speed Advantage: Unpacking AI’s Victory in Clinical Diagnosis
Author(s): Shashwata Bhattacharjee Originally published on Towards AI. The headline writes itself: AI defeats human doctors in medical diagnosis, delivering results in under two seconds versus 13 minutes. But beneath this dramatic 390x speed differential lies a far more nuanced story about …
Your AI Agent Works in Demo. It Dies in Production. Here’s Why.
Author(s): Elliott Girard Originally published on Towards AI. I’ve built 38 AI agents in 2025. 6 made it to production. 42 didn’t. Here’s what killed them — and how to avoid the same fate. The Demo That Fooled Everyone You know the …
The Builder’s Notes: Prior Authorization Wastes 16 Hours Per Week Per Physician. Here’s What It Actually Costs.
Author(s): Piyoosh Rai Originally published on Towards AI. Physicians spend 16 hours/week fighting insurance companies for treatment approval. That’s $70K/year per doctor in lost productivity. For a 10-physician practice: $2M in time spent on paperwork instead of patients. Here’s the math that …
I Tested a 7B Model That Beat Models 7× Its Size. Here’s What I Found.
Author(s): Adham Khaled Originally published on Towards AI. The Falcon-H1R doesn’t make sense on paper. Until you understand what UAE’s TII actually built. Last Saturday, I downloaded a model that shouldn’t exist. 7 billion parameters. Open-source. From Abu Dhabi. On paper, it’s …
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