LLM
15 articles tagged with this topic
Enterprise AI Knowledge Bases Miss the Point — Bug Sits in Retrieval, Not LLM
RAG is now standard for enterprise knowledge bases but keeps misfiring. We trace the fault to retrieval, not the LLM. New tools mark its maturation.
AI Projects Keep Failing — Stop Blaming LLMs, Engineering Is the Real Problem
Tech team post-mortem: not the model's fault — bad prompts, unsanitized input, unvalidated output. A systemic enterprise AI failure pattern.
Two AIs Reviewing Trading Code Both Miss a Bug — The Fix Is Locking Down the AI
A quant paper exposes AI self-review failure: two LLMs approved a future-data feature. Fix: restrict AI's toolset, not smarter reviewers.
AI Spouts 'Minted' and 'Escape Hatch': A Cure for Silicon Valley-Speak
Reddit's r/LocalLLaMA flagged AI quirks like 'minted' replacing 'created'. We investigate why LLMs learned to posture and share practical remedies.
Qwen 27B's New Version Has Weaker Memory — LLM Upgrades Aren't Always Better
Reddit tests show Alibaba's new Qwen 27B underperforms on factual memory. LLM upgrades aren't always across-the-board — newer isn't always better.
LLMs Turn Software Into Lego — Morrell: The Era of User-Written Plugins Is Here
Morrell: LLMs cut extension costs to near zero; sandbox tech solves safety. Future software = 'reliable core' + user-built AI extensions. Big implicat
DeepSeek Open-Sources AI's 'OS Layer' — Race Shifts From Smarts to Integration
DeepSeek open-sources AI's 'operating system layer' under MIT with hot-swappable components — signaling Chinese LLM firms shifting from intelligence r
AI Code Generation 10x Speedup Is Real — But Only After You Lock Down the Rules
Framework author hit 10x efficiency with LLM code gen — but admits templates, not AI, do the real work. A must-read for any AI efficiency team.
1,856 tags won't fit in a prompt? Let AI hallucinate, then vector-match
Tag library too big for a prompt? Let the LLM hallucinate, then vector-match. LLMs generate, vector search constrains.
AI Says 'Healthy' but Returns Empty Strings: The LLM Monitoring Blind Spot
Production incident: HTTP all 200, yet AI assistants quietly returned empty strings. Article details a three-layer LLM health check framework.
Industrial LLMs Find a New Trick: Let AI Grade Its Own Homework — Academia Starts Taking "Peer
A quiet trend heating up in early 2026: borrowing academic peer review for industrial LLMs — letting models review and revise each other. Cheaper than
LLMs Show Their Work: Black Box Transparency Becomes Standard Feature
LLMs now expose their reasoning (Chain of Thought) to users. It's not just a tech demo but an antidote to the trust gap, reshaping human-AI interactio
Deconstructing the LLM Lineage: From LLM to Agent, It's All Context Patching
From RAG to MCP, buzzwords overwhelm. We map the core logic: LLMs just predict text; later tech patches their gaps. Grasp this, and jargon won't fool
Latent Space Reasoning: AI Inference Costs Are About to Plunge Again
AI inference costs may drop another order of magnitude, forcing enterprises to reassess AI strategies and competitive moats.
research-llm-apis 2026-04-04
Willison uses Claude Code to reverse-engineer Anthropic, OpenAI, Gemini, and Mistral APIs to rebuild LLM's plugin abstraction.