Critical Perspective on LLM Implementation: Learning from Past Technology Cycles
Even though the impacts of LLMs have never been seen before, they feel familiar to earlier assumptions.
Read the full articleYou might also wanna read

LAI #134: Your First LLM App on AWS for Under a Dollar
Loop engineering with Claude Code, plus a Towards AI enterprise launch, vLLM on L40S, and context windows as memory management Good morning,
How OpenClaw and AI agent harnesses are reshaping LLMs, inference, and CPU demand
AI agent harnesses like OpenClaw are reshaping how LLMs are built, trained, and run, driving demand for CPUs, faster inference, and new AI a

Beyond the chatbot or AI sparkle: a seamless AI integration
When I talk about Generative AI , whether it’s with developers at conferences or with customers, I often find myself saying the same thing:
A Journey from AI to LLMs and MCP - 3 - Boosting LLM Performance – Fine-Tuning, Prompt Engineering, and RAG
> **Cross-posted.** This article's canonical home is [Data Lakehouse Hub]( ## Free Res...
What AI Is and Isnt: A Laypersons Guide to How LLMs Actually Work
> **Cross-posted.** This article's canonical home is [Data Lakehouse Hub](
How AI Agents Actually Work Under the Hood
Demystifying the agentic loop: understand how LLMs suggest actions, how Python validates and executes them, and why this matters for product

Comments
Sign in to join the conversation.
No comments yet. Be the first.