llm
32 articles
From Prompt to Production: A Practical Guide to Agentic AI Architecture
DataTalksClub founder Alexey Grigorev shared the AI Engineering Buildcamp syllabus: LLM APIs, RAG, Agentic Flows, Monitoring & Guardrails, Evaluation, and a capstone. A practical learning path for building agentic AI in production.
Your LLM Isn't Writing Correct Code — It's Writing Code That Looks Reasonable
The author benchmarked system SQLite against an LLM-generated Rust rewrite. Even though it compiled and passed all tests, primary key lookups were ~20,000x slower. The takeaway: define acceptance criteria before you talk about AI productivity.
MCP Lifesaver? Context Mode Saves You 98% of Context Tokens
A hot HackerNews project called Context Mode uses sandbox isolation and smart retrieval to block bloated tool outputs from flooding LLM context windows — claiming up to 98% token savings!
Programming is Becoming Unrecognizable: Karpathy Says December 2025 Was the Turning Point
Karpathy says coding agents started working in December 2025 as a hard discontinuity. He built a DGX Spark video analysis dashboard in 30 minutes from one English sentence. Programming is becoming agent direction, not typing.
The LLM Context Tax: 13 Ways to Stop Burning Money on Wasted Tokens
The 'Context Tax' in AI brings triple penalties: cost, latency, & reduced intelligence. Nicolas Bustamante's 13 Fintool techniques cut agent token bills by up to 90%. A real-money guide for optimizing AI context, covering KV cache, append-only context, & 200K token pricing.
The SaaS Moat Is Crumbling — When LLMs Eat the Interface, All That's Left Is API vs API
Nicolas Bustamante argues LLMs are ending Ben Thompson's Aggregation Theory. With chat as the universal interface, SaaS companies' moats built on 'workflow complexity + user muscle memory' evaporate, leading to pure API vs API commodity competition.
Karpathy Trained GPT-2 for Just $72 — OpenAI Spent $43,000 Seven Years Ago
Karpathy open-sourced nanochat — a minimal LLM training framework. With 8 H100 GPUs running for 3 hours at $72, you can train a GPT-2 level model. OpenAI spent $43,000 training the same model in 2019. That's a 600x cost reduction. On spot instances, it's just $20.
MIT Research: Making LLMs Recursively Call Themselves to Handle 10M+ Tokens
When you stuff too much into a context window, models get dumber — that's context rot. MIT proposes Recursive Language Models (RLMs), letting LLMs recursively call themselves in a Python REPL to handle massive inputs. GPT-5-mini + RLM beats vanilla GPT-5 on hard tasks, and it's cheaper too.
Simon Willison's 2026 Predictions: Is AI Replacing Human Coding?
Simon Willison shares his 2026 LLM predictions on Oxide and Friends podcast — LLM code quality will be undeniable, sandboxing will finally get solved, and there's a prediction about kākāpō parrots (◕‿◕)
AI Time Capsule: Karpathy Grades 10-Year-Old HN Predictions with GPT
Karpathy used GPT 5.1 to analyze decade-old Hacker News threads and find out who actually predicted the future (◕‿◕)
Sebastian Raschka's 2025 LLM Review — The RLVR Era Has Arrived
From RLVR to inference-time scaling, what happened in 2025? Raschka's year-end summary highlights the key shifts
Karpathy's 2025 LLM Year in Review — The RLVR Era Begins
From RLVR to Vibe Coding, Karpathy breaks down 6 key LLM developments in 2025