What It Means to Learn
Children forget everything yet learn faster than any AI. What are they exhibiting about learning that we've failed to capture in our models?
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MCP Discoverability: The Hidden Cost of Scale
As the agentic ecosystem matures, tools are no longer scarce. They're everywhere. The hard part now isn't wiring up tools — it's helping models discover which ones to use.
Context Engineering: The Hidden Lever Behind Agent Performance
In the past year, agent architectures have gone from niche experiments to front-page product strategies. But one area remains dramatically under-discussed: context engineering.
Building Better AI Evals: Lessons from the Trenches
Evaluation has quietly become the backbone of modern AI products. It's what separates a system that 'looks cool in demos' from one that actually works.
When Gemini CLI Feels Like a Junior Engineer With a Checklist
I spent 1.5 hours debugging what should've been a simple Postgres connection issue while using Google's Gemini CLI. Claude solved it in 5 minutes.
The Future of Generative AI Work: 5 Layers That Will Define the Next Decade
Over the next 10 years, the GenAI landscape won't be shaped by prompt hacks or viral demos. It will be defined by who builds the infrastructure, systems, safety nets, and experiences that actually ship and scale.
The Art of Saying No to Helpful AI
I've been building with AI coding agents lately — and they're surprisingly good. But one thing's become clear: you still have to say no. A lot.
Vibe Coding with AI: Loops, Logic, and Learning the Limits
Lately, I've been experimenting with Cursor's AI coding agent and had a pretty fascinating 'vibe coding' session — part exploration, part debugging, part babysitting.
What I'm Learning About Building Real LLM Agents
Over the past few days, I've been exploring how to design intelligent agents using large language models. What started as a simple weather bot turned into a deep dive.
Using Claude for ML: Great at Scaffolding, Rough on Efficiency
I recently used Claude as a coding partner for a project predicting patient appointment show rates. It was impressive in some ways — but frustrating in others.
The Production Reality of LLMs: A Comprehensive Analysis of Use Cases in 2023
A deep dive into how companies are actually using large language models in production, from GitHub Copilot writing 46% of code to enterprises struggling with hallucination rates of 27%
The Great AI Game: Mapping the Players, Power, and Politics of the LLM Revolution
An in-depth analysis of the LLM ecosystem in May 2023, from Geoffrey Hinton's dramatic Google exit to the $50 billion funding frenzy reshaping Silicon Valley's power structure
What are Large Language Models?
This is the first of a multi-part series exploring exciting new developments in AI. A deep dive into the models that power ChatGPT.