Why Founder-Led Technical Content Is Working So Well in AI
The technical context founders already have is becoming a distribution advantage.
THE ARCHIVE
All essays.
On AI, engineering, and getting products into people’s hands.
14 essays
Nobody knows which AI model to pick.
GPT-4.1 came after GPT-4.5 and this is where the entire problem starts
How Muse, Instinct, and OpenClaw Work
the stack behind next generation of agents and how they work
AI GTM Is Just Fast Experimentation
Inside the new GTM playbook where pricing, distribution and even the customer can keep changing.
AI Is Saving Time. Why Aren’t Costs Falling?
Employees feel faster. The company’s costs barely move. What happens to all the time AI saves?
The Rise of Engineer-Led Marketing
The strange new jobs appearing between engineering and marketing
AI safety is becoming an ops problem
The model tried to stop. The system kept it running. What happens when an agent’s safeguards fail?
Every attack in Anthropic's threat report ran on the cheaper models
The attackers didn’t have access to the best models. So what made them so effective?
Building a meme generator MCP server from scratch
What changes when Claude can actually use an API? Build a meme generator to see how an MCP server connects conversation to action.
Evaluating naive and hybrid RAG using Weaviate and Athina
Does adding keyword search actually improve your RAG pipeline? Compare retrieved context and generated answers against the same dataset.
Text to SQL without sharing database rows
A model can help query your database without receiving its rows. Here is the schema-only approach, and the tradeoffs that come with it.
13 projects from the generative AI hackathon I organized
A week, new teammates, and a working AI product. Thirteen teams took on problems across language, healthcare, hiring, and everyday life.
Best way to deploy open-source LLM models
Run the model yourself or use a hosted API? The answer depends on what you need to control, and what you can afford to maintain.
Model quantization techniques: use LLMs on your CPU
What if running a language model did not require an expensive GPU? Quantization changes the memory requirements, but the details matter.