We are living in the age of the specialized tool. Your phone’s assistant, your car’s navigation, the generative AI that drafts this very blog post—they are all brilliant, but they are also profoundly, beautifully limited. They are experts in their domain, a million-dollar drill that can’t hammer a nail. This is the era of Artificial […]
The Monolith and the Multiverse: Why AGI Is the Only Future That Matters Read More »
Running a large language model (LLM) locally offers serious advantages: privacy, speed, offline capabilities, and cost control. Wrap that in Docker, and you’ve got a clean, portable setup ready for production or local R&D. Here’s how to build a local LLM inside a Docker container without rage-quitting or sacrificing GPU horsepower. Step 1: Pick Your
How to Build a Local LLM in Docker: A Fast-Track Guide for AI Engineers Read More »
We’ve all heard it: “First, define the problem.” While sound in theory, in practice this mindset can trap organizations in endless loops of analysis, meetings, and slide decks. But the most transformative strategies—especially in AI and tech—begin not with whiteboarding the problem, but with building something. Anything. A prototype, a hypothesis, a system that forces
Building the Solution Is the First Step in Solving the Problem Read More »
