LeeBrown

Tech companies promise AI will take away all the boring chores. But the boring chores are how beginners learn to become experts. What happens when the easy work disappears, and why real experience cannot be automated.

When OpenAI showcased Astra building 3D scenes in Blender via MCP, commentators declared 3D artists finished. Anyone working in production saw the catch immediately. Why the demo was marketing theatre, and what it reveals about the limits of generic AI.

The case for Python and JavaScript was always developer time. Agents made typing free, which quietly removed the argument and left a stricter language holding something more valuable.

If your plan for agentic coding is to read every line, you have traded a speed gain for a queue with you in it. The work that scales is building the walls, not standing in front of them.

The machine that writes half my code is not on a path to waking up, and that was the design brief. Why the replacement question never made sense, and what near-free development does to off-the-shelf software.

The economic argument for waterfall was always that being wrong in code costs 100x being wrong on paper. Agentic coding flattens that curve. What replaces the premise, and what gets harder instead.