The End of Subsidized AI
The subsidy era is ending. The intelligence era is beginning. Mike Molinet & Govind Kavaturi break down what Claude dropping token subscriptions and Anthropic's Mythos model mean for every builder's margins and strategy.
Eleven volumes in. One thesis per week, explored fully. No roundups, no trend reports, no AI hype. Each volume is one idea that changes how you think about building.
The latest from each corner.
Who is an AI builder?
A person who works with AI to produce quality, scalable output that helps humans or other agents get something done. This is the definitional pillar anchor for what AI building means, who becomes an AI builder, and why the category is the new organizing unit of work.
Latest from across the publication
Build a research agent team where one agent finds, one verifies, one summarizes
Three specialized agents working in sequence produce verified research in five minutes; one generalist agent doing all three jobs takes twenty minutes and produces ungrounded claims.
Constrain agent tool access with per-task allowlists
An agent with fifty tools available picks the wrong one twelve percent of the time; an agent with five tools scoped to its current task picks correctly ninety-nine percent of the time.
Who is an AI builder?
A person who works with AI to produce quality, scalable output that helps humans or other agents get something done. This is the definitional pillar anchor for what AI building means, who becomes an AI builder, and why the category is the new organizing unit of work.
Anthropic API
Claude models (Sonnet, Opus, Haiku) via REST API with native tool-use, extended thinking, and MCP support.
The End of Subsidized AI
The subsidy era is ending. The intelligence era is beginning. Mike Molinet & Govind Kavaturi break down what Claude dropping token subscriptions and Anthropic's Mythos model mean for every builder's margins and strategy.
Three pillars. Everything belongs to one.
Building
The craft pillar.
What it means to build with AI, who builds, and how the work is shaped. The practical craft of operating as an AI builder — techniques, patterns, and the lived experience of shipping with AI.
Economics
The market pillar.
How the AI-native economy works, who makes money, where value accrues, and how business models are shifting. Market dynamics, business models, and the economics of building with AI at every scale.
Trust
The discipline pillar.
Verification, accountability, and how humans and agents establish trust in AI output. The operational discipline of making AI systems reliable, auditable, and worth relying on.
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