Market for Exhaustion: The Strategic Risk of Using AI Without Data Governance
The ‘Market for Exhaustion’ explains why companies withhold valuable knowledge and feed AI with generic data instead. Understand the paradox and how to reverse this logic.
AI
Memory, small models, and how to validate any of it
The last article in the series on building Bloom in a week: how to give an agent long-term memory without a vector database, what actually changes when you switch to smaller local models, and how to validate changes in a probabilistic system with evidence, not gut feeling.
The prompt before the architecture
Third article in the series on building Bloom in a week: why most of the perceived rigidity in a multi-agent agent comes from the prompt layer, not the architecture, and how to hard-code behavioral safety invariants.
Making the loop act without losing control
Second article in the series on building Bloom in a week: how to give an agent real freedom to act in the world — writing real events into Google Calendar via MCP — without giving up control over when and how it acts.
Who decides: the code or the model?
First article in a series on building Bloom-for-Learning in one week: why the most important decision in any agentic system is deliberately defining what belongs to deterministic code and what belongs to the model’s judgment.