May 7, 2026
The Economics of Abracapocus
Why governed execution will matter as AI execution costs become explicit and inference stops being treated as free.
Read insight →Insights
Writing on architecture, AI execution systems, and dependable delivery.
nSpace Insights
May 6, 2026
Abracapocus Building Abracapocus
Abracapocus is being developed through the same governed autonomous execution model it proposes for production software systems.
Read insight →May 6, 2026
Beyond the Dark Software Factory
Dan Shapiro’s Five Levels describe the path toward the dark software factory. Abracapocus points toward the governed software factory beyond it.
Read insight →May 6, 2026
From the Karpathy Loop to Governed Autonomous Development
AI coding is moving from conversational iteration to governed execution through contracts, verification, evidence, and bounded autonomous delivery systems.
Read insight →Dependable AI-Assisted Development Series
External article series from foxmike.github.io.
AI-Assisted Development Scales Through Verification, Not Generation
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The Unreliable Narrator Problem in AI-Assisted Development
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Stage Separation: Why Software Construction Needs a Supervisor Pattern
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Task Contracts as the Unit of Work in AI-Assisted Development
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Multi-Backend Routing Is Insurance Against Model Risk
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Tiered Retry Is a Failure Economy
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Minimal Blast Radius Is What Makes AI Automation Tolerable
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Curated Task Execution Beats Dynamic Planning in Real Work
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Anti-Patterns in AI-Assisted Development
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State, Resumability, and Why Chat Memory Is the Wrong Primitive
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External Notes
Older external notes on applied AI and data workflows.
CNN for Image Classification
Why it matters: demonstrates how robust image pipelines can classify operational inputs consistently and support faster downstream decisions.
Read on Medium →Extracting Structured Data from Images with GPT-4 Vision + Instructor
Why it matters: shows a practical method for converting visual documents into structured, machine-usable data with controlled output formats.
Read on Medium →Sharing Data with Large Language Models
Why it matters: explains how to share business data with language models while preserving context, controls, and decision quality.
Read on Medium →