Insights
Thoughts on AI, design, and building sovereign software
We Don't Know What We Don't Know
Every AI interaction begins with a human request. The quality of that request is bounded by what that human has been exposed to. This is the most important unsolved problem in AI, and almost nobody is framing it correctly.
What an Agent Can Do with Gerolamo MCP
11 tools, four capability layers, and five ready-made agent configurations. A practical guide to connecting Claude Code, custom agents, or any MCP client to Gerolamo's scored technical intelligence corpus.
Fusing Technical Intelligence to Generate New Alpha
A Gerolamo case study: two unrelated GitHub libraries — one in robotics, one in quantum computing — were discovered, fused in a Workspace, and composed into a technical specification scored 88/100 by an independent LLM. The entire loop took under five minutes.
Gerolamo: Technical Intelligence as Infrastructure for the Agentic Era
Introducing Gerolamo, a technical intelligence platform that scores the open-source landscape on defensibility, frontier risk, and novelty — and serves the results to both human analysts and AI agents via MCP.
The Outcome Leverage Framework
A scoring framework for evaluating what a person can produce end-to-end with current LLM access, how good the result is, and how much value it displaces from prior workflows. 16 dimensions, three scoring layers, one composite score.
The Fourth Signal: Why Observability Now Requires Provenance
OpenTelemetry's new Profiles Alpha completes the performance observability stack. But as autonomous agents take the wheel, understanding performance is no longer enough. We need cryptographic proof of behavior.
Task Compression and Human Advantage Framework
Applied scoring tables across 19 dimensions of disruptability for software engineering and the general economy. 200 tasks scored, ranked, and banded — from prime disruption candidates to strong human moats.
Provable Software: How Zephyr and GLITCHLAB Create a Cryptographically Verifiable AI Development Pipeline
GLITCHLAB's autonomous engineering engine combined with Zephyr's cryptographic provenance layer forms a provable pipeline for AI-driven software development through signed Software Bills of Function.
Announcing GLITCHLAB: The Local-First Agentic Engineering Engine
Bridging the gap between engineering decisions and pull requests. Meet our deterministic orchestration system for autonomous, local-first software engineering.
AI Assurance Is Not a Policy Problem
Why governing AI requires evidence, not promises, and how assurance emerges from execution rather than intent.
The Democratization of Knowledge and the Persistent Scarcity of Judgment
An examination of how modern knowledge work has shifted from information acquisition to context management, why judgment remains the limiting factor in complex systems, and how artificial intelligence functions most effectively as supporting infrastructure.
Show, Don't Tell: How Rapid Prototyping Transforms B2B Sales
Traditional sales cycles rely on past performance and PowerPoint decks. Modern buyers need working demonstrations in realistic environments. Here's how rapid prototyping creates tangible proof of capability that accelerates deal cycles and increases win rates.
Overcoming Habit Inertia in Generative AI Adoption
A comprehensive framework for accelerating AI adoption through micro-interventions, social amplification, and system integration—moving organizations beyond the demonstration phase.
The Software Bill of Function: A New Paradigm for Software Transparency
Introducing a behavioral inventory framework that captures what software actually does, enabling functional transparency and operational trust in critical systems.
How AI is Reshaping Customer and Employee Experience at Adjective
Exploring how unified intelligence, RAG systems, and conversational data create a virtuous cycle of continuous improvement across the entire organization.
The Human Symphony: Our Guide to Thriving in the AI Era
A comprehensive guide to workforce transformation through AI adoption, structured as a four-stage journey from awareness to leadership.
Leveraging User Experience to Enhance Model Training
How product design skills and user persona development create higher-quality machine learning models through human-centered AI development.
Customer Experience is Everywhere, Literally
How customer-obsessed principles and design thinking transformed counter-insurgency operations in Afghanistan—and can revolutionize any industry, including defense.