Articles
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Two Engineers. One Year. More Output Than Ten.
Executive Deck ↗Exec summary ↗Listen ↗Nathan joined a scale-up as CTO with a mandate to hire ten engineers. He hired zero. Twelve months later, he and one existing associate engineer had decomposed the monolith, automated deployments, and outshipped the original plan.
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The 2028 Problem You’re Creating in 2025
Executive Deck ↗Exec summary ↗Listen ↗Your 2025 AI decisions shape your 2028 reality. Learn why waiting for clarity is the riskiest strategy and how to build for capabilities that don’t exist yet.
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If You Want to Measure Macro Results, Answer These 3 Questions Before AI Touches Your SDLC
Executive Deck ↗Exec summary ↗Listen ↗Measure AI impact at the macro level by answering three critical questions before implementation: what you’re solving, how you’ll measure it, and who owns results.
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Waste Density vs Value Density: Managing the Emotions of Your Board with Real Economics
Executive Deck ↗Exec summary ↗Listen ↗Learn to communicate AI value to your board using waste density vs. value density. Move beyond emotional arguments to real economics.
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Hello New CTO : Your Loan Engine Cost More than Giving Billionaires Free Cars
Executive Deck ↗Exec summary ↗Listen ↗New CTO reality check: Your legacy systems cost more than you think. A frank analysis of technical debt and the business case for AI modernization.
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The Bottlenecked CEO: You Don’t Need New Metrics to Quantify AI Value. You Need the Courage to Eliminate the Silos That Make Measurement Impossible.
Executive Deck ↗Exec summary ↗Listen ↗A CEO watches a startup take 10 percent of his market in 8 months. The problem is not metrics. It is the silos that make measuring AI value impossible. A story about organizational courage.
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Your AI Investment Is Failing. Here’s Why.
Executive Deck ↗Exec summary ↗Listen ↗Most enterprise AI investments are failing. Here’s the real reason: you’re measuring tools, not outcomes. Learn how to fix your approach.
Essential or Ornamental
Three companies. Three choices. One satisfactory ending.
One does nothing. One maps the waste. One bets everything on twelve people in a warehouse.
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