Published
Why I built Aloha for agents that build over weeks
Aloha is my spec-driven workflow for Claude Code: it keeps a project's plan in files and git, commits each task, and verifies every phase against its goal rather than its task list.
A working publication
Questions worth
working through.
Current evidence, an operating point of view, and a practical next step.
Showing 12 of 14 pieces
Or ask the library a questionRevised
Who gets the AI assistant first
What Brynjolfsson, Li, and Raymond found when a software firm gave its support agents an AI assistant, and how I would decide who at a small investment firm gets one first and how to watch quality.
Revised
Before a model screens the firm's deal flow
What Maxime Bonelli found about venture firms that adopted data technologies for screening, and how I would decide whether a small investment firm should let a model rank its pipeline.
Revised
Letting a model into the investment decision
What Csaszar, Ketkar, and Kim found when they compared language models with investors at generating and judging startup strategies, and how I would decide where a model belongs in a small investment firm's decision.
Revised
Beyond the model frontier: chips, context, and human judgment
How chip architecture, model progress, context, and human learning affect the useful work a firm can accept and sustain.
Published
Duty of care in the AI transition
What the displacement and mental-health literature says, how people use AI day to day, and who decides what safe output is, framed as a duty of care an operator can act on.
Revised
A practical acceptance review for enterprise AI
A practical pilot with editable comparisons, evidence records, learning exercises, productivity measures, and recovery checks.
Revised
What makes AI-generated work safe to accept?
How I connect chips, models, context, and human understanding to five checks for accepting useful work.
Published
Helping people build capability with AI
How I would use AI coaching, practice, and observable progress to help people explain, adapt, and improve their work.
Published
The turbulent AI era: an operating lens
My reading of Bill Gates’s essay and the questions it raises for technology operations.
Added
When an AI task is actually finished
A completion standard that follows an assistant’s action into the authoritative system.
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Before an AI assistant can access firm data
Following information and authority through a connected assistant before granting access.
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When an AI workflow is ready for production
The task boundaries, evidence, and operating conditions I would test before expanding an AI workflow.
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Measuring the value of an AI workflow
How I would compare accepted work, review effort, rework, and changes in the tasks people attempt.