Optimized for Yesterday: Why Organizations Slow Down When Execution Becomes Abundant
Language: English
Published by Project Intent, 2026
- Softcover
- New
Seller: California Books, Miami, FL, U.S.A.California Books
AbeBooks seller since October 27, 2023
Condition: New
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- Title
- Optimized for Yesterday: Why Organizations Slow Down When Execution Becomes Abundant
- Author
- Florschuetz, Alan
- Publisher
- Project Intent
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798997125905
AI changed the economics of execution. Most organizations are still operating as if it didn’t.
For decades, large organizations were designed around a rational assumption: execution was expensive.
Software took teams of specialists to build. Infrastructure was scarce. Mistakes were costly. So companies learned to plan carefully, coordinate broadly, estimate extensively, and require layers of approval before committing resources.
Those structures worked.
Then the scarcity moved.
Today, one capable person working with AI can increasingly produce in days what once required a team for weeks or months. But the organization surrounding that work may still require the same planning cycles, status meetings, review boards, funding gates, and approval chains.
The result is a strange new reality: execution gets faster while organizations get slower.
In Optimized for Yesterday, Alan Florschuetz examines the hidden forces behind that contradiction and introduces a new vocabulary for understanding them:
Decision Latency — the time an organization spends waiting after it already knows enough to learn.
The Coordination Tax — the capacity consumed simply keeping fragmented parts of the organization aligned.
The Cost of Certainty — why the pursuit of predictive confidence can delay the evidence that would answer the question.
Bounded Governance — how organizations can preserve safety without placing human permission in every execution path.
Capacity Funding — why funding stable capability can be more adaptive than funding long-range predictions.
This is not a book about AI tools, prompt engineering, or replacing people with machines.
It is a book about what happens to leadership, governance, funding, architecture, and organizational design when execution is no longer the scarce resource.
The central idea is simple:
Planning produces predictions. Execution produces evidence.
The organizations that thrive in the age of abundant intelligence will not necessarily be the ones with the most AI.
They will be the ones that shorten the distance between intent and evidence—and learn faster than everyone else.
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