At 66, I have accumulated more information, experience, opinions, records, questions, and unfinished lines of inquiry than I can reliably hold in my head. Some came from building companies and software systems. Some came from investing, civic work, travel, family history, personal measurement, and the ordinary consequences of making decisions. Much of it remains scattered across documents, presentations, notes, conversations, and memories.
I don't want to merely preserve that accumulation. I want to test it.
I want to turn it into something more useful: a public, revisable account of how I think the world works, why I think it works that way, and what could persuade me to think differently. I am writing primarily for myself, writing what I’d want to read, even though anyone may read it. The work succeeds when it improves my understanding, survives serious scrutiny, remains useful over time, and occasionally helps someone else make a better decision.
That is what I mean by A Working Model.
The problem with an invisible worldview
Everyone carries some model of how the world works. It influences whom we trust, which risks we fear, what evidence we accept, how far ahead we look, and which consequences we notice. The model may be coherent or contradictory, explicit or mostly unconscious. Either way, it affects our decisions.
Mine does too. I have strong views about artificial intelligence, privacy, work, education, leadership, technology, public policy, measurement, service, and many other subjects. Those views grew out of different periods of my life and different kinds of evidence. Some have endured years of experience. Others may be artifacts of a particular event, an outdated assumption, selective memory, or an explanation that once sounded persuasive and was never adequately tested.
Leaving all of that implicit is easy. It is also a poor way to discover contradictions, weak evidence, and ideas that have quietly outlived their usefulness. If I want to understand how the world works, I need to make my current model visible enough to inspect.
The short answer: make the model explicit and keep it revisable
The approach has five parts:
1. Begin with questions consequential enough to investigate repeatedly, even without external reward or approval.
2. Combine evidence, lived experience, and first-principles reasoning without confusing their different roles.
3. Test conclusions against serious counterarguments, alternative explanations, and evidence that could change them.
4. Publish each result as a canonical living article that can be corrected, expanded, linked, and reconsidered over time.
5. Judge the work by whether it sharpens understanding and improves decisions, with audience size treated as a secondary signal.
While the structure sounds orderly, the material feeding it will not be. Curiosity rarely follows an editorial calendar.
Unsatisfied curiosity supplies the energy
My unsatisfied curiosity has guided much of my life. One question leads to another, and an answer often becomes interesting precisely where it stops being adequate. I may begin with a headline, a personal experience, a number that seems wrong, a confident public claim, an old family record, or a technology that people are either celebrating or fearing. The recurring impulse is the same: What is really happening here? My consistent finding is that the world is complex and nuanced.
The breadth of those questions could make this publication look unfocused. I see a different organizing principle. Coherence doesn't require every article to fit the same content category. It can come from repeatedly applying the same interpretive method across different subjects.
That method looks for hidden assumptions, incentives, baselines, denominators, time horizons, system boundaries, and second- and third-order effects. It asks whether a theoretical capability has become practical adoption, whether an announced plan produced an observed outcome, and whether an anecdote illustrates a mechanism or merely tells a memorable story. It also asks the practical question that analysis sometimes avoids: If the better explanation is true, how should my thinking change?
Curiosity generates the questions, but it cannot settle them. Experience and evidence do that work.
Experience supplies friction, not proof
A long life creates a large collection of inputs. I have spent decades building software, starting and advising businesses, working with people around the world, investing, speaking, serving community organizations, raising a family, traveling, collecting things, recording measurements, and pursuing questions with no apparent commercial purpose. Responsibility, failure, prolonged exposure, and consequences have forced me to reconsider explanations that once seemed complete.
Those experiences matter because they can reveal variables that an abstract account overlooks. They can expose the distance between policy and implementation, capability and adoption, intention and outcome, or public rhetoric and actual behavior. They also create biases of their own. One vivid experience can dominate memory. Professional success in one setting can create false confidence in another. A personal story can illuminate a general problem without proving a general conclusion.
I will insert personal experience in these articles when it establishes the stakes, generates the question, or makes an important mechanism visible. It should appear as evidence about what I experienced, with corroboration and uncertainty handled honestly. Research, analysis, counterarguments, and practical consequences must carry the broader argument.
Once experience is treated as an input rather than a verdict, writing becomes the mechanism that forces the other inputs into contact.
Writing turns impressions into claims
An idea can feel persuasive while it remains in my head because its gaps are easy to glide past. Writing removes some of that freedom. Terms need definitions. Comparisons need baselines. Numbers need denominators and dates. Causes must be separated from correlations, chronology, and plausibility. A conclusion needs enough structure that someone else could identify where the reasoning fails.
Thorough research matters, but accumulating sources is not the same as understanding a subject. Sources can repeat one another, omit the same variables, use different definitions, or report facts that do not establish the conclusions attached to them. Expertise deserves serious weight, especially because no individual can directly observe more than an immeasurably small fraction of the world. It still needs provenance, context, and an examination of what the evidence actually supports.
The goal is neither artificial neutrality nor permanent skepticism. I expect to reach conclusions, oftentimes strong ones. The discipline lies in distinguishing documented fact, personal recollection, inference, forecast, and value judgment, then matching confidence to evidence. A working model becomes useful only when it is clear enough to guide a decision and open enough to absorb a correction.
That openness makes disagreement part of the machinery, not an interruption.
Disagreement is a test, not an audience strategy
I do not want to write what merely restates what everyone already believes. I’m looking for contentment, not comfort. For me, contentment comes from continuing to engage with the world, test my assumptions, and understand more of how it works. Agreement can be comforting, but it is a poor substitute for examination. The strongest opposing argument may reveal a constraint I ignored, a cost I understated, or a boundary beyond which my explanation stops working.
Taking counterarguments seriously does not require treating every position as equally supported. It requires presenting the strongest reasonable case, identifying what it explains, and showing where its explanatory power ends. It also requires saying what evidence would materially change my conclusion. If nothing could change it, I am defending an identity rather than investigating a question.
Private reflection and public claims create different kinds of pressure. This is one reason I plan to keep public comments closed. Anyone who wants to respond can write to me directly, and useful criticism can improve the work. I have little interest in providing another stage for people to perform for one another. The purpose is better thinking, not maximum engagement.
Publication creates useful accountability
I am writing for myself, but publishing imposes discipline. It requires me to make the argument understandable, support consequential claims, acknowledge uncertainty, and take responsibility for the result. It also gives other people a chance to identify errors and perspectives I missed.
Popularity is not the governing objective. A large audience could be gratifying and useful, but it could also reward speed, certainty, outrage, and repetition. I would rather build a body of work in which curiosity supplies the energy, experience-tested knowledge supplies credibility, and practical usefulness supplies relevance. If those qualities compound into an audience, that is fine, but they remain worth pursuing even if they don't.
Publication also turns scattered articles into a connected system. A paper about artificial intelligence may change a paper about education. New evidence about privacy may alter a cybersecurity conclusion. A personal memory may illuminate a leadership argument written months earlier. As the body of work grows, the connections may become more important than the sequence in which the pieces appeared.
Those connections are also why the articles cannot be treated as finished objects.
The published version remains a working version
Each article will have one canonical public location. When evidence or reasoning changes, I will revise that article rather than publish competing versions and leave readers to determine which one I still believe. The page will show its original publication date and latest substantive revision date, and detailed notes will explain material corrections, expanded evidence, changed reasoning, altered conclusions, and meaningful new links.
Earlier states will remain recoverable internally. Publicly, the latest version should represent my best current understanding.
This approach carries a risk. Revisability can become an excuse to avoid commitment or endlessly polish work that should be released. The answer is to state the current conclusion clearly, identify material uncertainty, publish when the evidence is proportional to the claim, and revise when something important changes. A working model should remain capable of movement without becoming incapable of decision.
Over time, I expect substantial overlap will reduce the number of genuinely separate articles. New material may strengthen an existing paper, expose a contradiction, or connect several topics through a common concept. That convergence is useful. It may eventually create the structure for one or more books, although writing a book is not an overriding goal. The first obligation is to keep improving the model.
Artificial intelligence is part of the method
I write in collaboration with artificial intelligence. A stigma still surrounds acknowledging that assistance, just as working from home and using offshore software developers once attracted suspicion that later became routinely acceptable.
Artificial intelligence can challenge a categorical statement, identify a missing distinction, find counterarguments, organize evidence, and point out when my memory does not match the documented record. It can also be confidently wrong, accept a bad premise, flatten a distinctive voice, or generate a citation that does not support the claim. Its usefulness depends on how I direct, test, and review it.
My standing disclosure is straightforward:
I write in collaboration with artificial intelligence, using it as a research, analytical, and editorial partner. It helps me investigate claims, correct memory, identify counterarguments, organize evidence, and improve the writing. I retain judgment, conclusions, and responsibility for everything published here.
This collaboration lets the project scale without transferring accountability. I choose the questions, supply experience and judgment, decide what I believe, review the evidence, and approve every published version.
What I hope to build
The result will range widely because my curiosity does. Technology, work, institutions, public policy, health, measurement, history, genealogy, leadership, faith, culture, travel, service, family, and the experience of a long life all belong here when they help answer a consequential question.
Together, the articles should form a detailed, connected, and current definition of my worldview. They should also preserve the memories and experiences that explain how parts of that worldview developed, creating raw material for a more personal history without turning every article into an autobiography.
I am less interested in preserving a monument to what I once believed than in building a system that keeps asking whether I should still believe it. The work begins with unsatisfied curiosity, gains discipline through evidence and writing, and remains useful by staying open to revision.
That is the model I intend to keep working.
Questions, corrections, or disagreements are welcome. You can reach me directly at dave@aworkingmodel.com.