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We have been discussing document, test, and release-driven development (doing these things first before implementing features).
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Building on TDPD and RDPD, Document-driven product development (DDPD) offers another perspective.
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Yesterday we talked about Test-Driven Product Development.
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We’re familiar with TDD (test-driven development) in the software world.
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I recall a quote from the book The Soul of a New Machine that describes “Mushroom Management” and goes something like this: “Keep them in the dark, feed them sh**, and watch them grow.”
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How do we look at a product release?
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Git + Git hosting platforms enable both local and cloud-based workflows.
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Some people are wildly successful without writing.
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There are three levels of workflow: Personal (what you do to get things done) Department/Discipline (How multiple people who do the same thing get things done – Example: PCB design) Cross-functional (How people who do different jobs interact - Example: En…
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I wrote my first Claude plugin that packages up some commands that I use in about every project I work on.
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We live in a world of powerful tools.
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Do you deploy 10’s to 1000’s of devices and need to quickly identify them in the field for configuration, maintenance, or troubleshooting?
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Product is what you build.
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An intense discussion about part/version numbers driving application logic surfaced an idea to create a simplified version of the product metadata that simplified the programming logic.
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As scale increases (# of people, # of technologies, # of products, # of teams, life cycle of product, experience, amount of knowledge, etc.), what does the value produced look like?
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In the last couple decades, we’ve observed the success of SaaS web applications (Google Docs, Salesforce, Basecamp, Trello, etc.).
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Recently, effective communication has been discussed.
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In conversation, I find myself saying: “what is the context of your comment?”
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Lessons from AI-coding a 10,000 line app BRun is getting usable.
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Less code is not the ultimate goal Consider the following byte to binary C program: int main(int b,char**i){long long n=B,a=I^n,r=(a/b&a)>>4,y=atoi(*++i),_=(((a^n/b)*(y>>T)| y>>S)&r)|(a^r);printf("%.8s\n",(char*)&_);} Unless you are trying to win the Int…
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Yesterday, we discussed aligning the happy path in code.
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An idiom that I learned in the Go community is to align the happy path.
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An effective process, team, or organization should be able to continue on if any individual steps away for a bit, or forever.
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Not using new tech when applicable.
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Finding and leveraging existing technology.
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Technical debt is like any other kind of debt – it accrues when nothing is done.
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Design files (mechanical, electrical, or software) contain the technical details that allow us to manufacture something in the moment, but they often don’t contain the “why”.
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A wise developer once said: Code is a liability, not an asset.
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YAGNI - “You ain’t gonna need it!”
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Kernighan’s Law: Debugging is twice as hard as writing the code in the first place.
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My wife makes sourdough, which is a multi-day process and at times unpredictable.
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There is an ongoing shift in data analysis tools.
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AI is really good at updating documentation after implementation.
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I find it works best to keep documentation as close to the code or design files as possible.
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Be kind to others (and your future self) and document why you did something.
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What are some ways we can close the loop in engineering efforts?
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Rod’s thoughts on Riding a Bike are thought provoking. … A decision that might be bad.
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What are some ways we as humans can close the loop?
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Closed loop systems are stable.
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There is a fascinating statement in a recent MIT study that claims 95% of organizations are getting zero return from GenAI investments.
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AI is not free, as there are significant costs associated with training and hosting modern AI models.
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Product Data Management (PDM) is how you manage and publish your product data.
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Git, which was created 20 years, and various hosting platforms, has revolutionized software development workflow and collaboration.
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The thing you get with Git* is a sane way to manage files: organization (team/repo/directories) documentation (excellent support for Markdown) efficient navigation (links in READMEs and other markdown files) history (who changed what when) collaboration (…
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There is this movement against files in most disciplines.
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Starting with good documentation is often a better way to use AI.
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There are two ways to use AI: Start with a vague prompt and keep prompting until we get the result we want.
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With Claude Code (and likely many other AI technologies), anyone can write scripts now.
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Sketching is kind of like writing cursive—it engages a dynamic in our brains that inspires creativity.
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We’ve already explored 4 modes of communication (audio, written, images, video).