I love that I live in a world that has marmalade. I'm not particularly a fan of it myself. I generally don't turn to jams and jellys but in the rare times I do, I usually enjoy a berry variety. Triple berry is my favorite. And yet, while I don't like eating marmalade, it occupies a place in my heart that's more special than any triple berry jam could ever. I like marmalade not because I like it, but because other people do. This odd fact leads me to thinking a lot about marmalade. I probably think more about marmalade than the people who like it. Marmalade is so decidedly different from all the other jams that, I honestly don't even know if it qualifies as a "jam." It's not called orange jam, it's not orange jelly. Marmalade is so confident, so self-assured, that it offers know hint at all about what it is. Those who know, know and, it seems, most people actually happen to know. I don't just think about its name. I think about how i...

It's time to reveal that, for the past 10 years, every September 7th, I have been making the same "6 Degrees of Kevin Bacon" joke, and no one has caught on... For the record, I found it pretty funny. It's like a retrospective of the last 10 years of the internet...

  If you've ever built a feature, designed a user experience, created a logo, gotten finicky about a color scheme, or argued the merits of a specific font, you've made an intentional choice. The only thing I love more about intentional design is hearing about intentional design. It's great knowing choices weren't haphazard, and (whether or not you agree with those choices) it's delightful to understand the reasons behind those choices. There are stories behind the things we build, and I don't think we surface those often enough. Those stories are mostly known by the builders, which is a bit sad. Just like I'm happy to listen to 13 different takes of my favorite Beatles song (that's a lie, everyone knows it's impossible to have a favorite Beatles song), it's nice to learn about the decisions. Beyond the usability tests, the aggregated feedback, the A/B analysis, there was still some creative intention, some artistry. I was pleasantly reminded abou...

  It was the best of interviews, it was the worst of interviews. It was a measure of wisdom, it was a measure of foolishness. 20 years ago I was on the hunt for my next role as a Software Engineer. I was interviewing at two places: a small exciting start up of 10 people, and a large corporation you've mostly definitely have heard of. It was the final round of interviews for both roles. The start up hit me with a riddle: How do you retrieve a package on an island that's too small to build a runway? I thought out loud, I asked elaborating questions, I shared my assumptions. Can I inquire how the package wound up on the island if it's so hard to reach?  Irrelevant. Is money a constraint? No. Can I use a boat?  No, the island is surrounded by rocks. Can I use a helicopter?  No, winds are unsafe for helicopters. Are planes are not an option then, given the problem mentioned a runway?  No, planes are fine. We went back and forth like this for some time, until I felt I...

That feeling when you increase your NPCs by 10x, and watch them randomly navigate your largest map with A*, and there is no FPS dip. Here's to Saturday projects. I can't wait to share more details (but I need to, not far enough along yet). 

  PSA: Stop (just) posting on LinkedIn. LinkedIn is a great way of building an audience, a network, professional connections. And it's a path for establishing yourself a thought leader. BUT: as with most social networks, the relevancy algorithm is dominated by a timestamp. That's great when you're talking about short-lived topics but not when you're making macro observations, discussing careers, strategies, growth, trends. That astute observation you made 3 weeks ago is no less astute today. But yet social networks will deem it less relevant. The post you made 5 years ago? It will never appear in an anyone's feed (even if there's a sudden spike in interest in the very same topic). If you're creating content, then you should own and manage your content. It will have a far broader reach than you can ever predict, and it will give you insights into what people are looking for beyond  LinkedIn. Case in point: a blog post I wrote 20 years ago about MySpace of a...

Here's a thought experiment: Imagine you've built a product. It's great in all the right ways. It solves real problems. It's high quality. It's priced perfectly. It scales with ease. And, it so happens, the product has no UI. No experience to manage, no layouts to think through, no color schemes to worry about. It's entirely an API serving as the backbone to many end-customers. Without a user interface, what do your consumers and customers know about you? How do you build trust, loyalty? How do you build your brand? Let's pretend it's the 90s again. Surfing the World Wide Web means starting with any number of search engines. You're building a new approach for indexing pages. You tell your friends about it and are met with "Sounds cool, but does the world really need another search engine?" And so you decide, rather than purchase that Googol domain you've been considering, you'll instead use your engine to power the more established ...

  It has come to my attention that some of you have completely misunderstood what I'm refering to when I advocate for the use of A.I. You can code amazing things with A.I. ... Building strategic visions with A.I. with clear milestones that scale ... You can even get creative with A.I. and write amazing stories, create silly images, funny videos, or even build beautiful PPTs with A.I. I wouldn't trust A.I. for legal advice, or healthcare advice though (unless you think chocolate chip cookies are a cureall which, apparently, A.I. does...)

There was a time when, despite knowing how to code, I had no idea what XML was. That may seem an odd and embarrassing admission until you realize there was a time when XML was new. (In fact, HTML predates XML by several years...) Not knowing XML and, wanting to store data, I came up with a simple system that didn't look too different: I used square brackets and instead of closing slash, I just wrote the word END. I didn't realize I was reinventing the wheel until a much more seasoned engineer saw my code and asked "Why don't you just use XML?" (Which I promptly looked up and made a terrible non-face-saving excuse to save face). My early career was filled with similar examples: hacking a workaround to related database rows until I learned about how to set up proper database relationships, implementing weird architecture until I learned about different patterns like the factory pattern... But over time I learned more and more until I got better at looking out for th...

An interesting biproduct of using AI to build apps is that when costs are obscured we can slide down the slippery slope of requirements shifting-right. We experiment more (which is great) but there's more waste if we stop weighing the cost & benefits. Before: "I don't like that all the buttons are flat buttons with no glowing effect when the user hovers over the button. Can we change that?" "We can... but we have a lot of buttons and different kinds of buttons. Even if we make a pattern to repeat over and over, we have to go through the entire app and make sure all the buttons adopt this pattern. It'll take about 3 weeks, and we'll have to prioritize against the major feature we've been focused on..." "Well... let's hold off for now and do it as part of a full facelift..." After: "Claude, make the buttons green." "Actually, instead of buttons - what if they were little icons. Draw out some icons for each of the bu...

One critically valuable skill for anyone working with an AI coding agents is Computational Thinking. Whether you're a Software Engineer grappling with the fears of eroded job security, a Product Manager shifting to an "AI-first" mindset, or someone just trying to reconcile the dissonance between what people are claiming to achieve with AI and your own results, much of it boils down to Computational Thinking. It's a skill that will become more and more important as AI takes on more and more of the repetitive pattern-based tasks, quality continues to rise and costs reduce.  Computational Thinking is about understanding how a computer would solve a problem. It's about breaking things down into small, repeatable steps that have simple inputs and outputs and knowing how to order and arrange those steps to get the results you want. Whether it's AI, a Rube Goldberg machine, or helping your child with a multiplication problem, it's not enough to only have a clear ...

If there's one AI article you read today, make sure it's this one: https://www.forbes.com/sites/jasonwingard/2026/04/23/vibe-coding-will-break-your-company This isn't an anti-AI or AI-is-terrible take. This is a real & grounded take on the very real problem that AI is allowing us to move faster that the decision-time is compressed. Over the course of my career, I learned that the shift towards "seniority" isn't just that you have more of the core skills and are faster and better. It's that you become wiser about when to use those skills. You ask fundamental questions like: What new problems do we create by solving this? If we build this, who will maintain it? If we build this, will this distract us from our priorities? If we build this will we set some new expectations that we'll have to uphold? Just because something has value doesn't mean it doesn't create a form of debt in the long run. And these were all important to consider before  G...

There's a scene from the movie Big, I always think back to: Tom Hanks' character is sitting in his first big important meeting about a new toy launch, and he stops everyone in their tracks by saying "I don't get it... what's fun about playing with a building?" His question isn't meant to be antagonistic. It's honest, it's earnest, and (most importantly) it gets right to the point. One of the challenges we run into in our adult corporate lives is leaning so heavily on politeness that we introduce ambiguity ("we" should get this done...), and we combat that ambiguity with frameworks (OKRs, KPIs, SMART goals, etc.) But sometimes, we need a bit of Tom Hanks in the mix. That's the power of the Rude Q&A - a document that captures all the blunt, direct, and even rude questions. It's great for after the ideation, research, analysis, refinements and iterations. It challenges, stress-tests, detects contradictions, revalidates assumption...

I'm starting to think generative AI is a proxy for revealing skills gaps. Regardless of field, if you are a high performing, critical thinking, strategic and effective individual then AI is a time saving augmentor of your existing capabilities. Your high degree of skill lets you use AI tactically. You quickly iterate with prompts, better orchestrate, evaluate outputs, and immediately identify when you've been received a quality output. Alternatively, you will quickly revert to the traditional non-AI way of doing things if needed while offloading the more discreet and deterministic tasks to AI. And all that is great... If you're great at what you do. On the flip side, AI has also allowed for us all to easily fake that we are skilled in areas where we've not spent any time honing our craft. To our untrained eye, AI has given us passable-quality outputs that are in need of a trained eye to call out the risks, challenges, issues, or problems. At best, despite our lack of sk...

When I was a software engineer, I strengthened my delivery by also asking product questions. When I turned product manager, I strenghtened my delivery by also asking engineering questions. There's plenty to suggest that AI is blending the roles - but I want to propose an alternative theory: Software Engineering doesn't go away, Product Management doesn't go away. Instead, AI helps us fill the gaps in our individual perspectives so we can better engage with one another. It's not a replacement, but an enhancer. Whether PMs, Engineers, Designers, Operations, Marketing, or Millennials grappling with no longer being responsible for defining what is cool, and navigating a changing landscape of hip new vocabulary and memes (seriously, who references The Office anymore???), AI can be pretty handy for bridging divides. Said differently, AI helps you be "low-key goated, but only if your vibe check passes and your intentions aren’t sus."

You're walking in the forest and come upon a bridge. A mysteriously cloaked figure jumps out holding two envelopes. "Each of these envelopes contains a different number. You may pick either envelope. I will only let you cross if you can tell me whether the number in the envelope you pick is larger or smaller than mine"  Despite being put off by the disruption, you take an envelope and ask: "Can I look inside my envelope before making my guess?" The cloaked figure is surprised because, until now, everyone has ignored him and his envelopes. After some consideration, he says: "Sure." You open the envelope, thinking: "I don't even know how large a range he's picking from. This is a total 50/50..." OR. IS. IT?? What I love most about the solution is it doesn't come from gimmicks, hacks, or any external information. It is, in its purest form, a strategic decision framework. You magically improve your odds with something equally random....

I've been coding pretty intently on something in my off hours (I'm excited to share more once it takes shape). Like the carpenters I watch on YouTube working almost exclusively with hand tools, this is very much a labor of love, so I'm being very deliberate with when, where and why I use AI. I've very sparingly offloaded the soulless, non-creative, non-gratifying code to Claude in the same way the carpenters I watch will occasionally use a power drill when they need 32 precise holes. What I haven't accounted for was, as I've been working on this, my daughter taking a keen interest in watching me code. She's enjoyed watching me iterate, refine, expand - and she's asked with a lot of curiosity about design-thinking that goes into building something from the ground up - or, more precisely, as things have gone from generic to specific. To simplify the principles, I related things to grammar: Describing our weekend to a friend we can quickly and succinctly en...

I'm afraid we're losing our fingerprints. I love using, experimenting and making myself more efficient with AI. And I love being creative with AI - but only where AI is in the early stages of creativity, part of the brainstorming, refinement, and iterations. The final result, I try to make fully my own. (Admittedly, in the early and still novel days, I was regularly generating images and just using them as-is but this was before developing a more discerning eye for AI. Since then, I use AI as a launching pad not as the final product.) What worries me though, is how much I'm seeing AI get used right out of the box in our everyday lives. Posters on community bulletin boards. Homework assignments from elementary schools. User groups promoting meet ups.  What used to be a rich tapestry of people's individual tastes - from the poorly designed posters with clashing colors and excessive use of Comic Sans, to hand-drawn photocopies, to really well made amateur designs - is now ...

I've been writing some form of my blog for more than 25 years now - I think I started before it was even called 'blogging.' I'm that old. In 2026, when you have that much writing readily available on the internet, there's really only one thing left to do: Feed it to your favorite LLM, ask it to deeply analyze your writing, build memories for storage, and instruct that, hence forth, it should respond in your own voice. Why... why would I upload my thoughts to the machine overlords? I had a theory: A lot of my posts tend to be exploratory or pursuasive ideas, and (as observed by GPT) "favor metaphors, are often a bit playful, and grounded in shared experience rather than top-down instruction; warmth over authoritative;" and I think I write this way because it's also how I best receive and process information. I like a story, real-world examples, a healthy dose of self-deprecating humor and flexibility over rigidity. If GPT could explain things to me the...

5 years ago, I wanted to help the engineers on my team stretch their coding skills by presenting them with an entirely new set of challenges than the typical tedium that can come with building business applications day in and day out. Having built so many games over my own career, one unique element I've always enjoyed is building out the game's AI. After building the core engine, collision detection, and all that - building the AI was always a fun, and very different, challenge. I'd have to think it through: if I was a player, playing this character - what would my own in-game approach be? To be fair, what elements could my AI player see and interact with, and what would they not see, how could I scale my strategy to different difficulty levels. Expressing your strategy in code requires a different line of thinking. It may not directly translate to writing better business or consumer applications, but it stretches your computational thinking and problem solving. Plus it...

Can I be so bold as to create my own business acronym? What an apropos way to start this, because the acronym I want to create applies to that very question. Let me re-start by, somewhat apologetically, confessing that I'm one of those distracting types who gets an idea, feels really passionate about it, thinks it will change the world and will offer it up for consideration. Over the years, I've learned to balance out the negative qualities that come with it: I try to focus on nuance, rather than chase novelty; I started keeping more ideas to myself and doing more to vet my own solutions before offering them. While I'm a work-in-progress, I will admit I do love sitting in a meeting where there all problems and no solutions. The gears that start spinning at full speed in my brain can cause such a strong buzzing that people will look at their phones, thinking they're getting a call. One danger I learned long ago about getting so passionate about a new idea is that it can ...

It's always interesting to pit Gemini vs GPT using the same prompt and source data. There's never a clear winner - and it really points to how important the precision and quality of the prompt is.  Google's Gemini definitly wins on this one. It's really strong, but not great (zooming in, you can see the edges and there was overall quality loss) - however the speed of the update was impressve (<20 seconds!).

Will input change with AI? Speech detection with AI is remarkable and, in particular, the whisper-mode lets people speak comfortably in public. Folks are using it for everything from writing emails, creating presentations, and even writing code. But does that mean the death of my beloved keyboard? I like being as hands-free as the next driver (well, maybe not all drivers...) but right now it seems voice is meant to fill the gap when I can't use a keyboard, it's not the default.  There's the obvious social issue of talking outloud to a device. Whisper-mode and earbuds solves the privacy issue, but even then I've only found voice-input to be useful when I'm being conversational (researching, brainstorming, learning) or directional (send a short msg, asking for music to be played, requesting directions). It's a different story when I'm writing, editing, iterating, refining. It's hard to edit on the fly with spoken instructions. While reading is linear, writ...

  At some point in the early 90s I tried rebuilding a game I loved: Beast. It was written procedurally in Basic over couple of months of on and off coding. Clunky, filled with bugs but I felt proud. About 25 years later, with 12 years of professional experience, I tried again. In about an hour, I had a working version. No bugs this time. Of course, Beast is not a complicated game but by going object-oriented with multi-threading it was even easier. And then, another 8 years later, I built Beast again . In record time: 25 minutes using with 7 non-technical prompts. No logic or technical guidance - just plain-english rules. We're well past the point of arguing AI's abilities. Instead, I wondered: In those 25 minutes, what parts of my own experience did I leverage? Strategic Iterations: Even if the LLMs handles complex specs, doing things all at once will still overwhelm the human. There are too many things to track at once. The ability to break things down into discrete, logical...

I sense a lot of people are forming a love/hate relationship (or maybe, it's just become a hate relationship) with AI when it comes to creative pursuits. It intrinsically feels wrong to offload something so human to the machines. Being creative is so essential, so rewarding, that to use AI in any way evokes a primal knee-jerk reaction - as if we're trekking far too into the uncanny valley that our lizard brain keeps telling us "This is wrong. Go back." Am I fan of using AI to generate music, books, movies, or art? No. But do I enjoy using AI when I'm being creative? Absolutely, yes. Whenever I use an LLM (a good one, at least), I notice a few things happen: Even before I send my initial prompt, my creative idea is getting more refined. It's like talking to the rubber duck and critically evaluating your own thoughts - but, it's even better because the AI rubber duck actually responds. Putting emotions into words can be very hard. Capturing complex feelings...