CTO @opexfitness. Formerly founder/CEO at @truecoachco(acq by Xplor) and former co-owner of @crossfitkp. I like building things,🏂🏄🏼‍♂️🚵🏽🚣🏽🏀🎶 &🏋️‍♂️.

Colorado, USA
Joined November 2007
Casey Jenks retweeted
this California wealth tax thing is just incredible. so in October 2025, a California healthcare union proposed a "one time" 5% tax on any billionaire's wealth. the ballot measure will be voted on next month. In early December 2025, California announced that it would be a retroactive tax if passed, applying to anyone with CA residency as of Jan 1, 2026. The objective is to pay for Medi-Cal, California's incredibly dysfunctional healthcare system. (which also functions as a glorified welfare apparatus, but that's a discussion for another time). polls reveal that the CA electorate is split around 50/50 on the tax, but prediction markets only give Prop 40 a ~23% chance of passing (there are competing measures on the ballet that would nullify it). there are 200 billionaires in CA, worth collectively somewhere between $2.3 and $2.6 trillion. 5% of that is around $100b, accounting for a small amount of attrition. proponents of the tax forecasted a significant windfall, assuming only a 10% departure rate. supporters thought they were being clever with the retroactive concept. no billionares would leave CA in the few short months between the tax being proposed and the residency cutoff date, without the tax even having passed yet, right? well as it turns out, they did. a new paper [1] from two academics at Stanford called "The Net Present Value of the California Billionaire Tax Act", argues that not only did more billionaires leave due to the proposed tax than its proponents expected, but that the value of the tax, if it does pass, is actually negative. proponents of the tax only assumed 10% avoidance, that is, only 10% of the taxable base of targeted billionaires would leave CA within the very short Oct-Dec 2025 window. Jaros and Rauh, the Stanford academics, find that a lower bound of 28.6% of the taxable base managed to leave. just based on known departures, those departures total $577b in net worth, or $28.8b in potential tax lost. this of course does not capture everyone (many left without announcing their departure), so the authors normalize to departure rates estimated from other wealth tax events, and apply other discounts for litigation, arriving arrive at a figure of only $28-$36b in forecasted tax revenues. but this isn't all! all of the income taxes paid by the departed billionaires are also forsaken. the authors estimate that CA billionaires pay $3.3- 5.8b in annual income taxes. they assume a midpoint of $2b lost in annual collections from departed billionaires. the net present value of that lost income stream is -$68.9 billion. so when you add it all up you get: + $30b one-time tax windfall (estimated) - $69b in present value of lost future income taxes = - 38.9b overall net present value of the tax of course, this analysis is highly estimate driven. the authors simulate the parameters 100k times and find a negative NPV of the implemented tax 85 percent of the time. and if the tax doesn't pass, which it's not looking like it will, California still ended up losing at least $577b in departed net worth, and they have permanently poisoned the well with entrepreneurs who will now worry about future wealth taxes. [1]: nber.org/system/files/workin…
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Casey Jenks retweeted
We covered billions of healthy faces without evidence adequate to justify it. The objections went far beyond filtration: physiology, vision, speech, development, identity, autonomy. 18 arguments everyone should have heard. THEY COVERED OUR FUCKING FACES.
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Pair planning > Pair programming
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Casey Jenks retweeted
this man’s vision of our country is forcing you to take out loans from the government, to pay taxes on money you don’t have, to fund endemic fraud and healthcare for illegal immigrants
Replying to @RoKhanna @mcuban
Allow illiquid founders to pledge shares with a loan from the government to pay tax. The loan period is long but not infinite (e.g. 10 years). The loan is non-resource: at the end of the period, the loan is either paid back in cash, or the government assumes the shares.
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Hilarious. Imagine needing a meeting to figure this one out.
JUST IN: WNBA Commissioner announces the league is meeting to review what a woman is, after multiple former NBA stars announced plans to join the league.
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Casey Jenks retweeted
This is going down to $25m in under 18 months… then $10m and finally $3m
There it is… California's Democratic Party has voted to endorse the billionaire wealth tax on the ballot. If it passes, anyone with a net worth of $1B+ will have to give 5% of their assets to the state.
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Casey Jenks retweeted
Not every engineer will become a Product Engineer. That’s the uncomfortable truth. For years, the job was clear. - Take a ticket - Implement it well - Move to the next one You could be excellent without ever touching the “why”. That’s changing. AI is taking over more of the implementation. Which means the value moved upstream. To: - Defining the problem - Deciding what to build - Scoping what actually matters And not everyone enjoys that work. It’s messier. More ambiguous. Closer to business than code. Some engineers will step into it. They’ll talk to users. Challenge assumptions. Own outcomes end to end. Others will stay in execution. And over time, the gap will widen. Not because one codes better. But because one decides better. AI didn’t remove engineers. It split the role. Between those who define value and those who implement it.
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Oh you bought a @WHOOP ? Congrats, you like me are yet another person who spent $300 to figure out that eating well, exercising everyday and not drinking alcohol delivers better recovery and sleep
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Facts
Using Claude Code has a weird side effect: You don't just get more productive, you actually want to work more. There's something addictive about watching a product being born in real time in front of your eyes. "One last feature" after "one last feature" and it's already past 3am.
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Casey Jenks retweeted
I'm Boris and I created Claude Code. I wanted to quickly share a few tips for using Claude Code, sourced directly from the Claude Code team. The way the team uses Claude is different than how I use it. Remember: there is no one right way to use Claude Code -- everyones' setup is different. You should experiment to see what works for you!
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Casey Jenks retweeted
The profound thing that happens with AI coding is you just start to say yes to bigger and bigger projects. The work that felt daunting because there’s no way of validating if it was a good idea for 6 months all of a sudden you can sign up for since you’ll know in a week.
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Casey Jenks retweeted
A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.
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What an epic surprise tonight.
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We moved from Notion over to @linear for our project management a few weeks ago. It's a truly well crafted piece of software.
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Refreshing to see the tech community has finally developed anti-bodies to the Pronoun Taliban
A group of Lefist Activists are pushing for the Ruby on Rails project to remove the project’s founder (@dhh) because they claim he “holds racist and transphobic views” and “other traits undesirable”. This group, which compares themselves to the French resistance during WWII, is also demanding the adoption of a “modern Code of Conduct”. github.com/Floppy/plan-vert-…
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