My first name is a random set of numbers and letters and other alphanumerics that changes hourly forever

Joined December 2007
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"Really excited about something to the point of using it inappropriately or excessively, and only seeing upsides not downsides" describes how most good programmers respond to first learning any new tech or methodology. Why didn't we call those things "psychosis"?
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There is a psychological pull to keep agents moving, I feel like that is the path of slop. Delegate what makes sense to delegate when it’s ready to delegate, don’t treat subsidized token burn as a reason to generate code.
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If you do not spend more time thinking and learning and improving as a software engineer while using AI, you are doing it wrong. This should be a form of specialization. Trading technician skills for deeper engineering skills.
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mbriggs retweeted
I understand the concern of skills atrophying when using agents. But so far I am not seeing it. Instead I have learned all sorts of dark secrets of linux networking I somehow didn’t learn before agents building a networking product.
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mbriggs retweeted
The scourge of "Claude said..." is rampant. If you use "Claude said", it had better be in a sentence that is structured something like: "When I did some digging, Claude said <thing>, so I looked into that and it looks like it might work based on <x, y, z>." not "Well, Claude said <thing> so you're wrong." Claude says many things. Claude is very often wrong. Even when it's right, you should know why it's right. Own your work. Don't delegate all thinking to AI.
I think review is more important than ever but once 5000 line PRs started flying daily and people that have zero business in code opening PRs everyone stopped caring. Took 2 months to destroy a great design and review culture here. Now it’s all “claude said”
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AI is the most transformational technology of my lifetime, and I lived through the internet getting big and smartphones being a thing. How is it possible that I believe that 👆, and also think that AI is overhyped?
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I don't understand why people use terminal multiplexers (tmux / zellij) TTYs are a shitstorm of legacy standards.. All good terminals have solid split / tab implementations that do not inject complexity into the rendering pipeline. Why not just use your term?
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mbriggs retweeted
No one could have known that telling programmers "spend as much money as possible on this new agent technology; whoever spends the most money wins!" would result in companies spending too much money on this new technology.
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Giant caveat: we don't have a lot of data on this. Given that, I think most folks legitimately are not aware that pretty much all the data we have points to agent efficiency being better in dynamic langs. Anecdotally, that is also my experience. x.com/dhh/status/20586487897…

May 24
Agents don't need types. They're perfectly capable of pulling off incredible refactorings without. Give them a linter and a test suite, and you have all you need. Token efficiency is where it's at.
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I think part of the bad rap that OOP has came from the unfortunate practice of using private fields to avoid threading params through a lot of tiny methods. That is not OOP, that is DSL fetishism, and it exists in other forms in other paradigms.
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I'm glad @dhh is starting to market rails this way. The reality is your experience using agents with rails will be close to an order of magnitude better then nextjs / gin / react. Its a crime the platform has fallen so far out of favour. x.com/dhh/status/20586487897…

May 24
Agents don't need types. They're perfectly capable of pulling off incredible refactorings without. Give them a linter and a test suite, and you have all you need. Token efficiency is where it's at.
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mbriggs retweeted
Replying to @shreyansj
It’s refreshing to see a company of this size successfully call bs on the whole thing to this extent. One group of MTS on a mission, clean.
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I think solo dev ai on code not dealing with PII/Money you can responsibly operate at 5-10x output. solo dev dealing with PII/Money? maybe 3x? 2 devs? Maybe 1.5-2x limit is not workflows, techniques, or the models. It is human communication/comprehension.
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I feel like there is a hard cap on how much code you can responsibly merge in a day, and that number goes down as the number of folks you are working with goes up. Its not worth chasing reliable code gen past that.
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mbriggs retweeted
My current gut feel is that juniors will start at small companies as the first or second developer hire, for developing in-house software. They’ll build low stakes apps for those companies, like estimating, automations, websites, task management. It’ll teach them the strategic layer (since they own the whole stack) in a lower pressure environment. They’ll need to think about all of it, but the projects are small and the user bases tiny. This is as opposed to being a junior on a larger tech team, where you’re given small tactical slices to work on under close supervision. That route is drying up, I’m sad to say. These juniors will be affordable to a small business and AI will give them instant productivity that the business can leverage for operational efficiencies. My son @cedricholmgren is currently doing exactly this route; working at a local fence and deck company as their in-house programmer. He owns probably a dozen apps in 5 different languages and frameworks. It’s amazing. He’s been doing it for a couple years and at some point someone’s going to discover that he’s a lot smarter and more disciplined than his old man and snap him up.
Tactical vs Strategic Programming, and why I'm nervous for juniors: Good programming involves a mix of tactical and strategic decision-making: - Tactical: on the ground, short-term. The soldier doing the fighting. - Strategic: high-view, long-term. The general planning the war. You need to be a tactician to write good code. To choose the right syntax. To figure out the file structure. To figure out how best to test your changes. But you need to be a strategist to build code that lasts. To design the architecture. To automate away problems. To think beyond today. Agents have eaten the tactical part of programming. When you can pay below minimum wage for code, there's no point going into the trenches yourself. But AI cannot code strategically. Agents need someone at the top of the pyramid to tell them what to do. They need oversight. So, a developer's day-to-day job has become 100% strategy. Long-term thinking, all the time. (maybe this is why I'm so tired all the time now) If you identify as a tactical programmer - a code monkey - then you are out of luck. The job has changed. Personally, I like it. I always preferred thinking strategically about code. If you asked me what my job was about, I'd say 'building apps', not 'writing code'. But what makes me nervous is that we've pulled down the only bridge that brought juniors into the industry. We used to train juniors like this: 1. Give them only tactical tasks 2. Let them build up their strategic experience slowly Eventually, they are a good enough strategist that they are no longer a junior. But what happens when all tactical code is written by AI? What is the point of a junior? We obviously need juniors. We need new lifeblood coming into the industry. We need to leave paths open for extraordinary hires to enrich our companies. But how do we train them? How do you train strategic thinking? These are the questions I'm thinking about. I'd love to know your thoughts.
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After using @mattpocockuk grill-me-with-docs, I think there is a lot of value in sparse docs. Domain Language should deepen, not thrash, ADRs are a snapshot record of a thought in time, and don't pretend to be living/comprehensive. Document high value things that rarely change.
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mbriggs retweeted
I agree. Put your (human) time into understanding the problems, designing systems, and writing guides (or skills, if you prefer) that can amortize across many agent sessions. I just spent the equivalent of a full day rewriting my CODE_STYLE_GUIDE.md from scratch, by hand. The effort has already yielded better code, fewer little papercuts, and tighter, more understandable code.
Like many things, the 80/20 rule applies. Spend time on the process and the plan, which allows you to move more quickly through implementation. Slow and steady is faster in the long run because you spend less time (and tokens) correcting mistakes.
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mbriggs retweeted
There is a lack of grounding with many folks. HOWEVER, counter point. Most strong leaders arent very public with their opinions - especially on this platform - and a surprising amount of them are very grounded in the way they're adopting things. They look at the information the same as we do, have made similar well-reasoned decisions, and are cautiously moving forward with increasingly forward looking approaches. I think its important folks continue to push back on too-futurist opinions amongst corporate leaders (and others), but moderation is always the key component. Facts change over time, and you should be willing to change your way of thinking as they do. Two years ago there's not a chance in hell I would be generating code with an LLM (in any meaningful degree), but now I do it exclusively. My adoption and stance have changed over time as the technology has changed, but there are also many problems that I still see with the tech today that were very visible six months ago, let alone two years back. I dont see a lot of evidence for some of the things that have become popular opinion (the personal fav being engineering being a less valuable skill). I think the biggest issue that is pretty widely visible is that the public discourse is often wildly disconnected from the reality inside of these organizations. "AI is causing layoffs", "we're not hiring new grads", "engineering is dead", etc. Those are toxic, and do not reflect real truths.
I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out. I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really). It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely. The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture. We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying. I worry.
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mbriggs retweeted
I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out. I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really). It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely. The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture. We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying. I worry.
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