Builder • Software Engineer — Techno-polymath • Crypto-optimist • ai/acc — Ex: VP Eng @Apptegy, @BaseQL (acquired), CTO @Nimbo_X

The Internets
Joined February 2007
This is an excellent point. A (good) SW engineer has to learn continuously until the end of their career. And a great SW engineer actually enjoys learning, and teaches others as well!
I think many of us working in tech tend to forget that the reason software engineering vs other engineering fields pays (a lot!) more, is a lot more flexible (WFH/remote), and has better perks: Because this field changes much faster than other engineering fields. The premium is because fewer people are able/willing to pick up new technologies, methodologies so quickly. But the field had ~10-20 years of stability, and so lots of folks forgot this is why a premium exists. And that AI is just another tech wave: software engineers who pick it up and master it will generally fare better; those not will struggle a lot more.
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Ask your mechanical engineer, electrical engineer, civil engineer, chemical engineer friends (if you have them) what their pay is; how much equity; how easy it’s to work remote; and how easy to live countries without taking country-specific exams or learning the local language. Software engineering is a privileged field in many ways: but it’s like this because few enough put up with the brutal pace of change that happens periodically, and leaves those behind who don’t like sudden and less predictable change.
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I think many of us working in tech tend to forget that the reason software engineering vs other engineering fields pays (a lot!) more, is a lot more flexible (WFH/remote), and has better perks: Because this field changes much faster than other engineering fields. The premium is because fewer people are able/willing to pick up new technologies, methodologies so quickly. But the field had ~10-20 years of stability, and so lots of folks forgot this is why a premium exists. And that AI is just another tech wave: software engineers who pick it up and master it will generally fare better; those not will struggle a lot more.
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if the codebase is the prompt, DDD is prompt engineering ubiquitous language, bounded contexts, aggregates... Evans wrote it for teams of humans. turns out the agents needed it more
The codebase is the prompt
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- ubiquitous language = the agent's vocabulary. call it Order in one place and Purchase in another and it'll invent a third - bounded contexts = context windows that actually fit
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- aggregates = invariants the agent can't quietly break - anemic models leak rules into random services. the agent copies the leak
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Looking forward to install it on my Steam Deck!
Fortnite is coming to Linux!! We are already working with the folks at @EpicGames to ensure that @Omarchy is ready on day one with all the security requirements. Amazing what's possible when you nag @TimSweeneyEpic for years 😂 store.epicgames.com/news/epi…
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.@steipete should have gone to @SpaceXSI instead of OAI
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writing is thinking agents made typing cheap not judgment outsource the words you use to steer them and you outsourced the only leverage left
i love writing. i never let agents write for me. whether it's docs, or tweets, or shitposts, or even prompts (okay maybe that one's harder as agents manage other agents) there's a simple reason for that: i still strongly believe that writing is thinking. it's a skill i hope to never give up. it's also important to me that whatever i say is always authentic, mistakes and all. my favorite posts are the ones that i just full send without any editing i suspect it also helps with prompting. being able to clearly express what i want, and knowing the vocabulary i need to be able to direct my agents does seem to make for more effective usage of agents. in the same way that engineers have an advantage when we prompt agents to write code, because we are intimately familiar with the words that make up the discipline knowing the right word incantations to get an agent to produce a desired goal almost feels like spellcasting. as models get more capable, and that input box looks more and more like a magic box that can output anything, words become the interface between you and the genie there may come a time when we give up the keyboard in exchange for brain-computer interfaces. but until then, i'm writing every word.
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Replying to @dhh @poteto
I feel like domain driven design and few others still make sense in a world of agents.
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"The purpose of software engineering is to control complexity, not to create it." – Pamela Zave More true now than ever.
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Ben Orozco retweeted
hot take: by freeing us for the hassle of writing code, SWE is now more about engineering than it has ever been
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Replying to @bot
@bot give my bot an email address
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Hello @bot would like a mail.grokbot.com email address please!
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Hey @bot get me an email address please. Preferably [email protected] otherwise [email protected]
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flip side: programmers hold the deepest context in the building and context is the bottleneck now, for humans and agents alike the automation backlog is huge most of it is stuff only they know is broken put down the pencil, keep the context
before agents, programmers hated being micromanaged now they’re on the other side of the equation same pattern, same trap fixing the agent instead of the environment forced to learn the management lesson the hard way correct the system, not every output
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Ben Orozco retweeted
We can debate what "intelligence" is until the cows come home; I don't think it really matters. All I know is that I've seen both "intelligent" humans and "intelligent" machines do really stupid things when they aren't given enough context / information regarding a decision.
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iykyk
Oh shit I just realised that grilling is where the meat and the metal interact
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Ben Orozco retweeted
"This is not the time to doom, baby. This is the time to bloom. Intellectually, spiritually, and productively. Put down your anxieties, arrest your neurotic impulses, and decide to be happy about the present, the future, and..." world.hey.com/dhh/what-on-ea…
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Ben Orozco retweeted
Replying to @jcmrgo
The harsh reality is that programmers that wanted an IC-only career path will have the hardest time managing this transition
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before agents, programmers hated being micromanaged now they’re on the other side of the equation same pattern, same trap fixing the agent instead of the environment forced to learn the management lesson the hard way correct the system, not every output
it's easy to fall into the trap of micromanaging your agents instead of correcting the environment that shapes its behavior. pstack 0.15.9 now ships a new /correct skill: if you keep correcting agents for the same mistakes, it finds the pattern and fixes it with architecture, types, and checks. i like to imagine that commits rapidly flowing into the codebase are like a bonsai tree rapidly growing in whatever direction it pleases. what you want to do is not to give in to the chaos, but tame it intentionally with the right constraints 0.15.9 also has improvements to: • /architect: now includes instructions on designing agent friendly architecture • a new /benchmark-checklist skill based on @brendangregg's benchmarking checklist here's a prompt you can give to grok bot to start architecting a better codebase with pstack: /poteto-mode create a new Project agent to refactor and rearchitect my repo so that our architecture is more agent friendly. it should use both the /correct and /architect skill to look through past commits and find the most common pitfalls that agents fall into, whether its with code quality, performance, or bugs. if relevant you can also use the /recall skill to find past conversations for context. it should make a high level plan for me to review. it should also answer its own open questions by prototyping rather than defer to me. come back to me with a plan backed by real data. once i approve the plan, use either the stack or full autopilot playbook (ask me which i want) to execute
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