I agree. Even though I thought this mission was interesting, to me the article massively overstates everything. NASA and the crew is SO amazingly competent, the world in recent years is SO totally devoid of competency, everyone has been thirsting for the sense of AWE that we are ALL feeling (or should be feeling now, let me list the reasons!), etc.
To me, this was irritating. True competency and things that inspire real awe encapsulate “res ipsa loquitur” — they speak for themselves. Having some internet influencer try to hype me into getting awed, and implying that “we all” are feeling a certain way as she channels our collective zeitgeist is tiresome.
And personally, IMO although the mission was nice, it wasn’t groundbreaking technically or particularly awe-inspiring.
Ironically, I left feeling a tiny bit disappointed: if everyone is truly thinking this mission is the height of awesomeness or competency, we have a low-ish bar.
I bet that when the old-timers with their starched white shirts, pocket protectors, and horn-rimmed glasses that did the 60s missions got together to watch 2026 Artemis they privately had a good laugh about how little state-of-the-art has progressed.
One way that I could imagine a human-only HN could evolve in the coming AI wasteland: motivated individuals join small local groups and are validated face-to-face at meet-ups. Local trusted leads gatekeep their chapter’s posts, and this scalable moderation works up the tree. Bad leaves get culled out reasonably fast, maybe there’s some controls at the top level that let you see more content “lower down the tree” if you’re ok with lower SNR. Latency to get a post widely distributed grows but I don’t see that as a massive problem.
Fully agree: I believe my decades of software engineering experience definitely help me fly LLM tools better than less experienced folks.
But the much more interesting question to me: as LLM coding becomes the norm, does it drive the cost of self or small-company generated software to 0?
Like many SW architects/engineers my not-so-developed work-in-retirement plan is to assemble a small team of people I’ve loved working with over the years, start an LLC, and try to make a reasonable (not posh) living doing what we love: making software to solve problems.
On the one hand, it’s clear LLM coding can accelerate and amplify our efforts, but alternately there’s many people claiming there’s no possibility of a moat, your solution/innovation can be cloned in a matter of days … ie. the value of your software is exactly 0.
Not sure which future will be closer to reality. A backup plan that seems reasonable in the 0-value case is to focus our effort on creating actual physical gadgets and systems in the embedded realm, which conceivably can be designed and prototyped by a small team… It seems like these would still be valuable.
My team has experienced this over the past 6 months for sure.
The core of the article is “ AI-assisted development potentially short-circuits this replenishment mechanism. If new engineers can generate working modifications without developing deep comprehension, they never form the tacit knowledge that would traditionally accumulate. The organization loses knowledge not just through attrition but through insufficient formation.”
But is it possible this phenomenon is transient?
Isn’t part of the presumed value add of LLM coding agents in the meta-realm around coding; e.g. that well-structured human+LLM generated code (green field in particular) will be organized in such a way that the human will not have to develop deep comprehension until needed (e.g. for bug fix/optimization) and then only for a working set of the code, with the LLM bringing the person up to speed on the working set in question and also providing the architectural context to frame the working set properly?
Agree on data value, but as mentioned above I am not yet buying the “everything will be instantly copyable and so any solution is instantly commodity” argument … crud web-app sure, something with significant back-end complexity or a multi-service systems level solution, not so much. Perhaps optimistic, admittedly. Cheers.
Fair point, but my hope is that the creativity involved in deciding what to build, with the choice informed by engineering experience (the project/value will not be obvious to everyone) will allow differentiation.
After a multi-decade career that spanned what is rapidly seeming like the golden age of software development, I have two emotions: first gratefulness; second a mixture of resignation, maudlin reflection, and bitterness that I am fighting hard to resist.
As someone who’s always wanted to “get home and code something on my own”, I do have a glimmer of hope that I wonder if others share. I’ve worked extensively with Claude and there’s no question I am now a high velocity “builder” and my broad experience has some value here. I am sad that I won’t be able to deeply look at all the code I am producing, but I am making sure the LLM and I structure things so that I could eventually dig in to modules if needed (unlikely to happen I suppose).
Anyway, my hope/question: if I embrace my new role as fast system builder and I am creative in producing systems that solve real problems “first”, is there a path to making that a career (I.e. 4 friends and I cranking out real production software that’s filling a real niche)? There must be some way for this to succeed —- I am not yet buying the “everything will be instantly copyable and so any solution is instantly commodity” argument. If that’s true, then there is no hope. I am still in shape, though, so going pro in pickleball is always an option, ha ha.
Thanks very much for this awesome write up! It’s detailed labor-of-love work like this that helps others (like me!) make great jumps in learning. So appreciated.
Politics aside, according to a pretty comprehensive study (118 missions) it does seem that SpaceX is much more efficient than NASA [1]. Data like this would suggest privatization of space missions is a good idea. Maybe this conclusion is biased somehow, or perhaps the purpose of a dedicated govt org is different in some way that justifies its budget and scope despite the difference in efficiency?