https://stripe.com/blog/engineering
https://engineering.linkedin.com/
https://engineering.atspotify.com/
https://careersatdoordash.com/engineering-blog/
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Aggregators:( https://engineering.fyi/ ; https://diff.blog/ )
+ https://hn.algolia.com/?query=engineering%20blog
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create a public engineering-blog SKILL.md. ( ~ collect the writing patterns that work on HN )
But thank you!
* https://engineering.fb.com/feed
* https://netflixtechblog.com/feed
* No feed for stripe
* https://www.uber.com/en-GB/blog/london/engineering/rss/
* No feed for LinkedIn
* https://engineering.atspotify.com/feed
* https://tailscale.com/blog/index.xml
I think it's on purpose. It is to signal that these (those without RSS) aren't really "engineering" blogs at all, they're marketing websites aimed to help with recruiting and making the organization seem "engineering-like".
Edit: Ah, noticed I made a without/with typo, fixed that, should make about 2% more sense now for the ones who the original meaning was unclear :)
> It is to signal that these (those with RSS) aren't really "engineering" blogs at all
So now when I corrected that with/without typo, it looks like your previous comment doesn't make sense, but it kind of did, at the time. Sorry about that and thanks for making me realize the typo!
Maybe, generously, in retrospect, an aspiration?
I never considered myself an actual engineer; I was (and still am) a self-taught un-credentialed computer programmer. More art than science. They made me take the title and the stock options and the business cards.
I mostly worked for and with EEs, making software tools for test automation. I was a fanboy hardware wannabee (and still am), got some on me but was never a true engineer. I learned from those who practiced their discipline; it was plain to me the reality of real engineering versus what I was doing.
I suppose in my travels I have on occasion encountered a true Software Engineer. I suppose there's reason to hope that software development will continue to mature and evolve, and eventually the other engineering disciplines will accept software as a science.
For me, it will always be a joy to make that hardware work with my twiddly bits. Not engineering, no. But very rewarding work that often resembles engineering.
edit: typo
In general, though, my very limited experience working in manufacturing was that much of the blog equivalents were covered in things like white papers from hardware manufacturers or articles in trade publications. We always had a bunch of magazines delivered each month and there were usually some interesting articles to review.
For example: The Architecture of Open Source Applications
She also publishes a number of technical topics as ZINES. I bought her "Oh Shit, Git!" zine and learned a ton of useful info, despite having decades in the industry.Zines are a great way to encourage book-allergic coworkers into learning great material.
Blog posts where I find quality really shows are usually about something I know next to nothing about how it works. A badly written article usually either goes really shallow or skips some facts when going into depth and requires catchup elsewhere to actually understand it. The lidar article from Main Street Autonomy goes beyond basics and explained everything from the ground up in such a connected way that it was a real pleasure reading it.
Antirez' blog (of Redis fame) https://antirez.com/
Simon Willison's blog (about AI) https://simonwillison.net/
His "Today I Learned" series is an extremely useful selection of small learnings: https://til.simonwillison.net/
Sometimes they do it in the form of free or open source software releases.
A while ago I felt this "information fatigue" due to the overwhelming updates from the typical news sources (reddit, twitter, even hn).
So I built a _slow_ webdev newsfeed aggregator that doesn't overwhelm you of constant updates, so you focus on reading the actual blog contents and enjoy other things.
It's not "technical" so much as it just educates you on how to be a good web developer/run a team. There's zero fluff and considerable detail (footnotes are practically blog posts themselves).
Raymond Chen's The Old New Thing is also required reading for anyone that works with Windows.
Otherwise... coming soon from a vibe-coding session near you...
We'll filter an RSS feed based on the topic and description that you provide. Feel free to reach out to me at s.kufuor@<domain> if you have any questions or feedback.
quite diverse, often challenging, sometimes mind bending
https://www.mongodb.com/company/blog/channel/engineering-blo...
There is much to learn, in these books.
The Mind of an Engineer by Purnendu Ghosh et al. - https://link.springer.com/book/10.1007/978-981-10-0119-2
The Mind of an Engineer: Volume 2 by Purnendu Ghosh et al. - https://link.springer.com/book/10.1007/978-981-15-1330-5
Nothing wrong with the phrase itself of course, other than the fact that it's like literally in every other reply for me lol.
But sure, cheer on the homogenization of online spaces into beige slop staccato bullshit!
˙ ͜ʟ˙
- Even if you separate each point with a new line, - HN formatter will join everything to one line anyway. - So it's not OP's fault his points are in the same line, because the source post has them in separate lines.
Always happens to me (and I don’t use fucking LLMs) so I’d really like to know.
It was a great question and now I have a ton of new things on my reading list.
1. https://nepp.nasa.gov/whisker/
2. https://standards.nasa.gov/standard/NASA/NASA-STD-87394
3. https://standards.nasa.gov/NASA-Technical-Standards
4. https://sma.nasa.gov/sma-disciplines/workmanship
5. https://www.stroustrup.com/JSF-AV-rules.pdf
6. https://en.wikipedia.org/wiki/The_Power_of_10:_Rules_for_Dev...
7. https://www.nist.gov/pml/owm/laboratory-metrology/metrology-...
8. https://www.mitutoyo.com/training-education/
9. "Memoirs of extraordinary popular delusions and the madness of crowds" (Charles Mackay, 1852, https://www.gutenberg.org/files/24518/24518-h/24518-h.htm )
The artifacts are usually beautiful from good Workmanship Standards, Design For Manufacturability, and systematic Metrology. Dragging us all into the future one project at a time.
Note that training an ML model with such data would be pointless, as statistical saliency forms a paradox with consumer product design compromises. Note, there are _always_ tradeoffs in every problem domain.
'What it actually means to be "AI Generated"' ( https://www.youtube.com/watch?v=ERiXDhLHxmo )
https://www.youtube.com/watch?v=iXbzktx1KfU
Have a nice day, and note >52% of the web is LLM slop now. YMMV =3