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
---
create a public engineering-blog SKILL.md. ( ~ collect the writing patterns that work on HN )
Ugh. That looks like AI this, LLM that, Agent this.
Where are the databases, the distributed systems, where is the software verification?
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 built a feed reader with that concept in mind, having a separate triage stage where you only decide if it's worth reading or not. This will make it easier to handle large feed lists and find the best articles from them.
For example my HN feed only surfaces articles with enough votes + comments and a few other variables.
All high-content feeds also have a maximum number of items, if it goes over they're marked as read.
Now if I don't see it on a page I check the page source - some blogs don't advertise the feed but it's there.
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!
For example: The Architecture of Open Source Applications
edit: typo
To answer the OP, this Civil engineering blog / video site is really good. I always learn something new, and his enthusiasm is infectious. Well worth giving it a look:
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.
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.
but to specific is much important, imo Engineering means "Solving problem at a scale", irrelevant of the industry.
Words change meaning over time and with the audience.
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.
Raymond Chen's The Old New Thing is also required reading for anyone that works with Windows.
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/
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.
Sometimes they do it in the form of free or open source software releases.
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).
https://www.redblobgames.com/ is not strictly speaking a blog, but an interested collection of articles on algorithmic concepts you might want to know for writing games.
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
from a Phd maths guy, who's worked in satellite comms, and blogs on software defined radio and comms protocols (eg error correction and radio modulation, often in space related contexts, eg decoding Voyager comms).
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.
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.
Problem I had with the other newsfeeds is that I get distracted by the constant updates, always refresh the front-page, skipping the actual content and just skimming through headlines and comments.
So I built this one, set it as my homepage, and because it doesn't update often, I will actually read the content of the links. When I'm done, I move on to other things in life.
It's curated by matching keywords (focusing on web development) on HN, mostly automated but with few manual adjustments now and then.
1. BI Cortex - sadly seemingly not active anymore: https://bicortex.com/
2. Mark Litwintschik's Tech Blog: https://tech.marksblogg.com/
The best ever is, IMO, Charles Bloom's blog, especially if you have any interest in data compression:
https://cbloomrants.blogspot.com/
But it is no longer regularly updated.
quite diverse, often challenging, sometimes mind bending
https://www.mongodb.com/company/blog/channel/engineering-blo...
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.
date
of
an
account
means
nothing,
bro.
Gold
star
for
the
decade
of
participation
though!
Always happens to me (and I don’t use fucking LLMs) so I’d really like to know.
1. this is first line
2. This is second
3. ...and so on
It was a great question and now I have a ton of new things on my reading list.
Nothing wrong with the phrase itself of course, other than the fact that it's like literally in every other reply for me lol.
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
I’m trying to surface and study those scattered examples—especially the ones that explain why decisions were made, not just what was built.