Discover the best developer blogs on any tech stack(bloggingfordevs.com) |
Discover the best developer blogs on any tech stack(bloggingfordevs.com) |
what I didn't expect about that site is that it gets shared A LOT on twitter. still trying to refine the algorithm :)
thanks a ton for checking it out and sharing your feedback!
Perhaps not a straight ascending or descending by frequency. For me, the sweet spot seems to be no more than once a month. More if it's one that does something like a weekly post aggregating interesting articles from other blogs.
That being said, it looks like points are awarded two ways:
* Counts the least: Retweets and likes of a tweet containing a link to an article on the blog
* Counts the most: Replies and mentions of an article on the blog by other people
So I'm sure it's possible to game this, and it seems to bias toward incumbents (but what doesn't), but at least it's trying to be a little better than "here's a list of blogs I like."
He definitely has a far more commercial focus than many other bloggers but this seems a bit too critical to me.
One slight improvement that would push me to actually bookmark a site like this is if, rather than merely listing _entire blogs_, it listed a feed of the most recent _posts_ from the various blogs.
Posts are the level of abstraction that directly aligns with our reading habits. (Similar story for podcasts: give me an episode feed, not a podcast feed.) Twitter and other social media giants have cracked this code well.
Cheers! * opens google.com/reader and plays the 2005 Gorillaz hit song Feel Good Inc before going to the cinema to see V for Vendetta *
Glad you enjoy it, and yes, the goal is to make it easier to find blogs from individuals. I don't reject sites hosted on 3rd party platforms, but I do encourage people to post their own domain name when possible.
Cheers!
While the BFD trends site is focused on personal developer blogs & trending posts, that one includes high-quality engineering team blogs too, like Cloudflare and Google Research. It's a bit simpler, and focuses simply on the latest posts rather than trending content, but it's worth a look.
One of today's (tech) luminaries? For me it's Scott Hanselman. Always worth reading, even if you're not particularly on the Microsoft stack.
You directly go to dark mode ;) it's more popular I known; I like to suggest a light mode; maybe you can read it from the system like StackOverflow.
Yeah it's kinda meant to be like its own mini site. But if you click the logo at the top, it does take you to the root homepage :)
Adding a light mode is on the backlog, thanks for the suggestion! I need to remove a few hard-coded CSS values first ;)
Bring back the old school internet, forums, curated lists, niche communities, irc !
I would be happy to use human curated collections of links by topics.
I found it similarly irritating while sourcing the data that all the top 10 google results recycled the same, outdated recommendations.
Do you mean you'd like a central place to discover individual's curated list of blogs they read? Like blogrolls?
not sure about the sites linked, but i reject sites that are low quality and filled with aggressive ads!
Thanks
Gives people more control over their personal "algorithm" and what they value most when reading personal blogs.
Hadn't thought about frequency but that could definitely be something you could automate based on RSS. Thanks for the idea!
I'd possibly put a shared blog under a similar category as the ones with weekly roundups. Which is exactly why I threw out that example - I don't want hard-and-fast Google-style rules, because I would expect that to work out about as well as hard-and-fast Google-style rules ever does.
as you suggested though, i didn't know the ML space enough to know that Machine Learning Mastery publishes daily and has an army of people who like and retweet ANYTHING they publish.
so it makes me wonder if i need to have some kind of dampening effect or how i can adapt the algorithm to handle that.
Let's take Stack Overflow as an example. Jeff found a small group of experts and expanded it. They seeded both questions and answers. They didn't bring on just one or two experts though, they brought on enough to ensure a good distribution (not perfect) of viewpoints and then reviewed before expansion. They kept repeating this and didn't optimize for just one kind of developer (Django over Java.) All segments of developers tended to need the same features, but it would show up with one segment first. Getting answers on some topics wasn't possible until the product was more mature. Kill crap ruthlessly like SO did with downvoting and moderator-led deletion.
If you are building an ML model then you are going to need to find a range of experts and either seed from what they are sharing, or create a review system. You can reward people with kudos on a contribution page, donations to open source projects or charities (even on behalf of a group of them), or find another way to motivate them. It just needs some hustle, but you've got to forget about purity, be open about how your model works, and iterate.