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Alwayslearning alternatives & similar sites

Always Learning… — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Technology And Computing →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
pacoworks.com ↗	68 match 2 shared topics	Paco won't stop learning	en	programming-languages Ghost	robotsllmsaihumans	emailphone	none
jasonmojica.net ↗	66 match 2 shared topics	Jason Mojica — Never Stop Learning	en	programming-languages WordPress Reaction Commerce	robotsllmsaihumans	emailphone	none
developerstv.com ↗	65 match 2 shared topics	DevelopersTV \| Curated Developer Learning Videos	en	technology-and-computing	robotsllmsaihumans	emailphone	none
derickpeterson.com ↗	65 match 2 shared topics	CS Guy – The Adventure of Learning Computer Science	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
devdotdev.dev ↗	64 match 2 shared topics	DevDotDev.dev – compiling…	en	programming-languages WordPress	robotsllmsaihumans	emailphone	none
devconfbd.com ↗	63 match 2 shared topics	devConf 1.0 \| Powered by Learn with Sumit	en	programming-languages	robotsllmsaihumans	emailphone	none
outofmemo.com ↗	63 match 2 shared topics	Out Of Memory! – Learn. Share. Succeed.	en	programming-languages WordPress	robotsllmsaihumans	emailphone	none
thingsilearned.com ↗	62 match 2 shared topics	ThingsILearned by Dave Fowler - ThingsILearned	en	technology-and-computing	robotsllmsaihumans	emailphone	none
bohiomushtaque.com ↗	61 match 2 shared topics	Learn with Bohio Mushtaque - Tech Educator \| Software Engineer \| Freelancer	en	technology-and-computing WordPress	robots llmsaihumans	emailphone	none
devcaffeine.com ↗	61 match 2 shared topics	/dev/caffeine: a programmer is a biological machine for turning coffee into code	en	programming-languages	robotsllmsaihumans	emailphone	none
jeffrey-lean.com ↗	61 match 2 shared topics	Jeffrey Lean TechHub \| Jeffrey Lean TechHub	en	technology-and-computing	robotsllmsaihumans	emailphone	partial · 8
james-lemin.com ↗	61 match 2 shared topics	James Lemin \| The personal site of James Lemin	en	programming-languages	robotsllmsaihumans	emailphone	none
24daysindecember.net ↗	61 match 2 shared topics	24 Days in December – Thoughts of the PHPamily	en	programming-languages WordPress	robotsllmsaihumans	emailphone	none
cslib.io ↗	61 match 2 shared topics	A Focused Effort on Formalizing Computer Science in Lean	en	technology-and-computing	robotsllmsaihumans	emailphone	none
boringrails.com ↗	61 match 2 shared topics	Boring Rails: Skip the bullshit and ship fast \| Learn about the boring tools and practices used by Basecamp, GitHub, and Shopify to keep you as happy and productive as the day you typed rails new	en	programming-languages	robotsllmsaihumans	emailphone	none
bolt-software.com ↗	60 match 2 shared topics	Home - Keeping up with the fast paced world of software design, planning, and implementation.	en	programming-languages	robotsllmsaihumans	emailphone	none
thicolares.com ↗	60 match 2 shared topics	Thiago Colares \| Senior software developer, tech lead, entrepreneur, agilist, customer-centric. Based in Montréal, Canada 🇨🇦	en	programming-languages	robotsllmsaihumans	emailphone	none
mbinjamil.dev ↗	60 match 2 shared topics	Muhammad Bin Jamil \| mbinjamil.dev	en	technology-and-computing	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.