Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to brownjohnf.com

Jack Brown · ranked by shared content topics & relevance
63match
gregtjack.com
Greg Jackson
2 shared topicsprogramming-languages
62match
benjack.io
Benjamin R. Jack
2 shared topicstechnology-and-computing
62match
adambrohl.dev
Adam Brohl - Home
2 shared topicsprogramming-languages
62match
docsallover.com
DocsAllOver | Improve Your Skills | Browse Programming Docs
2 shared topicsprogramming-languages
61match
aaronlindsay.dev
Aaron Lindsay | Full-Stack Developer
2 shared topicsprogramming-languages
61match
alandjackson.com
Alan Jackson's Blog – Painless Coding
2 shared topicsprogramming-languages
61match
maxminded.com
Maxminded | less talking, more coding
2 shared topicstechnology-and-computing
61match
roadtofullstack.com
Road To Fullstack | Road to Fullstack
2 shared topicstechnology-and-computing
61match
1funlab.com
Peifeng Wang — Full-Stack Engineer, Tokyo
2 shared topicsprogramming-languages
61match
mavindrude.com
Marvin Drude - Senior Full Stack .NET Developer
2 shared topicstechnology-and-computing
61match
0not.net
0not -- Programming, hacking, making, and science.
2 shared topicsprogramming-languages
61match
maxencerb.com
Maxence Raballand - Fullstack and Blockchain Engineer
2 shared topicsprogramming-languages
61match
benji377.dev
benji377 (Benjamin Demetz) - Full-Stack Developer Portfolio
2 shared topicstechnology-and-computing
61match
bondaika.com
Bondaika Blog – Data Engineering, Python, Cloud & More
2 shared topicsprogramming-languages
61match
pirgee.com
Pir Gee | Learn Programming, APIs, Databases & Tech Trends
2 shared topicsprogramming-languages
61match
softwaredebugged.com
Software Debugged – Computing, software and the internet
2 shared topicstechnology-and-computing
61match
mauihackday.com
MAUI Hack Day - Mobile Apps and AI | Sydney, Brisbane, Melbourne and more
2 shared topicsprogramming-languages
60match
4dpiecharts.com
4D Pie Charts | Scientific computing, data viz and general geekery, with examples in R and MATLAB.
2 shared topicsprogramming-languages

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:

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.