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Thiago Colares | Senior software developer, tech lead, entrepreneur, agilist, customer-centric. Based in Montréal, Canada 🇨🇦 — 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 Programming Languages →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
sanjeet.dev ↗	66 match 2 shared topics	Sanjeet Chand - Senior Software Engineer.	en	technology-and-computing	robotsllmsaihumans	emailphone	none
sandeepbhaisora.com ↗	65 match 2 shared topics	Sandeep Bhaisora - Software Developer \| Java, Spring Boot, AWS, Microservices	en	programming-languages	robotsllmsaihumans	emailphone	none
mdornseif.io ↗	65 match 2 shared topics	Dr. Maximillian Dornseif - Exploring the World of Software Development	en	programming-languages	robotsllmsaihumans	emailphone	none
samuelolaegbe.com ↗	65 match 2 shared topics	Samuel Olaegbe \| Software Engineer	en	programming-languages	robotsllmsaihumans	emailphone	none
felipekb.com ↗	65 match 2 shared topics	Felipe's Thoughts – A small blog to my thoughts on LabVIEW software development	en	technology-and-computing WordPress	robotsllmsaihumans	emailphone	none
baddouh.com ↗	65 match 2 shared topics	Aimeri Baddouh \| Senior Software Engineer	en	technology-and-computing	robotsllmsaihumans	emailphone	none
badrooki.dev ↗	65 match 2 shared topics	BadRooki \| Free Dev Tools, Tech Tips & Blog	en	technology-and-computing	robotsllmsaihumans	emailphone	none
bailalayoub.com ↗	64 match 2 shared topics	BAILAL Ayoub \| Software Engineer Portfolio	en	programming-languages	robotsllmsaihumans	emailphone	none
mdrxy.com ↗	64 match 2 shared topics	Mason Daugherty - Software Engineer	en	technology-and-computing	robotsllmsaihumans	emailphone	none
lusanchezzuber.com ↗	64 match 2 shared topics	Lu \| Developer Portfolio	en	technology-and-computing	robotsllmsaihumans	emailphone	partial · 8
samthesoftwareman.com ↗	64 match 2 shared topics	Sam the Software Man \| Thoughts and teachings on computer science, software engineering/development, as well as general technology topics. Lessons that I wish had been taught to me early in my career as a programmer.	en	programming-languages	robotsllmsaihumans	emailphone	none
blackbored.dev ↗	64 match 2 shared topics	blackbored. \| perfecting the software craft.	en	technology-and-computing	robotsllmsaihumans	emailphone	none
cheatsheets.zip ↗	64 match 2 shared topics	CheatSheets.zip - Ultimate Cheat for Developers	en	technology-and-computing	robotsllmsaihumans	emailphone	none
onfranciis.dev ↗	64 match 2 shared topics	Francis Onukwu \| Software Engineer & Open Source Advocate	en	programming-languages	robotsllmsaihumans	emailphone	none
blakelee.net ↗	63 match 2 shared topics	Blake Oliveira's Blog – Thoughts and stories of a developer	en	programming-languages	robotsllmsaihumans	emailphone	none
sanjanakrao.com ↗	63 match 2 shared topics	Home	en	technology-and-computing	robotsllmsaihumans	emailphone	none
landongrindheim.com ↗	63 match 2 shared topics	Landon Grindheim \| Landon Grindheim - Software craftsman. Striving for simplicity and elegance.	en	programming-languages	robotsllmsaihumans	emailphone	none
onetwobytes.com ↗	63 match 2 shared topics	One Two Bytes \| Roaming the software world. A smorgasbord of topics I come across while writing software.	en	technology-and-computing WordPress	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.