So, let's talk about Hackers.dev - or what it used to be, anyway. I first heard about this tool back in early 2023, when the job market for devs was a total mess, you know? Everyone was scrambling, and I was right there with 'em, sending out resumes into the void. This platform promised to cut through that noise with AI that actually gets your skills, and honestly, it sounded too good to be true.
But it worked - at least while it lasted. The main draw? It dramatically reduces the hours you waste on irrelevant listings. Instead of sifting through hundreds of generic dev jobs, the AI analyzes your profile - think React, Node.js, whatever your stack is - and serves up matches that fit like a glove.
We're talking a massive database of over 100,000 jobs, fine-tuned with embeddings to capture semantic similarities. No more applying to roles that say 'developer' but mean something totally different. In my experience, it boosted my application success rate by about 30%, or so I figured from the offers I landed.
Key features included that smart AI matching, easy filters for tech stacks and locations, and integrations with GitHub and Twitter for community vibes. You could tweak your profile with real code samples, and the system would embed them into a vector space to find gigs that align. It solved the big pains: invisibility to recruiters, mismatched opportunities, and the sheer exhaustion of job hunting.
I remember using it to pivot from web dev to fintech - the recommendations were spot on, highlighting roles with GraphQL and AWS that I hadn't even considered. This was geared toward developers at all levels - juniors building portfolios, mid-level folks seeking stability, or seniors eyeing leadership spots.
Use cases:
Perfect for remote work hunters, freelance contract seekers, or anyone tired of LinkedIn's algorithm roulette. Tech startups loved it for quick hires, but individual devs got the most mileage. If you're in software engineering, data science, or full-stack, it felt custom-made. What set it apart from, say, Indeed or Dice?
The deep AI personalization - not just keywords, but actual skill embeddings that understood nuances like 'microservices' versus 'monoliths.' Plus, being open-source meant you could peek under the hood on GitHub, which built trust. Unlike bloated platforms, it was lightweight, no ads, just pure matching.
I was torn between it and AngelList at first, but the accuracy won me over. That said, it's discontinued now - bummer, right? The site still points to the GitHub repo, so you can fork the code and run your own version if you're handy. Last I checked, the community lingers on socials. If you're a dev navigating this tough market - with layoffs hitting hard in 2024 - tools like this remind us what's possible.
Check out the repo; maybe it'll spark your next project. Who knows, you might even revive it.
But it worked - at least while it lasted. The main draw? It dramatically reduces the hours you waste on irrelevant listings. Instead of sifting through hundreds of generic dev jobs, the AI analyzes your profile - think React, Node.js, whatever your stack is - and serves up matches that fit like a glove.
We're talking a massive database of over 100,000 jobs, fine-tuned with embeddings to capture semantic similarities. No more applying to roles that say 'developer' but mean something totally different. In my experience, it boosted my application success rate by about 30%, or so I figured from the offers I landed.
Key features included that smart AI matching, easy filters for tech stacks and locations, and integrations with GitHub and Twitter for community vibes. You could tweak your profile with real code samples, and the system would embed them into a vector space to find gigs that align. It solved the big pains: invisibility to recruiters, mismatched opportunities, and the sheer exhaustion of job hunting.
I remember using it to pivot from web dev to fintech - the recommendations were spot on, highlighting roles with GraphQL and AWS that I hadn't even considered. This was geared toward developers at all levels - juniors building portfolios, mid-level folks seeking stability, or seniors eyeing leadership spots.
Use cases:
Perfect for remote work hunters, freelance contract seekers, or anyone tired of LinkedIn's algorithm roulette. Tech startups loved it for quick hires, but individual devs got the most mileage. If you're in software engineering, data science, or full-stack, it felt custom-made. What set it apart from, say, Indeed or Dice?
The deep AI personalization - not just keywords, but actual skill embeddings that understood nuances like 'microservices' versus 'monoliths.' Plus, being open-source meant you could peek under the hood on GitHub, which built trust. Unlike bloated platforms, it was lightweight, no ads, just pure matching.
I was torn between it and AngelList at first, but the accuracy won me over. That said, it's discontinued now - bummer, right? The site still points to the GitHub repo, so you can fork the code and run your own version if you're handy. Last I checked, the community lingers on socials. If you're a dev navigating this tough market - with layoffs hitting hard in 2024 - tools like this remind us what's possible.
Check out the repo; maybe it'll spark your next project. Who knows, you might even revive it.
