gurachek

4 ms·

1.
by gurachek 3mo ago
I think engineers are misreading part of the 2026 job market. Some roles are not being eliminated. They are never being created. That distinction matters because layoffs recover cyclically, which may not be the case with non-backfilled role
2.
by gurachek 6mo ago
Yeah, I think so. So far, Claude Opus is the only model I found that doesn't fold under the minimal pressure and can push back, but still - push just a little bit harder and it's back to "appear productive and useful to the u
3.
by gurachek 6mo ago
I had exactly this between two LLMs in my project. An evaluator model that was supposed to grade a coaching model's work. Except it could see the coach's notes, so it just... agreed with everything. Coach says "user improved
4.
by gurachek 6mo ago
The examples in the article are all big scary wipes, But I think the more common damage is way smaller and harder to notice. I've been using claude code daily for months and the worst thing that happened wasnt a wipe(yet). It needed to
5.
by gurachek 6mo ago
The compounding booboos bit is the key insight here. Humans are a bottleneck and that bottleneck is actually load-bearing. You feel the pain of bad decisions slowly enough to course correct. I've been building the same AI product for m
6.
by gurachek 6mo ago
Raw audio is a cool idea! I've seen a similar approach in other domains, "keep the source of truth accessible so you can verify the AI output against it". I wouldn't go as far as "no place in medicine" though.
7.
by gurachek 6mo ago
The float comparison slider is great. One thing from practical experience - the quality gap between model sizes shows up in a way benchmarks don't capture. I have a system where a smaller model generates plans and a larger model can ov
8.
by gurachek 6mo ago
The union rep gets it - people improvise when you cut their tools and then threaten discipline for improvising. That memo is how you make staff hide things instead of asking for help. The scarier part though is that LLM-written clinical not
9.
by gurachek 6mo ago
Yeeah, LLMs are the perfect procrastination tool because they feel productive. You're "learning", you're "exploring", you're having this great conversation about the problem. And then you close the tab and
10.
by gurachek 6mo ago
Your "no compiler" rule on day 3 taught you more than the LLM did. The LLM made concepts click. But the binary search vanishing under interview stress proves that understanding something and being able to produce it under pressure
11.
by gurachek 7mo ago
I wrote this after going through Fabric HQ's data. The 61% stat surprised me - the cheating actually works, at least for now. Happy to discuss the implications.
12.
61% of interview cheaters passed detection(prepto.tech)
2 points by gurachek 7mo ago|1 comments
13.
by gurachek 7mo ago
Forgot to include: answers not stored. Here is DB schema(content hash is to save money on requests with the same answer): | # | column_name | data_type | |----|--------------|------------
14.
by gurachek 7mo ago
I built this because it's easier for me to treat interview & job search as a math game, and math needs numbers(lol?). The original component works with voice, because engineers delivery collapse under interview pressure and it&#x27
15.
Show HN: Free tool that scores your interview answers on 4 dimensions(prepto.tech)
1 points by gurachek 7mo ago|2 comments
16.
Show HN: Prepto.tech – Interviews are simple with AI (no cheating)
1 points by gurachek 1y ago|0 comments
17.
Preparing for Senior PHP Symfony Developer Role at Clubee(prepto.tech)
2 points by gurachek 2y ago|0 comments
18.
by gurachek 4y ago
Hey guys! It's a concept at the moment. But still, what do you think about such a tool if it's real? Should I invest more time building such stuff?
19.
Show HN: AI-based learning roadmaps for developers(indiehackers.com)
1 points by gurachek 4y ago|1 comments