andreyandrade

Joined 10 months ago

Karma
4
Submissions
18
Member since
Dec 31
Senior Backend Engineer with 22+ years of experience building high-performance systems. Go specialist since 2012, prior to version 1.0. Founder of https://stickybit.com.br, where he develops solutions that replace expensive SaaS with custom systems up to 100× more efficient.

Porto Alegre | https://stickybit.com.br | https://ligadous.com

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Recent submissions

Comment · 10 months ago
Comment · 10 months ago
Right, but that's retention for legal defense — they keep everything. The selective hiding is a different layer. They retain it, they just choose when to surface it. So users get "deleted" as UX theater while the data sits in cold storage waiting for subpoenas or PR fires. The irony is the same infrastructure that protects them in copyright suits also lets them curate what investigators see. Retention and visibility are decoupled by design.
Comment · 10 months ago
The technical implication here is that 'deleted' or 'hidden' doesn't mean gone. It’s interesting to see the tension between GDPR-like 'right to be forgotten' and the need for data preservation in legal investigations. However, selective hiding based on PR risk is different from automated safety filters. It suggests a manual layer of intervention that most users aren't aware exists.
Comment · 10 months ago

  I see current AIs as tools—a sophisticated lathe, not a thinking partner. The question isn't whether it "knows" anything.

  The interesting question is: why does AI with correct information in its weights still give wrong answers? That's an engineering problem, not a metaphysics problem.

  But here's what bothers me about the "AI doesn't truly know" argument: do we? When a senior dev answers "use Kubernetes" without asking about team size or user count, are they "comprehending" or pattern-matching on what sounds authoritative? The AI failure I described is identical to what I see in human experts daily.

  Maybe the flaw isn't unique to AI. Maybe it's a mirror.
Comment · 10 months ago
Works for large projects with active communities (Ghostty has both). The filter pays off when volume is high. Doesn't work for smaller projects where every report matters and you want to lower barriers. The brutal honesty ("80-90% of you are wrong") is refreshing but may alienate contributors. A middle ground would be issue templates with mandatory checklists, filters without adding an extra step.
Comment · 10 months ago
Interesting timing. I just analyzed TabNews (Brazilian dev community) and ~50% of 2025 posts mention AI/LLMs. The shift is real. The 2014 peak is telling. That's before LLMs, before the worst toxicity complaints. Feels like natural saturation, most common questions were already answered. My bet, LLMs accelerated the decline but didn't cause it. They just made finding those existing answers frictionless.
Comment · 10 months ago
Comment · 10 months ago
Great execution! The multi-source aggregation approach is smart - averaging warnings from 5+ governments gives a more balanced picture than relying on a single source. The comparison feature is particularly useful for trip planning. Have you considered adding historical data to show if a country's safety rating is trending up or down over time?

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