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andreyandrade

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1 points·by andreyandrade·6 mesi fa·0 comments

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1 points·by andreyandrade·6 mesi fa·0 comments

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1 points·by andreyandrade·6 mesi fa·0 comments

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1 points·by andreyandrade·6 mesi fa·0 comments

Why AI Gave Me the Wrong Answer While Knowing the Right One

andreyandrade.com
2 points·by andreyandrade·6 mesi fa·3 comments

Reddit Has Become the Internet's Strip Mall

pontozero.info
25 points·by andreyandrade·6 mesi fa·35 comments

[untitled]

1 points·by andreyandrade·6 mesi fa·0 comments

Market Saturation Radar

pontozero.info
1 points·by andreyandrade·6 mesi fa·1 comments

comments

andreyandrade
·6 mesi fa·discuss
Remote work is effective—why the RTO mandates? | Heejung Chung | TEDxLondonBusinessSchool https://www.youtube.com/watch?v=_xHQWLjE6xQ
andreyandrade
·6 mesi fa·discuss
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.
andreyandrade
·6 mesi fa·discuss
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.
andreyandrade
·6 mesi fa·discuss


  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.
andreyandrade
·6 mesi fa·discuss
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.
andreyandrade
·6 mesi fa·discuss
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.
andreyandrade
·6 mesi fa·discuss
Built a crawler to analyze 6,380 posts from TabNews (Brazilian dev community) and turned the data into an interactive infographic. Found that AI/ML dominates ~50% of discussions, Monday 8am is the best time to post, and longer titles (100+ chars) actually perform better.

  Stack: Python for scraping, pure HTML/CSS for the viz. No JS frameworks needed.
https://andreyandrade.com/static/tabnews-2025/
andreyandrade
·6 mesi fa·discuss
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?
andreyandrade
·6 mesi fa·discuss
In the past, technical friction acted as a 'natural quality filter.' Today, curation and distribution have become the new bottlenecks. 'Vibe coding' is creating software inflation—when software becomes too cheap to produce, the real value migrates toward trust and brand.
andreyandrade
·6 mesi fa·discuss
Ponto Zero scores markets 0-100 based on: - Number of established players - Market concentration - Entry barriers - Growth rate - Sector maturity

Examples: Food Delivery (92/100 - Critical), Elder Care Tech (28/100 - Low).

Stack: Pure Go, LevelDB, server-side HTML, zero JS frameworks. Loads <1s.

Currently ~80 markets analyzed. Open to suggestions for markets to add.

Feedback welcome – especially on methodology improvements.