afiodorov · HackerTrans

afiodorov

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Submissions

The Age of Personalized Software: How LLMs Are Changing Programming

afiodorov.github.io

1 pointsby afiodorovvorig jaar0 comments

Show HN: IMDb SQL Best Movie Finder

imdb-sql.com

129 pointsby afiodorov2 jaar geleden81 comments

Show HN: Translate Subtitles Using GPT

subsgpt.com

2 pointsby afiodorov3 jaar geleden0 comments

Show HN: Real-Time Transcription and Translation

livetranslate.net

1 pointsby afiodorov3 jaar geleden0 comments

Releasing LiveTranslate: automatic simultaneous translation

afiodorov.github.io

2 pointsby afiodorov3 jaar geleden1 comments

Show HN: Save your Thoughts on Ethereum network

thoughtful3.eth.limo

2 pointsby afiodorov4 jaar geleden0 comments

Show HN: Radix sort big files in memory

github.com

36 pointsby afiodorov6 jaar geleden32 comments

Computing Rolling Median in Go

afiodorov.github.io

2 pointsby afiodorov6 jaar geleden0 comments

Getting a Musical Note from Audio

afiodorov.github.io

2 pointsby afiodorov7 jaar geleden0 comments

Generating Ethereum Address from Scratch

afiodorov.github.io

78 pointsby afiodorov7 jaar geleden21 comments

comments

27 dagen geledendiscuss

  Location: Las Palmas, Spain
  Remote: Yes
  Willing to relocate: Yes (can work in EU & UK)
  Technologies: Go, Python, Kubernetes, AWS, Apache Spark, Airflow, LangGraph, RAG, gRPC, PostgreSQL, Docker
  Résumé/CV: https://cv.fiodorov.es/
  Email: [email protected]

Senior Backend & AI Engineer with 10+ years of industry experience, including 5+ years in crypto (Kraken / CryptoWatch, Glassnode). Work spans high-throughput Go microservices, large-scale data pipelines (Spark, Airflow, Iceberg, Kubernetes), and hands-on AI product development (LangGraph, RAG, pgvector). Most recently launched AI-driven, company-wide recommendations for crypto tokens & assets at Kraken. Mathematical background: Cambridge MMath, UCL MPhil in Probability (published paper). Looking for senior, autonomous roles at small companies or start-ups where I can drive technical decisions from architecture to production.

vorige maanddiscuss

A RAG search accross all HackerNews comments is back online with a new design: https://hn.fiodorov.es/

8 maanden geledendiscuss

The running costs are very low. Since posting it today we burned 30 cents in DeepSeek inference. Postgres instance though costs me $40 a month on Railway; mostly due to RAM usage during to HNSW incremental update.

8 maanden geledendiscuss

Daily updates I do on my m4 mac air: takes about 5 minutes to process roughly 10k fresh comments. Historic backfill was done on an Nvidia GPU rented on vast.ai for a few dollars. If I recall correctly took about an hour or so. It’s mentioned in the README.md on GitHub.

8 maanden geledendiscuss

I've been embedding all HN comments since 2023 from BigQuery and hosting at https://hn.fiodorov.es

Source is at https://github.com/afiodorov/hn-search

10 maanden geledendiscuss

Apparently Persian and Russian are close. Which is surprising to say the least. I know people keep getting confused about how Portuguese from Portugal and Russian sound close yet the Persian is new to me.

10 maanden geledendiscuss

I've found that building my side projects to be "scalable" is a practical side effect of choosing the most cost-effective hosting.

When a project has little to no traffic, the on-demand pricing of serverless is unbeatable. A static site on S3 or a backend on Lambda with DynamoDB will cost nothing under the AWS free tier. A dedicated server, even a cheap one, is an immediate and fixed $8-10/month liability.

The cost to run a monolith on a VPS only becomes competitive once you have enough users to burn through the very generous free tiers, which for many side projects is a long way off. The primary driver here is minimizing cost and operational overhead from day one.

10 maanden geledendiscuss

Data all-rounder with 10 years building everything from low-latency Go microservices to training ML models to large-scale AWS data pipelines. Looking for a senior, autonomous role at a small company/startup.

  Location: Las Palmas, Spain
  Remote: Yes
  Willing to relocate: No
  Technologies: Go, Python, SQL, Kubernetes, Docker, AWS (S3, EMR, RDS, Aurora, Athena), Apache Spark, Apache Airflow, TypeScript, React, gRPC, REST APIs, PostgreSQL, Google BigQuery, LangChain, LangGraph, RAG, faster-whisper
  Résumé/CV: https://cv.fiodorov.es
  Email: [email protected]

10 maanden geledendiscuss

RAG search that contains all HN comments since 2023

https://hn.fiodorov.es

I treat it more like a homework exercise for a Coursera course but I like the result.

10 maanden geledendiscuss

> It was uncomfortable at first. I had to learn to let go of reading every line of PR code. I still read the tests pretty carefully, but the specs became our source of truth for what was being built and why.

This is exactly right. Our role is shifting from writing implementation details to defining and verifying behavior.

I recently needed to add recursive uploads to a complex S3-to-SFTP Python operator that had a dozen path manipulation flags. My process was:

* Extract the existing behavior into a clear spec (i.e., get the unit tests passing).

* Expand that spec to cover the new recursive functionality.

* Hand the problem and the tests to a coding agent.

I quickly realized I didn't need to understand the old code at all. My entire focus was on whether the new code was faithful to the spec. This is the future: our value will be in demonstrating correctness through verification, while the code itself becomes an implementation detail handled by an agent.

vorig jaardiscuss

  sign of serious organizational disfunction.

You're not wrong, but it's a "dysfunction" that many successful tech companies have learned to leverage.

The reality is, most engineers spend far less than half their time writing new code. This is where the 80/20 principle comes into play. It's common for 80% of a company's revenue to come from 20% of its features. That core, revenue-generating code is often mature and requires more maintenance than new code. Its stability allows the company to afford what you call "dysfunction": having a large portion of engineers work on speculative features and "big bets" that might never see the light of day.

So, while it looks like a bug from a pure "coding hours" perspective, for many businesses, it's a strategic feature!

vorig jaardiscuss

I live next to an abandoned building from the Spanish property boom. It's now occupied illegally. Hype's over yet the consequence is staring at me every day. I am sure it'll eventually be knocked down or repurposed yet it'd be better had the misallocation never happened.

vorig jaardiscuss

The crux of the article is asking whether such a large investment is justified; downplaying the article saying it's only X% of the GDP compared to Y doesn't address the issue.

vorig jaardiscuss

Nice clip yet it does not make it clear why 9% is the good value of GDP. Why not 7%?

vorig jaardiscuss

My rule of the thumb is that Dataclasses are for compile-time type-checking, pydantic classes are for run time type checking.

vorig jaardiscuss

You're right, they can try to manipulate you on a thousand tiny things. My counter-argument is that at a certain point, it's not worth the mental energy to fight over what amounts to pennies on the dollar.

Anecdotally, when I bought my car recently, they forgot to even offer me the extended warranty they'd planned to push. I find it funny to think it was so minor, even they forgot to care.

vorig jaardiscuss

Let's be clear: it's entirely possible to leave the "herd". People can and do go completely off-grid and thus disengage from capitalism. The crucial point is that the vast majority of us choose not to. That choice is what makes your "slowest antelope" analogy so much more complex.

An antelope's greatest desire is to be in the herd, because while it may contain a lion, the world outside contains a thousand wolves.

We've built a herd—society—that is incredibly effective at holding those wolves at bay: famine, plague, and chaos. We willingly participate because it provides "shields" our ancestors could only dream of. The problem isn't the herd itself; it's the lion that we allow to stalk within it.

What I am suggesting isn't to abandon this safety and comfort brought by modern capitalism. It's to improve the herd—to enjoy its protections while finding ways to tame, cage, or evade the lion of exploitation. What we're discussing here aren't futile attempts to escape, but vital tactics for building a better, safer herd for everyone.

vorig jaardiscuss

There's nothing an algorithm can do against disciplined, intentional engagement.

If you know which car you want to buy it doesn't matter what the salesman has to say.

vorig jaardiscuss

We should not underestimate the timeless human response to being manipulated: disengagement.

This isn't theoretical, it's happening right now. The boom in digital detoxes, the dumbphone revival among young people, the shift from public feeds to private DMs, and the "Do Not Disturb" generation are all symptoms of the same thing. People are feeling the manipulation and are choosing to opt out, one notification at a time.

vorig jaardiscuss

We've been visited by alien intelligence that is simultaneously fascinating and underwhelming.

The real issue isn't the technology itself, but our complete inability to predict its competence. Our intuition for what should be hard or easy simply shatters. It can display superhuman breadth of knowledge, yet fail with a confident absurdity that, in a person, we'd label as malicious or delusional.

The discourse is stuck because we're trying to map a familiar psychology onto a system that has none. We haven't just built a new tool; we've built a new kind of intellectual blindness for ourselves.