Top all-time · #12795
Bartosz Mikulski
Personal blog · mikulskibartosz.nameaiprogrammingdata
Bartosz Mikulski's personal blog at mikulskibartosz.name covers ai, programming and data. Since 2017, 6 different Hacker News readers have linked it 11 times. It is still writing: the last post was on 2026-09-19, and you can follow it by feed.
Too few sampled comments (2) to say how often HN recommends it.?
Why HN links it
Linked posts cover search engine spam and SEO, and a git workflow for organizing commits into reviewable units. Comments discuss Google voting manipulation and rebasing in git.
Summarised by Claude from a sample of 2 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
AI & MLOps Engineer. I build production-ready data and ML systems that survive the real world. Specialist in Reliable RAG, MLOps, and Data Platforms.
What Hacker News says?
Randomly select votes that are actually recorded. Then add in metavoting that votes on the votes with random sampling. At Google's scale with a sufficiently random sampling you'd be extremely hard pressed to successfully brigade or spam the voting. Google could easily use its current fingerprinting to constrain (to an extent) multiple votes. Even knowing only a portion of the population will participate in the votin…
Comment linking /wilson-score-in-python-example/
on “Search engines and SEO spam”Submitted TypeSafe's Jev Can't See. I Made It Guess What I Drew Anyway as a story · 3 points
HN discussionThe reset part seem superfluous, most of this can be handled via rebasing. In fact, this is exactly what we do at <day job>. Much like the thesis of this article, the goal is to have a set of well organized commits so that when it comes time to do a PR review, you have 1-3 logical units of change and it also improves the ability to do reverts. But you can very easily do this just by rebasing instead of resetting and…
Comment linking /git-fixup-explained/
on “A Better Git Flow”Submitted AI Workflow Patterns with PydanticAI (based on Anthropic agents guide) as a story · 3 points
HN discussionSubmitted A “known bug” is still a bug as a story · 3 points
HN discussionSubmitted How to become a data engineer for free as a story · 2 points
HN discussionSubmitted Putting machine learning models in production using Flask, Docker and Kubernetes as a story · 2 points
HN discussionSubmitted In defence of whiteboard interviews as a story · 2 points
HN discussionSubmitted Graphical Explanation of Advanced RAG: Query Expansion, HyDE, ReRanking, etc. as a story · 1 points
HN discussionSubmitted How to replace your data analyst with an AI-powered Slack bot as a story · 1 points
HN discussionSubmitted Extreme ownership and taking responsibility in software engineering as a story · 1 points
HN discussion