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#pybeach — Public Fediverse posts

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  1. On Saturday I attended PyBeach, my local Python conference. Here's a summary to give you a taste of it: bernat.tech/posts/pybeach-2026. If you're interested in Python, I recommend joining next year!

  2. Slowly trying to catch up on 650 posts from mastodon like an animal. Seeing #PyBeach in my timeline, I wish it didn’t collide with my racing again this year. Someday…

  3. RE: mastodon.social/@RonJeffries/1

    Yesterday at #pybeach, I mentioned that a relatively common AI tooling error is reversing negation... here's an example 😅

    (Thanks for sharing it, @RonJeffries !)

  4. And just like that, #pybeach is over. What a lovely conference and what a lovely group of people. I feel lucky to be able to call them my friends. ❤️

  5. (this was in my drafts, but didn't go out!) Final (non-lightning) talk of the day, @MaggieFero explains the importance of good documentation practice, regardless of who is reading it.

  6. @phildini is it "3 (or whatever) ways to put something on the internet" because you didn't want to write "3 or 4" after this week? #pybeach

  7. tl;dr: continue writing useful docs well. 🫠

    @MaggieFero #PyBeach

  8. @MaggieFero documenting anti-recommended settings is far more risky in the age of LLMs. The chance of negation means that AIs might recommend the settings you don’t want used.

    #pybeach

  9. @MaggieFero the reading attention span of users has only decreased, and keeping this in mind only compounds with LLM context limits.

    The LLM doesn’t have an “attention span”, but if the doc is too big it can’t fit in context and won’t be tokenized into a representation that returns authoritative results.

    #pybeach

  10. @MaggieFero

    For the age of AI, it’s more important than ever to write docs for a specific audience, as well as match queries well using GEO or AEO techniques

    (Generative engine / answer engine optimization)

    News items perform well, mixed content appears less authoritative, content length impacts relevance

    #pybeach

  11. "generative engine optimisation (GEO); answer enging optimisation (AEO)" - @MaggieFero
    "Old McDonald had a farm (EIEIO)" - Me

    #PyBeach

  12. @MaggieFero AI greatly improves discovery

    - secrets in commits
    - creds in commits
    - live keys in common crawl

    Credential abuse is still 13% of breach causes. Security by obscurity is already failing, AI makes it even worse

    #pybeach

  13. @MaggieFero docs can impact security!

    Preset auth material (default passwords), anti-recommended settings, and revealing potential vulnerabilities are all potentially impactful and regularly show up in docs

    #pybeach

  14. Up next at #pybeach, @MaggieFero is covering “Technical Documentation in the Age of LLMs”

    Things may not be as different as you think!

    Also this talk will cover most of what we currently call AIs or LLMs

  15. “oh shit, it’s a certificate key!” #pybeach

  16. In closing his #pybeach talk, @andrew informs us all that mountain rescue in the US is always free, and they'd rather be called sooner than later if you think you might need it.

    As a security professional, please also notify us sooner than later if something feels weird, whether you clicked a link that felt wrong in retrospect or a process is suddenly taking an unexpected length of time. Most of us wanna help!

  17. CW: discussion of peril

    Software systems aren't just code. @andrew @ #pybeach

  18. CW: discussion of peril

    "Heroics hide process failures"; "every near miss is a massive gift to you" because you can learn and adapt without experiencing the full consequences of the incident. Avoid the same one happening twice if you can, though. - @andrew @ #pybeach

  19. CW: discussion of peril

    "It is human nature to ignore risk" and everyone does it all the time. You have to accept some amount of risk, but it's important to address head-on and acknowledge.- @andrew @ #pybeach

  20. "Clear leadership is critical": "rescue is not a democracy", advice must be considered but you need a clearly accountable individual who can make the call. You can't do everyone's thing every time. - @andrew @ #pybeach

  21. extremely important point from @andrew: safety culture has *two* parts:

    1) blamelessness
    2) everyone can meaningfully say "stop"

    tech organizations tend to do reasonably-well at (1) and utterly lack (2)

    #pybeach

  22. CW: discussion of peril

    Practice incident response, and practice it proportionate to how often that type of incident occurs (with some extra reps on higher-risk areas).

    Leave time in your schedule for problems to happen! If you're scheduled 100% of the time, you have no margin of error.

    Try to move slowly and steadily, with small, frequent releases. Big jumps are riskier.

    Have a safety culture: blameless is good, but also every single person must be able to call stop and *actually* cause an evaluation. That's not to say you should never tolerate risk, but that you should consider it carefully.

    - @andrew @ #pybeach

  23. CW: discussion of peril

    In software, we can limit the scope of what we collect, by not creating user data unnecessarily, for example. Also, we have the opportunity to cheaply roll back our mistakes. They're not literally set in stone like some other disciplines' mistakes may be.

    In mountain rescue, if there's a problem with a rope system for example, someone may already be over the edge and fully dependent on it, so you can't fix that. - @andrew @ #pybeach

  24. CW: discussion of peril

    Mountain rescue teams can help handle some risk by building a safety culture, training in advance, and having a clear chain of command to reduce duplication of work. - @andrew @ #pybeach

  25. CW: discussion of peril

    Andrew also introduces the risk matrix: likelihood of occurring and severity of consequences if it occurs. In mountain rescue, you're guaranteed high consequences and that it's dangerous (you didn't get called out to have tea).

    We also have risk in our codebases, but we can likely impact both the likelihood and the consequences, using some of the same levers that mountain rescue teams use. - @andrew @ #pybeach

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