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Joined 1 year ago
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Cake day: June 14th, 2023

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  • No worries, sounds like you’re definitely on the right track with your approach.

    In terms of the style of editor I don’t have a strong preference, I think the most important thing is discoverability which generally means putting docs where they are expected to be found and using whatever your team or org is using. Personally I have a slight preference for markdown mainly because it’s easy to version control, see who wrote what (so I can ask them questions) and use all the tools I’m used to that work well with plain text. Tools that use more WYSIWYG style can be good too though and many of them like Notion have the advantage of making it relatively easy to search across your entire companies documentation assuming everyone uses the one tool.

    For my personal notes I use Logseq which I highly recommend. It’s a bit of both, markdown under the hood but with a simple editor that lets you focus on writing notes, tasks and links.


  • I would say as a new junior dev you are uniquely placed to help with this. Documentation tends to be written by people who know a lot about a thing and they try to imagine what might be useful for someone. Someone new coming in with a fresh perspective can help uncover assumed knowledge or missing leaps to make the documentation better. One of the common onboarding steps I’ve seen is to go back and update/improve the onboarding docs after you’ve just been onboarded for example.

    I would say pick your battles though because documentation can be a never ending task and documents are almost always out of date shortly after they are written. Think about what would have saved you time or mental overhead if it was just written down and fix those first.

    As far as organising and writing, every place is different and it can depend on the tools your org is using. In general I’d at least have links to relevant docs as close to where they might be needed as possible. Like how to set up and get up and running with a code base should probably be documented directly in the readme, or at least linked to if it’s overly complicated.

    Hopefully that’s at least somewhat helpful. It’s definitely a problem basically everywhere I have worked though, you have to do what you can and not stress too much about it.


  • I dunno, it’s already pretty good at writing code and only going to get better. I agree with your conclusion though, mainly because as a software engineer writing code is actually not even the most complicated part of the job. If an AI could write perfect code every time it’d make my job a lot easier but I’d still have to do a significant amount of work such as:

    • Figuring out which code to write in the first place! Work discovery if I’m senior enough or clarifying requirements.
    • Co-ordination with other teams. Depending on the exact work this becomes more or less important
    • Managing the lifecycle of a change including testing, deployment, monitoring and triaging issues.
    • Ongoing maintenance. Staying on top of upcoming changes in adjacent or foundational teams, making sure our stuff will keep in working.
    • Architecture design. You mentioned this in your post, understanding interactions with adjacent systems and how to organise our own systems to meet current and (reasonable) future requirements.
    • Conducting non project work such as interviews, involvement in working groups to help decide overall technical direction of my group, upskilling myself and those around me.

    That’s just off the top of my head, I’m sure I’ve missed some things. As much as I love writing code I honestly feel like if an AI could do that part it’d just take stress out of my day and give me more time to focus on those other parts of the job. Of course in reality more work would probably just be piled on but that’s just life I guess.








  • There is a lot of good stuff there but it’s still opaque when it comes to bias specifically. I mean, am I missing somether here? I genuinely feel like there must be a whole section I’ve missed or something based on some of the other commenters. The bias methodology is no more a methodology than “grind up some wheat, mix some water and yeast before chucking it in the oven for a bit” is a recipe for bread. You rate 4 categories from 0 - 10 and average it, but the ratings themselves are totally subjective.

    Story Choices: Does the source report news from both sides, or do they only publish one side.

    What does this even mean? If a site runs stories covering the IPCC recommendations for climate action but doesn’t run some right wing conspiracy version of how climate change is a hoax, is that biased story selection?

    What did I miss here?