Who is in your developer "community"?

I was recently talking with some people (mostly developers) who had a very narrow idea of the concept of "community" (in relation to a software product) and who is in it. They thought it only referred to people who shared their opinions on social media.

Whether "community" is the right, or best, term is also much debated.
Some feel "ecosystem" is better.
I've seen "community" used much more, so I'll go with that.

Either way, my list is much larger, and there are lots of different types of people on it: 

People online:

• "Keyboard warriors"
• "Fan boys" (and girls)
• FOSS purists
• Influencers
• Press

People who build with the product:

• People who write code using the product
• Hobbyists
• Students
• Start ups
• Small businesses
• Large businesses
• Enterprises

People who choose the product:

• Trial users
• People "evaluating" software
• Those researching the company/software

People affected by the product:

• People who work with people who write code
• The people who pay for the products used to write the code
• The people who use the software created with code written with your tools/products

People with an external interest in the product:

• People building the product
• External contributors
• Partners
• Resellers
• Those providing integrations

Others:

• Bots?
• Competitors?

Who have I missed?

Thinking about ALL the people who are affected by and interested in your software can be much more helpful than placing undue attention and effort on a vocal minority....

Code AI can't write? - I have 6 examples

I was recently at a software development conference where there was a heavy emphasis on getting developers to use AI to write more code, rather than them typing it.

As part of the Q&A, I asked if the panel thought there were any circumstances where AI shouldn't be used to write code or where it wasn't appropriate.

They said that, as AI was being used to write the frameworks that developers are building on top of, they couldn't see a reason not to have AI write the code.

Being nervous of absolutes, and knowing how varied developers and the software they build are, I quickly came up with six scenarios where developers can't (or shouldn't) "just" point an agent at their codebase and tell it what to do:

1. Code is written and exists in an air-gapped environment (so on machines without access to the internet) for security or privacy reasons. This means Claude, ChatGPT, Copilot, or similar can't look at it. [Yes, I acknowledge that as an alternative, you may be able to use an agent with a local model, but you won't have access to the latest tools and may need very high-spec (so expensive) machines to run those models on. Time spent managing and maintaining such tools must also be considered.]
2. Code that you don't want the AI [company] to see. Similar to the above, but where you don't want to, or can't legally, let another company see your code or the data it uses. [Again, a local agent/model may be an option here.]
3. Code that is very hard to test in an automated way. If the code needs complex integrations with other systems that can't easily be mocked or abstracted, especially if it requires specific hardware to interact with, the AI agent is unlikely to be able to do and test everything for you. It may think it's finished, but you wouldn't accept untested code from a person, so why accept it from an AI agent?
4. Code that uses very obscure APIs. In my experience, when the AI hasn't been trained on the APIs you want (and need) to use (because there just aren't very many--or any--examples on the internet for it to learn from), then the AI can easily start hallucinating the methods it wishes existed, or it might even be reasonable to assume should exist. When this happens, it takes a person to correct what the AI has done/tried, and it can be easier to have a person do it in the first place, rather than have to fix the invalid approaches.
5. Code that requires a small and specific change. If the change is small and you know what needs changing and where, it can be quicker and easier to do it by hand rather than trying to describe what the AI should do. (And not have AI make other changes at the same time.)
6. Code you write for fun. Ignoring the challenge of finding an employer to pay you for the things you find fun; if, as a developer, you find writing code fun, then there's no reason you have to stop. It may not be how you earn a living, but that doesn't mean you can't write code by hand at other times.

I'm sure there are more. What have I missed?

Is "QA" just about manual testing?

I've seen recent viral posts that imply it is.

I think differently.

QA is (or, at least should be) a lot more than manually testing software.

What are you (or they) assuring the quality of?

- Software, yes! (Obviously?)

- All customer engagement? (From marketing to ongoing support?)

- Internal processes and interactions? (Even hiring, and onboarding?)

- Every part of the business?

What are the consequences of people who are excused from having to think about, or the responsibilities related to, ensuring that all they do is of an acceptable (& presumably high) standard?

VS [Code] Marketplace error: "An item with the same key has already been added."

 If you're very unlucky and when trying to upload a new extension to the VSCode marketplace, you may get this error: "An item with the same key has already been added."

If you use the website, you may see this (not particularly helpful) error message.

Of course, you really should be using an automated, repeatable process/script to manage your submissions, and if you do that, you'll still get the same result. (I only tried the website after all other attempts to work out what the duplicate key might be.)

Error: An item with the same key has already been added.

Error: Process completed with exit code 1.

Anyway, for me, it turned out that we had content types for both "json" and ".json" defined. (With and without the leading dot.)
Some systems don't mind this, while it turns out the marketplace does.

I hope this helps someone else find a solution to their problems faster than I did. (10 emails, back and forth with support over 11 days!)

Human questions to ask in code reviews

Automated (AI) powered code reviews are becoming increasingly popular and powerful. I use them myself to catch things I miss.

But there are questions I ask as a human reviewer that I've yet to see any AI-powered tooling help with.

 Questions like:

• Does this fix the cause or the symptoms?
• Are there related changes that should be addressed while we're in this part of the codebase?
• Is this just fixing a problem or actively making things better for the user? (They aren't always the same.)
• Do we have related docs or samples that need correcting/updating or adding to?