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Posted by Heidi Waterhouse

https://heidiwaterhouse.com/generationship-wayfinder/

https://heidiwaterhouse.com/?p=11342

I was on the Generationship podcast to talk about Progressive Delivery!

Rachel Chalmers and I talked about how to think of Progressive Delivery in the context of CI/CD and observability, and then we got into the nitty-gritty of what I think about AI and how it intersects with user choice.

My favorite pullquote:

When we realized that we needed continuous delivery to do faster releases and get more value from our work in a more immediate way, that was really revolutionary to say, releasing faster makes you safer, makes your product better, that was astonishing. But we felt like we had left something out, and what we had left out was the user experience.

Transcript

https://heidiwaterhouse.com/generationship-wayfinder/

https://heidiwaterhouse.com/?p=11342

Posted by Heidi Waterhouse

https://heidiwaterhouse.com/ldx3-how-to-write-right-now/

https://heidiwaterhouse.com/?p=11335

I count Lead Dev London 2016 as my “breakout” conference. I gave a talk about The Seven Righteous Fights, which I’ve covered in more depth at the #7fights tag. So imagine my delight when I was invited back for Lead Dev’s 10th anniversary bash!

I talked about technical writing and AI. The video is here and the slides are here. You’ll need a LeadDev account to view the video, but it’s free, and honestly, you’ll benefit from a lot of amazing content.

Direct link to How to Write Right Now

The main thing I wanted to convey in this talk is that the hard part of technical writing is not figuring out what order to put words in. Indeed, an LLM can do a medium job of that given a sound prompt. The hard part is thinking through the context that makes it useful to the people reading it.

I think that it’s easy and buzzy to think about AGI or generative tools. That’s not where I see the real value of machine learning. I think it’s going to be in specific tools that have a narrow focus and can do as well or better than humans at a small set of tasks, precisely because they can sift so much data.

What that means for technical writing is that there are a lot of places you can use “AI” to write documents for procedures and topics that are predictable, well-formed, semantically reliable.

• APIs? Yes, absolutely.
• Procedures that have stable and mature test suites? Sounds great.
• Release notes in a system with trustworthy and well-defined bug tracking? Probably.
• Tracking the programming decisions made that got everything the way it was? No, but humans don’t do that either, so whatever.
• Conceptual explanations that cross domain boundaries? No. Please don’t try.

I then took some time in the talk to go through tools that are (as of mid-June 2025) useful for parts of the writing process.

Mostly, I want you to remember that generative AI is risky, because it doesn’t know what is true, but that other kinds of machine-assisted writing can be good and useful if you don’t imagine they’re magical.

https://heidiwaterhouse.com/ldx3-how-to-write-right-now/

https://heidiwaterhouse.com/?p=11335