I used Orca for ages and that was great; I'm just tired of having to scroll back through a convo to find that "one last blocking question" that Claude or Codex spit out 15 tool calls and subagent messages ago.

Building my own tool is super fun though...

Why?

The underlying conversation has nothing to do with the work. That there is one context window is an implementation detail.

I've built one of these for myself, and instead it shares questions, plans, findings, assumptions as distinct UI elements. The conversation is hidden: your focus is on "what's next".

Are there other meta-harnesses doing the same thing? I'd love to stop building my own and use a product someone else has already built!

Maisem Ali writes about how they have not stopped engineering despite handing production of code over to AI. I think that's an interesting perspective for a few reasons, but most of all, I'm not sure I agree.

First, we see a prime example of how that can blow up. "botd died this month. It crumbled under its own weight." It's hard to imagine how an agent harness (or is it an overlay on top of other harnesses?) could crumble under its own weight from sheer technical complexity. What makes a tool like this "crumble"? If properly architected, it seems that any outside change could be adaptable. Failing tests could be fixed.

This AI coding evolution has given us the ability to spin up prototypes we don't understand the inner workings of, but I believe for anything of value (and, I would argue, botd appeared to have value to Maisem) we should at the very least understand and influence the architecture and engineering of what we're building. If Maisem had done that for botd, it would not and _could not_ have "crumbled under its own weight". Whatever outside influence required change within botd would have been manageable.

Second, the off-loading of the production of this article indicates to me a lack of respect (with no offence to Maisem, because this is what much of the industry is doing today) for the value in thinking through the writing process. There's a lot that I've learned personally about software I worked on that only came to me through trying to write explainers. Taking a step back from the software we build and looking at it from a birds-eye view, to share how it is constructed or how to use it, helps develop our understanding.

Maisem's article is already very good, and I hope that is demonstrative of their own writing! I would read more! But I want to read words written by a person for other people. AI can help edit, it can help us build ideas, but in code and in our written word, AI should not be _the author_.

FWIW the tool I’ve built has no built-in ereader because I use apps like Apple Books or my kobo to read. i don’t need another half-built ereader

Looking forward to seeing what comes next for Bookshelf!

Bookshelf, for example -- what possesses someone to make an ebook library that _only works on object storage_? Is this a weekend project, answering the question of "what would this look like"? Or was it something the author wanted for a long time?

Imagine what’s possible if you had GLM-5.2 turned into a hardware chip like this.

https://digits.com/downloads/beyond-the-hype-evaluating-llms...

I've been wondering, since you're building desktop software, how do you get AI to test your changes? Boot the whole app? Run the frontend/UI with a mock backend?

Immediately I started thinking how nice it would be to use natural language to have LLMs generate a deterministic filter for stories matching content I DO care about, filtered from New. Instead of filtering it out.