Get Shit Done: A meta-prompting, context engineering and spec-driven dev system

Agreed.this paper studied 33k+ agent-authored PRs on GitHub (https://arxiv.org/pdf/2601.15195)

#1 rejection reason: missing context. 80% needed human fixes. Agents can write code fine. They just don't know what "done" looks like in your codebase.

Count successful merges into repos with real history instead of LOC and the hard part is specification, not execution.

Wrote about this topic @ https://www.augmentcode.com/blog/the-end-of-linear-work

This is a great post, thanks for sharing! Over the last couple months I fell into my own unique (but similar) spec driven workflow and couldn’t help but start building my own tooling around it. Since you’ve clearly thought so much about this I would really value any feedback / criticism / reactions you have.

https://acai.sh

I find the added structure of yaml + requirement ids helps tremendously compared to plain markdown -

https://acai.sh/writing-specs

I am still a few days away from open sourcing the stack (CLI / API & Server), plan is to gather as much feedback as I can and decide if this is worth maintaining.

In my view, Spec-Driven systems are doomed to fail. There's nothing that couples the english language specs you've written with the actual code and behaviour of the system - unless your agent is being insanely diligent and constantly checking if the entire system aligns with your specs.

This has been solved already - automated testing. They encode behaviour of the system into executables which actually tell you if your system aligns or not.

Better to encode the behaviour of your system into real, executable, scalable specs (aka automated tests), otherwise your app's behaviour is going to spiral out of control after the Nth AI generated feature.

The way to ensure this actually scales with the firepower that LLMs have for writing implementation is ensure it follows a workflow where it knows how to test, it writes the tests first, and ensures that the tests actually reflect the behaviour of the system with mutation testing.

I've scoped this out here [1] and here [2].

[1] https://www.joegaebel.com/articles/principled-agentic-softwa... [2] https://github.com/JoeGaebel/outside-in-tdd-starter

Question for people who have spent more time than I have wrangling agents to manage other agents:

I've been using a Claude Pro plan just as a code analyzer / autocomplete for a year or so. But I recently decided to try to rewrite a very large older code base I own, and set up an AI management system for it.

I started this last week, after reading about paperclip.ing. But my strategy was to layer the system in a way I felt comfortable with. So I set up something that now feels a bit like a rube goldberg machine. What I did was, set up a clean box and give my Claude Pro plan root access to it. Then set up openclaw on that box, but not with root... so just in case it ran wild, I could intervene. Then have openclaw set up paperclip.ing.

The openclaw is on a separate Claude API account and is already costing what seems like way too many tokens, but it does have a lot of memory now of the project, and in fairness, for the $150 I've spent, it has rewritten an enormous chunk of the code in a satisfactory way (with a lot of oversight). I do like being able to whatsapp with it - that's a huge bonus.

But I feel like maybe this a pretty wasteful way of doing things. I've heard maybe I could just run openclaw through my Claude Pro plan, without paying for API usage. But I've heard that Anthropic might be shutting down that OAuth pathway. I've also heard people saying openclaw just thoroughly sucks, although I've been pretty impressed with its results.

The general strategy I'm taking on this is to have Claude read the old codebase side by side with me in VSCode, then prepare documents for openclaw to act on as editor, then re-evaluate; then have openclaw produce documents for agent roles in Paperclip and evaluate them.

Am I just wasting my money on all these API calls? $150 so far doesn't seem bad for the amount of refactoring I've gotten, across a database and back and front end at the same time, which I'm pretty sure Claude Pro would not have been able to handle without much more file-by-file supervision. I'm slightly afraid now to abandon the memory I've built up with openclaw and switch to a different tool. But hey, maybe I should just be doing this all on the Claude Pro CLI at this point...?

Looking for some advice before I try to switch this project to a different paradigm. But I'm still testing this as a structure, and trying to figure out the costs.

[Edit: I see so many people talking about these lighter-weight frameworks meant for driving an agent through a large, long-running code building task... like superpowers, GSD, etc... which to me as a solo coder sound very appealing if I were building a new project. But for taking 500k LOC and a complicated database and refactoring the whole thing into a headless version that can be run by agents, which is what I'm doing now, I'm not sure those are the right tools; but at the same time, I never heard anyone say openclaw was a great coding assistant -- all I hear about it being used for is, like, spamming Twitter or reading your email or ordering lunch for you. But I've only used it as a code-manager, not for any daily tasks, and I'm pretty impressed with its usefulness at that...]

> gsd is a highly overengineered piece of software that unfortunately does not get shit done, burns limits and takes ages while doing so

That was my impression of superpowers as well. Maybe not highly overengineered but definitely somewhat. I ended up stripping it back to get something useful. Kept maybe 30%.

There's a kernel of a good idea in there but I feel it's something that we're all gradually aligning on independently, these shared systems are just fancy versions of a "standard agentic workflow".