It absolutely tore through tokens though. I don't normally hit my session limits, but hit the 5-hour limits in ~30 minutes and my weekly limits by Tuesday with GSD.
This is the real challenge. The people I know that jump around to new tools have a tough time explaining what they want, and thus how new tool is better than last tool.
There's some VC money interest but I'd classify more than 9 / 10ths of it as good old fashioned wildcat open source interest. Because it's fascinating and amazing, because it helps us direct our attention & steer our works.
And also it's so much more approachable and interesting, now that it's all tmux terminal stuff. It's so much more direct & hackable than, say, wading into vscode extension building, deep in someone else's brambly thicket of APIs, and where the skeleton is already in place anyhow, where you are only grafting little panes onto the experience rather than recasting the experience. The devs suddenly don't need or care for or want that monolithic big UI, and have new soaring freedom to explore something much nearer to them, much more direct, and much more malleable: the terminal.
There's so many different forms of this happening all at once. Totally different topic, but still in the same broad area, submitted just now too: Horizon, an infinite canvas for trrminals/AI work. https://github.com/peters/horizon https://news.ycombinator.com/item?id=47416227
Another great technique is to use one of these structures in a repo, then task your AI with overhauling the framework using best practices for whatever your target project is. It works great for creative writing, humanizing, songwriting, technical/scientific domains, and so on. In conjunction with agents, these are excellent to have.
I think they're going to be a temporary thing - a hack that boosts utility for a few model releases until there's sufficient successful use cases in the training data that models can just do this sort of thing really well without all the extra prompting.
These are fun to use.
I started with all the standard spec flow and as I got more confident and opinionated I simplified it to my liking.
I think the point of any spec driven framework is that you want to eventually own the workflow yourself, so that you can constraint code generation on your own terms.
It's hard to say why GSD worked so much better for us than other similar frameworks, because the underlying models also improved considerably during the same period. What is clear is that it's a huge productivity boost over vanilla Claude Code.
It is perhaps confirmation bias on my part but I've been finding it's doing a better job with similar problems than I was getting with base plan mode. I've been attributing this to its multiple layers of cross checks and self-reviews. Yes, I could do that by hand of course, but I find superpowers is automating what I was already trying to accomplish in this regard.
I've been poking at security issues in AI-generated repos and it's the same thing: more generation means less review. Not just logic — checking what's in your .env, whether API routes have auth middleware, whether debug endpoints made it to prod.
You can move that fast. But "review" means something different now. Humans make human mistakes. AI writes clean-looking code that ships with hardcoded credentials because some template had them and nobody caught it.
All these frameworks are racing to generate faster. Nobody's solving the verification side at that speed.
Saying "I generated 250k lines" is like saying "I used 2500 gallons of gas". Cool, nice expense, but where did you get? Because it it's three miles, you're just burning money.
250k lines is roughly SQLite or Redis in project size. Do you have SQLite-maintaining money? Did you get as far as Redis did in outcomes?
I've been down the "don't read the code" path and I can say it leads nowhere good.
I am perhaps talking my own book here, but I'd like to see more tools that brag about "shipped N real features to production" or "solved Y problem in large-10-year-old-codebase"
I'm not saying that coding agents can't do these things and such tools don't exist, I'm just afraid that counting 100k+ LOC that the author didn't read kind of fuels the "this is all hype-slop" argument rather than helping people discover the ways that coding agents can solve real and valuable problems.
prakashrj•1h ago
rsoto2•1h ago
Faster than using ai. Cheaper. Code is better tested/more secure. I can learn/build with other humans.
prakashrj•56m ago
prakashrj•54m ago
0x696C6961•13m ago
wslh•1h ago
prakashrj•1h ago
I will open source it soon in few weeks, as I have still complete few more features.
prakashrj•52m ago