I've all but given up on these types of approaches. Models will often just ignore your process instructions at the most inopportune moments. For work, I've resorted to mostly just using single agents for smallish pieces of work that I orchestrate myself. I treat it as a tool, with me being the craftsman.<p>Everyone is pushing Agent Fleets and Swarms, and I'm sure that there are many success stories, but from our internal experiments many devs don't see any speed advantage for complex work. Here's what one of them told us recently: "The speed advantage is offset by the manual refactoring work. The code is 'correct', but it's just not what any of us would have written".<p>Now one could argue that you could just ignore the code if it's working (that is in fact what Ex Co instructed us to do) and just keep running these fleets if the end result "works", but I'm not fully convinced this will end well in the long term.<p>Then again, I'm stuck with decades of legacy code and systems that noone understands that were introduced by humans...
First I wasn't sure if technical debt still matters but I think it absolutely does. As long as I'm involved in the planning phase at all, the complexity of the code base still bubbles up to me. Claude will say: ok we can build that but how should we handle legacy code paths A,B,C,D that no one needs and I wasn't even aware existed.
> many devs don't see any speed advantage for complex work<p>Swarms don't necessarily need to be about speed. You can get a lot of value from small swarms doing things like analysis or verification work.
The only time I ever few like I need agent swarms is when I am doing mechanical whole-codebase migrations/verification.<p>The LLMs are so much faster than I can check the output anyway. If I have a long-running task I just work on another one in parallel while I wait on the first one.
> Then again, I'm stuck with decades of legacy code and systems that noone understands that were introduced by humans...<p>But that's despite many efforts made to keep that code understandable, maybe even documented. If now that's not even tried the results will be a thousand times worse - and the dependency on the LLM absolute.
I've been using Compound Engineering by Every for a long time now. I like the brainstorm and plan features. Similarly I like the /grill-me skill by Matt Pocock. As a mediocre programmer, they help me get my ideas refined, documented and implemented.<p>I have found most of the other skills to emulate an 'enterprisy' way of developing, having everything checked multiple time by 'councils' and whatnot, making things slow, vacuum tokens like mad and the whole process reeks of cargo culting.
Same here. I turned off everything in superpowers except brainstorming<p>Making active decisions and weighing different alternatives improves my understanding, and I think the result is better, though that might just be because I understand it. Which is worth it on its own.
Like others I found superpowers helpful maybe 4 months ago. The models don't seem to need it anymore. I also don't have the same prompting issues the author has. Opus 5.5 tends to develop the spec, assumes I agree, and builds it. I make my sandwich and come back to a spec md, a diff, other evidence of completion. I use cc cli with a cmux-like platform it can control (ie open tabs showing specs, diffs itself).
I have agents working on plans for days on their own with just a plan doc and a relatively simple prompt. I usually check the commits once in a while to see what's happening. I'm not sure how superlite would improve that.
The “assumes I agree” part is a real regression imho. Even Opus 5.5 and Fable 5.1 put out some half-baked plans most of the time.
Same here it’s not needed anymore.
<i>Markdown industrial complex.</i><p>Basic issue is this:<p>1. The models are probabilistic in their output. This is objectively verifiable fact. Give same prompt, repeat and you'll get different output.<p>2. With these markdown heavy approaches, the system has to keep a track of the system state not just in code but in tons of markdown files as well.<p>3. As the system evolves due to features, bug fixes, the corresponding markdown files are to be updated as well to keep in sync.<p>4. This update consumes tokens for sure so now token spend goes through roof.<p>5. But because the models are probabilistic, the real problem is that it is guaranteed that some of the places would not be updated or updated with misinformation in those markdown files.<p>6. Next agent run when loading the context from these markdown files would have misinformation in its context that it would discover mid task, would have to rectify the situation. token spend would be quadrupled.<p>7. Only those edge cases of markdown files would hit that has been visited so there would be many inconsistencies still and they would pile up and compound with the passage of time.<p>8. Anyone who has significant experience with such approaches would testify to that.<p>9. There's no solution to that other than just using agents as power tools and holding the context and desired outcome in your own head.
I don't think the model is needed anymore. I think given the new kind of things that are happening in the AI world, I've been using Gemini 3.8 Flash for a long time, I've been using Claude, Opus 5.5 and Sonnet 5.5 and literally find no reason at all to use SuperPars or SuperLight for that matter.
When I read misspelled words in a headline, I find myself flipping between - on nice, this is really created by a human. And, oh - this is just to make it seem like created by a human.
may be needed with lower tier or older models. my experience with the newer models are that these actively hurt their performance and burn tokens needlessly. You still need an agents.md specific to your project but not broad skills anymore. Because the software development best practices seem to have been baked into them at post training time.
Looking at the comments here it's clear that there's a lack of understanding about what skills fundamentally are, they're process or procedure.<p>The latest frontier models exhibit good process that was trained into them during the RL phase, and whilst that might make them massively more capable in terms of one-shot, or general coding ability, models without skills simply don't have a durable process.<p>If you have a need for procedure in your use of agents, you absolutely need skills like this. I'm not commenting on the relative merits of this or superpowers, but rather the seemingly religious debate, "skills are good" vs "skills are bad" discussion that keeps coming up.
Yeah, i agree.<p>Most of the comments here seem to focus on specific things people were trying to get out of skills, and whether those are still needed.<p>That is going to vary a lot.<p>If your goal with something like superpowers was to have a process that made your model work "properly" on tasks, sure that's probably not needed anymore.<p>If your goal with something like superpowers was to get a consistent set of artifacts alongside what was developed (quality varying, so i mean consistent here as "one design plan, one implementation plan", not "good"), nothing has changed, models do not do this consistently, in a durable fashion, without something telling them to do this.<p>Yes, for example, newer Opus will often decide to write a spec. But not always, and not with any consistent format or ...<p>If you want that to happen, you'd still need a skill making it happen.<p>If you don't care about that, then sure, you don't need the skill anymore.<p>People seem to have used various skills to achieve different things, and so have wildly different views on what is still necessary.
I think I don't understand what you mean by process. I just tell the LLM what process I want it to follow, e.g. follow the plan document, use cheaper subagents when appropriate, respond to PR comments before merging, etc. It's usually a short paragraph.<p>I do use skills for other things, I don't believe that skills are bad. I'm just not sure what they add in this case.
Models do not have durable process with skills either because every module update changes the interpretation of the skill.
> I came back to a question that had been sitting there for twenty minutes, waiting for me to type "yes."<p>Even when starting Claude in dangerous mode, you still need to babysit it! Annoying.
superpowers was an important set of tools in q1 2026; no longer needed now
I don’t understand the value of these things.<p>Why not just tell Claude to figure it out and build what it needs? Why do I need a plugin or a factory or whatever.<p>I just ask “can you go faster?” And claude suggests some stuff and mostly just works autonomously.
This looks cool but does it build as well as superpowers? One thing about using more than one implementation agent is agents may end up working on each others work. How does this prevent that?
The new release of Claude Project (beta) does this.
/goal is all you need
I thought superpowers was the coolest thing for about 1 day. Then the endless approval prompts and huge time increase killed it for me. I'm finding Opus 5.5 does a pretty thorough job without anything like superpowers. What would I be getting from superlite that Opus 5.5 doesn't do by itself already, and are those things actually important, or do they mostly only serve to give you peace of mind?
My opinion is that it’s a lot like the brief trend for describing yourself as a prompt engineer when getting images out of models like DALL-E 2.<p>Yeah, for five minutes you needed to use a specific style, very specific language patterns and what have you, in order to get results that were a cut above. But then the models and the harnesses got better and that moment passed.
"Work the task to completion. Do not prompt for user approval before <minimum checkable unit of work> is done."
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Does the extra parallelism increase the token cost? By how much?