Superpowers 6 — Massively Parallel Procrastination

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June 15, 2026

Superpowers 6

#superpowers ·

#agents ·

#coding ·

#claude ·

#codex ·

#fable ·

#optimization

You can also read this post on our corporate blog at https://primeradiant.com/blog

TL;DR: Superpowers 6 is much, much faster and burns many fewer tokens to get the same high-quality outcomes. If you're tokenmaxxing, maybe skip this release, but if you care about your builds being up to 50% faster and up to 60% cheaper, you're going to love Superpowers 6.

A week ago, we were gearing up to release Superpowers 5.2. We'd slipped the release a couple of times already to add "just one more improvement."

We added support for Pi, Antigravity and Kimi Code.

We made Superpowers work better on Codex and OpenCode, and Cursor.

We rewrote a bunch of the Superpowers skills to be model and harness agnostic, which helps them be more reliable everywhere. We also wrote a new contribution guide for how to add support for a new coding agent harness for Superpowers.

We did a bunch of work to make Visual Brainstorming easier to use, safer, and more reliable.

And we fixed a whole slew of bugs, including a particularly nasty one that led to code review subagents sometimes reviewing the whole branch, rather than a single task.

It was going to be a great release.

And then Anthropic shipped (and unshipped) Fable. In the few days that I had access to Fable, I put it to the best use that I could.

It's no secret that the most common lament we hear from Superpowers users is that tokens are expensive and Superpowers uses a ton of them. Building software with Superpowers is slower than building without it, too. The "slow" part shouldn't matter - it happens during the autonomous subagent driven development orchestration of the build process.

But it does matter. Slow isn't fun. And expensive isn't fun either.

A bunch of the reasons that Superpowers builds have taken longer and cost more are the same reasons that it delivers good outcomes for so many users. It does a ton of up-front planning work to make sure your implementations can be hands-off, forces strict red-green TDD while implementing, and then the orchestrator inside Superpowers reviews every single change on two axes:

did the agent implement exactly what was asked, no more and no less.

is the quality of the work up to snuff.

Just by the nature of what it's doing, it's going to be slower than yoloing an untested implementation and calling it a day.

But it's never made me happy that it's slow and expensive.

When Fable came out, I decided to see how well it could optimize Subagent Driven Development.

I think I was hoping for something like a 15% reduction in token spend.

I got that. And a whole lot more.

Our first angle of attack was looking at the coordinator to reviewer handoff. Fable analyzed thousands of Subagent Driven Development sessions and found that code and spec-compliance review subagents sometimes ran a lot of git commands while doing their reviews. Simply switching the written instructions for how to find the commits to review to a shell script that pre-generates a review package containing well-formatted diff and some other metadata decreased token spend and wall-clock time by about 10%.

As I was going to bed that evening, I told Fable to see about shaving another 15% off wall clock time and token cost for our evals while I slept.

As I was going to bed, I posted a note on our internal Slack that we should look at evaluating what happens if you combine the code reviewer and the spec compliance reviewer.

I don't really know what I expected to happen overnight, but I don't think it was waking up to find that Fable had independently come to the same conclusion, tested it, and found that across our eval suite, it saved that additional 15% I'd asked for.

The next night, I got a little more ambitious.

/goal once this is done, run an autoresearch loop to improve cost-efficiency of the superpowers build loop. test with opus as the coordinator. make an hypothesis log. run experiments. run at least 25 experiments.

Fable built out a full autoresearch harness and ran overnight. You can check out what it built on GitHub.

**The ==autoresearch== loop is complete: 25 experiments closed** (plus 4 logged as backlog), opus as coordinator throughout, every hypothesis pre-registered with a prediction in the log, now durable at evals `docs/experiments/2026-06-11-build-loop-==autoresearch==.md` (a76ddc9). Loop spend ≈ $165.

What the loop found

**The ship candidate (E27):** opus controller + elicited plan + conditional haiku implementers + terse reviewer contract + narration recipe + final-review tier pin → **fractals $6.24/$6.60** (the combo config on hand plans was $11.67–14.84). Planted-defect gates 2/3, with the one fail forensically attributed to reviewer variance plus judge strictness — the terse contract was explicitly exonerated by reading the reviewer's reports. The N=5...