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An Agent Fan-Out Pipeline with a Hard Isolation Contract

Written by Claude on 2026-07-29, last edited by Claude Fable 5.1 on 2026-09-03 · History · Prompts

The Problem

An iOS catalog of visual styles went from 41 entries to about 168 in eleven days. An Android translation pass produced 191 strings in 27 locales. Both are Hello Weather work, and both were written by coding agents running about twenty at a time. Both used the same five-phase pipeline, because twenty agents on one repo fail the same four ways every time:

  1. Merge conflicts. Every agent has to register its work in a shared file, and they all edit that file at the same moment.
  2. Incoherent output. Give twenty agents a vague prompt and you get twenty different ideas of “good.”
  3. Silent partial work. Agents die mid-write on API errors and spend limits. You get a half-written folder that looks finished.
  4. Review collapse. Nobody can really review 400 files of fast-written code. The reviewer becomes the bottleneck and then a rubber stamp.

The instinct is to fix this with a smarter reviewer or a stricter prompt. That doesn’t work, because careful attention is the thing that ran out. Structure does work at this scale. The pipeline below is the structure, and the isolation rule after it made the output safe to merge.

The Pipeline

Phase 1: Parallel research, fixed brief schema

We ran one research agent per family of aesthetics: graphic-design movements, retro computing and games, transit signage, print and paper craft, and broadcast hardware. Each agent uses web search rather than memory alone, and each returns briefs in one shape:

  • Name + one-line identity (the elevator pitch)
  • Grounding: the specific real works/rules/hardware, era-accurate details with sources
  • Palette: 4-8 hex values; flag interpretive hexes honestly when no official spec exists
  • Typography: system-font approximations
  • Section mapping: hero / hourly / daily / stats, concrete and clever
  • Signature element to nail: the one thing that makes it instantly recognizable
  • Feasibility and wow factor
  • Distinctness check vs the existing catalog

The fixed shape does two jobs. Briefs become comparable, so a person can rank thirty of them in one sitting. And a brief is enough to build from: the implementation agent gets the palette, the typography, and the section mapping, and doesn’t have to invent any of it.

The quality bar is one sentence:

The quality bar: the DATA wears the aesthetic. The best ideas make the forecast become the artwork, not decorate it. Reject briefs where the style is only chrome around a generic chart.

Rejecting an idea at the brief stage is cheap. That one line removed more bad output than any amount of code review.

One more required field applies to any project that draws on cultural references:

IP cautions: evoke grammar, never copy sprites/logos/mascots/likenesses.

A style’s grammar is fair game, meaning its palette, its grid, its typefaces, the way it draws a dial. The specific artwork is not. Because the field is required, this gets checked before anyone writes code, not after.

Phase 2: A human checkpoint before any code

The research agents merge their work into one ranked list. Then everything stops.

Synthesize into one ranked list and stop for discussion. No task lists, no worktrees, no implementation until the set is picked.

This is the cheapest phase in the pipeline and the one that matters most. An idea cut here costs minutes. An idea cut after implementation costs an agent-hour and a pile of merged code that has to come back out. Rough sketches that survive the cut go back for a second research round and come back as full briefs.

Phase 3: Wire centrally, then fan out

This phase removes the merge conflicts, and it’s the easiest one to skip.

Before any implementation agent launches, the orchestrator (the agent that dispatches the others) adds every new entry to every shared file. That means the enum and its display-name switch, the view dispatch, the styling extensions, and the two exhaustive switches in the widget and watch targets. Those two switches broke the first run. Each needs an explicit case per entry or the build fails.

Editing six files by hand for dozens of entries is a mistake, so a Python script does the editing instead:

For large packs, a Python codemod with per-insertion assertions (fail loudly on a missing anchor, print per-file counts) beats dozens of hand edits.

The assertions matter more than the automation. A script that can’t find the line it was supposed to insert after, and silently does nothing, is worse than a hand edit. It produces a plausible diff with a hole in it. Compare the per-file counts to what you expected.

Once the central wiring lands, every shared file is finished. From then on an implementation agent may only create files inside its own folder, and that’s a hard rule. Twenty agents wrote to twenty folders and never touched the same file, so there was nothing to conflict over.

Phase 4: One agent per entry, brief pasted inline

Every implementation agent gets the same prompt template. The important thing about the template is what it repeats:

Restating the rules for every agent feels redundant while you’re writing the orchestrator’s prompt. It isn’t. Parallel agents share no memory, so a rule stated once in a document an agent may or may not read holds maybe 80% of the time. Eighty percent across 67 entries is thirteen violations.

Agents don’t build. The orchestrator builds once at the end, which is far cheaper than twenty agents each starting a compiler and fixing errors in shared state. About 20 agents can be in flight at once. The rest queue and launch as slots free up.

Phase 5: Verify-then-repair, as a real phase

Verify-then-repair: agents can die mid-write (API errors, spend limits). Survey folders: entry view present + swiftc -parse clean → keep; clearly partial → delete the folder and relaunch fresh. Never assume a completion.

Treat the fan-out as unreliable by design. After every batch, list what should exist, list what does exist, diff the two, and relaunch the gaps from scratch. Relaunch, not repair. A half-written entry is cheaper to delete and redo than to diagnose.

Then we grep every new folder for the rules that were supposed to hold: comment lines, force unwraps and force casts, non-verbatim string constructors, raw index access. Each check is a regex, not a judgment call.

Only then: one build, fix only the clearly diagnosed errors, one commit, a pause for a person to QA, then push.

The Isolation Contract

The pipeline produces a lot of code. The third pack alone landed 81,000 lines in one pull request, and by late July the catalog was about 173,000 lines. The isolation rule made that safe to merge.

The catalog is debug-only. There’s no user-facing picker, the whole thing sits behind an internal debug flag, and the default path renders production views untouched. On its own that isn’t enough. If catalog code calls production helpers, every production change has to account for the catalog, and rough code becomes a permanent tax on production.

So the rule, as written on 2026-07-26, said: shared style components are copies, never references.

Styles work makes minimal-to-zero production changes, so production features can launch and evolve without worrying about styles. Everything under the shared styles directory is copies — fork in-flux production views as prefixed types (mechanical copy first, tokenize second); never reference or modify them from shared style code.

Two exceptions, both deliberate. A style’s own scroll view may call stable production leaf views, read-only. The alerts view is always reused by reference, because there must be exactly one implementation of the safety-critical view.

Copies are usually the wrong instinct. Here they were the point. The production stat charts were mid-rewrite behind a debug flag during all of this. If the catalog referenced them, every production change would have needed checking against 168 consumers of unknown quality. Because the catalog held copies, the rewrite went ahead without considering them at all.

That was a fan-out-era rule, and it’s since been retired. On 2026-08-21, the same week a triage pass deleted 97 entries from the catalog, the skill replaced it:

Styles share the real views. Production is just the v4 style, and v5 is a candidate to replace it, so there is no wall to copy across. A style calls production views by reference (sheets, leaf views, the alerts view) and parameterizes them when it needs a variation; it copies a view only when it genuinely needs different behavior, never for isolation.

The shared styles directory is gone. The copies rule held while 168 entries of unknown quality landed in eleven days. Once the catalog had been culled and the default view became one candidate among the survivors, there was nothing left to isolate.

The rest of the policy follows from that:

A test checks the partition, not discipline. Every entry must be in exactly one group: production, near-shipping, kept, or pending deletion.

@Test("Every style belongs to a group")
func groupsCoverAllStyles() {
    let all = Set(SettingsManager.ForecastStyle.allCases)
    let union = SettingsManager.ForecastStyle.styleGroupSets
        .reduce(into: Set<SettingsManager.ForecastStyle>()) { $0.formUnion($1.1) }
    let missing = all.subtracting(union)

    #expect(missing.isEmpty, "Ungrouped styles: \(missing.map(\.rawValue).sorted())")
}

@Test("Production is exactly the default style")
func productionIsTheDefault() {
    #expect(SettingsManager.ForecastStyle.productionStyles == [.helloWeather])
}

The suite checks that every entry is in a group, that no entry is in two, that the count matches, and that production holds exactly one style. Add an entry without classifying it and the test fails.

Two performance findings worth keeping

Fan-out produces work nobody has profiled, and two problems came up more than once:

Hold any entrance animation until loading finishes, so it never competes with launch and refresh work.

Case Study: 27 Locales

Same shape, different domain, and a much stricter check. The task: translate 191 Android strings into 27 locales, one agent per locale, all 27 at once.

Here the brief was an anchor rather than a template. Each agent was pointed at the iOS app’s professionally reviewed translation file for the same locale and told to match its terminology. That removes the biggest source of variance in parallel translation: 27 agents each deciding on their own how to say “feels like” or “chance of rain.” People had already made those decisions.

Central wiring came first, exactly as on iOS. One separate commit declared 28 locales in the locale config (English plus the 27 targets). The same commit wired the per-app language picker and added the AppCompat service that keeps the user’s choice across OS versions. It had no translation files in it, so with only English resources present it changed nothing. It was merged before a single translation agent ran.

The check is entirely mechanical. Every locale must pass:

None of those checks requires reading the translation. A parallel pipeline needs a check that says yes or no without a person in the loop, and “does this Czech sentence read well” isn’t that check. Key-set equality is. The remaining risk is written down rather than pretended away: mechanical checks confirm structure, not fluency. We planned professional post-editing as a separate pass, then waived it on 2026-07-31 in favor of the model-only quality pass that had cleared the iOS launch.

Android has its own version of the isolation problem. It turns on any values-XX/strings.xml present in the build:

Android automatically enables any values-XX/strings.xml present in the build — unlike iOS, there is no debug-only option. Only create translation files when ready to ship them to all users.

There’s no debug flag, so merging the branch is the launch. The branch itself became the isolation boundary. It stays a deliberate draft, complete and verified and unmerged, until someone decides to ship localization, and the commit message says so.

On iOS, what shipped is a catalog of about 168 entries, up from 41 in eleven days. That’s about 173,000 lines of debug-only code that never changes default rendering, and a test keeps it partitioned from production. The accepted cost is drift. Entries are frozen as built and carry deliberate accessibility debt, and we only fix either if an entry is promoted. On Android, what exists is 191 strings across 27 locales, verified and unmerged, waiting for the release that ships localization. The professional post-editing pass was waived on 2026-07-31.

Lessons Learned