
More autonomy and parallelism without skipping control, isolation or the review queue.
SCALE TIER // SCALING
The scaling tier of the 10x Workflow: you run more cycles in parallel, with quality gates and autonomy, instead of adding agents to a single task. Your capacity to review sets the throughput ceiling.
SCALE TIER // CLICK A NODE TO FLY TO A SECTION
Tier brief · three nodes in 30 seconds
Automatic gates close out every phase - none passes on red.
NODE 02The plan executes itself: a commit per phase or an honest STOP.
NODE 03More cycles in parallel with context isolation - review sets the ceiling.
Scaling means more cycles in parallel, each with its own context - not more agents on one slice of work.
"Hand in the box, needle at the neck. Only what survives the test goes on - the rest drops out at the gate."
- the Reverend Mother at the box, the gom jabbar testThe gom jabbar checks one thing: whether the candidate can survive the test before anyone trusts them. This node does the same with every phase of the plan. Without it, autonomy means code nobody checked at the moment it was written - you are the only gate and you have to watch everything. Quality gates answer the question: what guards quality when you are not there?
This node answers the question: what guards quality when you are not there? Without automatic gates, autonomy means code nobody checked at the moment it was written - you are the only gate and you have to watch everything.
Input: a plan with success criteria. Output: a phase closed out automatically - lint and typecheck after every edit, tests per phase, a commit only on green. The mechanism: the deliberate-break check - you break the implementation on purpose and confirm the test fails. You can trust a gate only once you have seen it close.
before you hand the machine more autonomy - the gates must be guarding quality before you stop watching over its shoulder.
Implementation review as an automatic gate: the skill runs in CI on a pull request, with no questions and no code edits. It reads, analyzes, writes a report and issues a verdict - guarding quality exactly when nobody is watching.
Input: a pull request plus the change plan (context/changes/<change-id>/plan.md), found by convention or from a Plan: line in the PR description. Output: a reviews/impl-review.md report committed to the PR branch, a comment with the verdict and a dimension table, and inline comments on flagged diff lines.
Three subagents work in parallel: drift against the plan (MATCH / DRIFT / MISSING / EXTRA), safety and pattern compliance, test coverage. Then lint, build and typecheck, PASS / WARNING / FAIL grades across seven dimensions and an overall verdict: APPROVED, NEEDS ATTENTION or REJECTED.
The output contract is strict:
<!-- IMPL-REVIEW-REPORT --> marker in the first line - triage tools recognize the report by it,Decision: PENDING field for a later human decision,[skip ci] so the review does not trigger itself in a loop,The skill does not edit code and asks no questions - fixes go in a separate step after triage. A PR without a plan gets a neutral comment instead of a red check. A REJECTED verdict blocks the merge; an override exists (the impl-review-override label), but that is a deliberate human decision, not the machine's.
"This crisis was computed centuries before you were born. The Vault will open exactly when the plan requires it."
- in the spirit of Hari Seldon's recordings from the Time VaultThe Seldon Plan works because it does not need its author at the controls: the crises were foreseen in advance, and the Vault speaks up exactly when needed. This node brings that to a change plan. Without it, you sit between phases as a "next" clicker and autonomy ends at the first question. /10x-goal-implement under /goal answers: how does the plan execute without you?
This node answers the question: how does the plan execute without you? Without it, you sit between phases as a "next" clicker and autonomy ends at the first question - /10x-goal-implement under /goal takes you off that post.
Input: an approved plan.md. Output: a commit per phase on green or an honest STOP. The mechanism: phases run on their own, the Progress section works as a state machine, and on a structural mismatch execution halts with a STOP block instead of improvising. The crisis is foreseen in the plan itself - not acted out live.
with an approved plan and limited time - the plan runs on its own, and you come back to finished commits or to an honest STOP with the reason in writing.
The autonomous sibling of /10x-implement: it executes an approved plan under /goal with no interaction at all - in a regular session or headless via claude -p. An explicit, written policy replaces every decision a human would normally make; where policy is missing, it picks the conservative interpretation and reports it.
Input: an approved plan.md with a Progress section as the state machine. Output: a commit per phase (Conventional Commits) plus a run report - or an honest STOP block with what the plan expected, what was found, why it blocks and where to resume from.
Every phase goes through a fixed sequence: success criteria from the plan → staging of touched files → the deliberate-break check (breaking production code on purpose; the test must fail - red is the passing condition) → the full test suite, lint, typecheck → a commit only on green. A failing gate gets at most 2 repair attempts, then STOP.
When the code disagrees with the plan: Minor (a moved file, a rename, import drift) - it adapts and reports in one line; Structural (a missing dependency, a different architecture, a nonexistent API) - a STOP block and end of work. When in doubt, the mismatch is structural: a wrong STOP costs one resume, a wrong adaptation smuggles in a redesign nobody approved.
Manual rows in Progress are outside the machine's jurisdiction: it never checks them off and never blocks on them - they land at the end of the run report as a checklist for a human. Repairing a failing gate never weakens an assertion, removes a test or loosens lint rules: the code has to meet the check, not the other way around.
"Every pilot in their own cockpit, all of them on my comms. I lead as many wings as I can keep track of."
- squadron leader at the pre-launch briefingA squadron scales with more ships, isolated cockpits and one leader on comms - not by packing twelve pilots into one starfighter. Work is the same: more cycles in parallel with context isolation, not more agents on one slice. The node answers the question: how many cycles can you carry at once?
Scaling work means more cycles in parallel with context isolation, not more agents on one slice. The node answers the question: how many cycles can you carry at once?
Input: several independent units of work. Output: more throughput without unreviewed code. The mechanism: plan → implement → review cycles run on a cadence (/loop), each in its own context, and all converge on one gate - your review. More agents without review does not raise throughput, only debt; the leader sets the ceiling, not the number of ships.
once a single cycle stops being enough - you keep adding tracks as long as every commit still goes through your review.
The single-track engine: it executes an approved plan from context/changes/<change-id>/plan.md phase by phase, with verification and a separate commit after each phase. This is exactly the cycle you replicate when adding more parallel tracks.
Input: a plan with a Progress section at the bottom. Output: implemented phases - each with its own commit (Conventional Commits), whose short SHA goes back into the checked-off Progress rows as proof of what landed and when.
The Progress section in the plan is the only source of state - no helper files, no markers. "Where am I" is computed, not stored: the first empty checkbox is the next step. That means you can interrupt the cycle, clear the context and resume with a single command - the state never gets lost.
After the automated checks go green: manual confirmation from a human → staging of only the files touched in the phase (never git add -A; dirty files outside the set get a separate question) → message approval → commit → the SHA written back into Progress.
After each phase, a decision: continue in the same context or clear it and resume with a command copied to the clipboard (/10x-implement <change-id> phase N). This mechanism lets you run several cycles in parallel - each track has its own context and its own state in its own plan.
When the plan diverges from reality, it stops and asks: adapt, skip or go back to planning. On a track that is meant to run unattended, use /10x-goal-implement - there those decisions are made by written policy.
The scaling tier replaces nothing - it orbits above what already works. The foundation gives the project a launch ramp, the chain carries units of work, scaling adds tracks.
The scaling tier replaces nothing - it works on what you already have. The foundation prepares the project, the chain delivers individual units of work, scaling runs more of them in parallel.
Scaling raises throughput - the next module tightens the rigor. More tracks make sense only when the bar drops on none of them.
Scaling adds throughput to the chain, but your review still sets the ceiling. Before you run more tracks in parallel, work through module 3 - that is what holds the bar as the pace goes up.
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