MECHANISM · ORCHESTRATION · EMERGING

Subagent Orchestration

Delegate bounded work into isolated contexts, control capabilities and lifecycle, and merge results without confusing ownership or workspace state.

1 lessons6 agent snapshots0 experiments
orchestrationsubagent-orchestrationproblem → policy → evidence
L0Intuitionpartial
L1Buildmissing
L2Engineeringpartial
L3Architecturepartial
L4Researchpartial
DEPENDENCY GRAPH · READER PATH

What feeds it, and what does it unlock?

Arrows show learning and design dependencies, not runtime data flow. Follow any node to continue through the Atlas.

subagent-orchestrationSubagent OrchestrationCurrent research boundary
UnlocksNo dependents yet
Bilingual deep dive missing

Delegate bounded work into isolated contexts, control capabilities and lifecycle, and merge results without confusing ownership or workspace state.

The structured record is in the Atlas, but the L0–L4 article has not passed content review.

AGENT MAPPING · EVIDENCE ONLY

Snapshot implementations

An implementation enters the map only when both a snapshot and claims exist; unknowns remain visible.

PARTIALClaude Code

Official docs distinguish one-way subagent delegation from experimental peer-capable Agent Teams and state that teammates do not receive automatic worktree isolation.

claude-code-2026-08-10-docs
SUBSTANTIALPi

The source-backed result is an intentional absence from core plus documented extension points.

pi-2026-08-10-source
UNKNOWN · EVIDENCE GAPReference Harness

No implementation currently clears the Snapshot + Claim threshold; this is not a claim that the product lacks the capability.

Inspect coverage boundary
CLAIMS · EVIDENCE LEDGER7 RECORDS
EXPERIMENTS · EXERCISES

What has actually been tested?

Formal experiments are separate from course exercises. Exercises can validate the reference implementation but cannot replace Native evidence from a real agent.

Formal experiment · not registered

No experiment record means untested, not passed. The course checks below cover only the deterministic reference harness.

s01-agent-loopobserve
Verify the Golden Trace

The committed JSONL exactly matches a real demo run and passes the trace schema.

python3 -m curriculum.golden verify s01-agent-loop
s01-agent-loopmodify
Preserve loop invariants

A completed run keeps contiguous sequence numbers and ends with session.stop.

python3 -m unittest curriculum.tests.test_vertical_slice.VerticalSliceTests.test_s01_minimal_loop -v
OPEN QUESTIONS · L4
01

Which context, permissions, and instructions should a child inherit?

02

When is a worktree a sufficient isolation boundary?

03

How should cancellation, partial results, and nested delegation be represented in traces?