From YAML to Deterministic + Agentic Runners

Most "agent frameworks" treat agents like function calls: pass context, wait for output, move to the next node. In practice that produces a subtle failure mode: groupthink. When agents see each other's reasoning while generating their own, the outputs converge to the same safe middle.

What worked for us (in Leviathan + the Kingly Studio workflows) wasn't a clever orchestrator. It was a dumb one.

The core move: disk-based orchestration. YAML describes structure. Agents read/write files. A synthesis step reads all. No shared hidden state, no in-memory broker, no "chain" object that leaks context.

The pattern that actually works#

• Agents communicate through files only.
• Parallel work means "same input file, different output files".
• The orchestrator dispatches; it does not synthesize.

Why files beat fancy state#

Files are the lowest-common-denominator substrate:

• Humans can read them.
• Git can diff them.
• Agents can consume them.
• Debugging is literally just opening the folder.

And most importantly: files enforce isolation. If two agents run in parallel and only see 00-input.md, they produce genuinely different angles.

Gastown: "Claude Code is the runtime"#

In Leviathan terms, Gastown is the operationalization of that idea:

1. Load workflow YAML
2. Create tmp/<workflow>-<timestamp>/
3. Write 00-input.md
4. Dispatch agents (parallel or sequential)
5. Verify outputs exist
6. Dispatch synthesis

No bespoke workflow engine required.

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CDO: the useful reduction#

The useful reduction (captured in our internal skills) is:

Graph-based layout + agentic execution = CDO

Not a new programming language. Not a new runtime. The "language" is the graph shape + the enforced I/O discipline.

BD (beads): when it becomes multi-session#

Once work becomes multi-session, you need persistent tracking distinct from artifacts. That's where issue tracking shines:

• Files are source-of-truth artifacts (outputs, drafts, reports).
• The dependency graph tracks what's blocked, what's next, what's done.

A pragmatic template you can steal#

If you want to try this pattern without committing to infrastructure:

• Create a workflow folder: tmp/<name>-<timestamp>/
• Write 00-input.md
• Dispatch 2 agents in parallel against the same input
• Dispatch a third agent to synthesize

If you can't reproduce "non-groupthink divergence" with that, you don't have a multi-agent system—you have a single voice wearing costumes.

Related Concepts#

• Swarm DAG — Interactive visualization of multi-agent orchestration
• Context Engineering — Why context beats prompts
• AI Dictionary — Multi-agent terminology explained

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2026 Field Notes: Orchestration over God Prompts#

The era of the "God prompt" is over. We're seeing a massive industry shift toward specialized micro-agents orchestrated via frameworks like CrewAI and LangGraph.

At Kingly, we power this with Lev (Leviathan), our universal agent runtime. Lev deploys AI workflows across 38 platforms without rewrites, utilizing disk-based orchestration (FlowMind YAML) instead of in-memory state. This guarantees deterministic handoffs and fundamentally prevents the "groupthink" that plagues shared-memory agent swarms.