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Prompts and workflows

DeepSeek V4 Flash · workflow

Delegate in layers and synthesize a monograph with DSH

The source publishes a complete starting prompt with research, pushback, editing, and final synthesis targeting one cited Markdown artifact.

Source reviewed; not testedDeepSeek Harness (DSH)

Prerequisites and inputs

  • workspace name
  • subagent count
  • question and output format

Complete templates

Source-complete starting prompt: layered subagent monograph

original
Use new subfolder "{{WORKSPACE}}", spawn {{SUBAGENT_COUNT}} subagents. Each answers "{{QUESTION}}" from first principles with actionable insights and a contrarian view. For each, spawn one pushback subagent and one editor subagent. Save level-1 outputs as markdown, let level-2 agents update only those outputs, then spawn one final subagent to synthesize all outputs into a cited monograph.

Replace before running: {{WORKSPACE}}, {{SUBAGENT_COUNT}}, {{QUESTION}}

Steps

  1. Replace the workspace, question, agent count, and final filename.

  2. Start small and ensure each first-level agent has a bounded output.

  3. Restrict pushback/editor agents to their assigned artifacts; have the final agent preserve citations.

  4. Check duplication, citations, and file count; the source's 151 agents/25-minute run is not a general performance claim.

Read the source research notes

Tweet highlights

"RAN 151 SUBAGENTS IN DEEPSEEK HARNESS (DSH) On Sunday I was tokenmaxxing, running multiple workspace sessions to explor… This is a necessary excerpt; read the original source for full context.

Starting Prompt (original text)

Use new subfolder "WITMOLv2", spawn 50 subagents, each embodies famous past and modern philosophers and thinkers. each answer the question "what is the meaning of life? covering first principles, axioms and actionable insights plus their contrarian views or strawman arguments". for each subagent, spawn 2 subagent: one for pushback (to make better arguments), one for editor (to make writing clearer and clarity for general audience). level 1 subagent each output into markdown with their name as <name>.md. level 2 subagent only do final update on level 1 subagent output. once all subagents are done (level 1 and level 2), spawn a final subagent use all 50 output and synthesis a final what-is-the-meaning-of-line-50.md as a monograph, include citation from each philosopher when required.

Output: 151 Subagents, 51 Files, 860 KB Total

Output under the WITMOLv2/ directory:

  • 50 philosopher essays, each structured to include:

    • First Principles (the foundational axioms of philosophy)

    • The Meaning of Life (meaning derived from their tradition)

    • Actionable Insights (how to put it into daily life)

    • Contrarian View / Strawman (the strongest objection + response)

    • Final Reflection (closing thoughts)

    • Strengthened Through Critique (added by the pushback agent: rigorously tests 2–3 weaknesses and strengthens the response)

    • Reading Guide (added by the editor agent: an entry point for general readers)

  • Synthesis monograph what-is-the-meaning-of-life-50.md (44 KB, 392 lines):

    • Part I: The Great Traditions (10 chapters, grouping philosophers by tradition)

    • Part II: Cross-Cutting Themes (6 cross-cutting themes)

Prompt Design Breakdown (Reusable Pattern)

  1. Hierarchical delegation: 1 prompt → 50 level-1 subagents (writing) → each spawns 2 level-2 subagents (pushback + editing) → final synthesis agent

  2. Explicit boundaries: each subagent has a “bounded task” (answer a specific question, use a specific Markdown output format, and follow a specific filename)

  3. File convention: the <name>.md naming convention makes the output easy to aggregate

  4. Quality loop: the pushback agent strengthens the argument + the editor agent improves readability, addressing the quality problem of “generation as final draft”

  5. Single deliverable: all subagents target one final synthesis document

Use Case Notes

  • Runtime: DeepSeek Harness (DSH), with a DeepSeek V4 Flash series model

  • This pattern is suitable for research report/monograph generation, multi-perspective analysis, and large tasks that require a “writing + critique + polishing” pipeline

  • A single session takes 25 minutes and uses 151 subagents; token consumption matters (tokenmaxxing means maximizing use of the subscription quota)

Source and dates

X (Twitter) · Source date: 2026-08-17 · Edited: 2026-09-20

Read the original source
Variable checklist

Still to replace: 3

{{WORKSPACE}}{{SUBAGENT_COUNT}}{{QUESTION}}

Related prompts

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Related reviews

I Ran DeepSeek V4 Flash on 8 Agent Harnesses (Reddit r/DeepSeek)DeepSeek-V4-Flash: 0731 Benchmark Update and Harness ConditionsDeepSeek-V4-Flash: Local Deployment, Quantization, and Agent TestingDeepSeek V4 Flash doesn't like us? (Reddit r/opencodeCLI)

Read the full analysis

Pricing · English

DeepSeek V4 Flash Pricing: What You Pay in 2026

DeepSeek V4 Flash pricing changed with the V4.1 migration. See the current cache, peak-hour, output, and workload cost math before you budget.

DeepSeek V4 Flash

Use DeepSeek V4 Flash in Tabbit

Run this guide in the environment listed above. Downloading does not transfer the template or establish model availability for your account.