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Introducing Dynamic Workflows in Claude Code: Quarter-Long Work in Days

Dynamic workflows in Claude Code enable Claude to tackle the most challenging engineering tasks end-to-end with parallel subagents, adversarial checking, and automated orchestration.

6 min readYash Thakker
Claude CodeAI AgentsDeveloper ToolsCode MigrationAutomation

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Introducing Dynamic Workflows in Claude Code: Quarter-Long Work in Days

TL;DR: Dynamic workflows in Claude Code let Claude orchestrate tens to hundreds of parallel subagents to tackle complex engineering tasks end-to-end. Work that normally takes quarters now finishes in days—bug hunts across entire services, migrations touching hundreds of files, and plans stress-tested from every angle.


What Are Dynamic Workflows?

Anthropic launched dynamic workflows in Claude Code today (May 28, 2026), introducing a paradigm shift in how AI handles complex, large-scale engineering tasks.

Some problems are too big for one pass by a single agent, especially in complex, legacy codebases:

  • Bug hunts across an entire service
  • Migrations that touch hundreds of files
  • Plans you want stress-tested from every angle before committing

Dynamic workflows handle all of these end-to-end.


How Dynamic Workflows Work

When a workflow kicks off, Claude:

  1. Plans dynamically based on your prompt
  2. Breaks it into subtasks with clear objectives
  3. Fans the work out across subagents running in parallel
  4. Checks results before they're folded in
  5. Iterates until answers converge

Agents address the problem from independent angles, other agents try to refute what they found, and the run keeps iterating until the answers converge—which is how a workflow reaches results a single pass can't.

Key Capabilities

Parallel Execution: Dynamic workflows can run dozens to hundreds of subagents simultaneously, each working on independent subtasks.

Adversarial Checking: Independent agents work to break the results before you see them, ensuring high-quality outputs when the cost of a wrong answer is high.

Long-Running Sessions: Built for work that can extend into hours and days, with progress saved continuously so interrupted jobs pick up where they left off.

Coordinated Results: Because the coordination happens outside the conversation, the plan stays on track no matter how big the task gets.


Real-World Use Cases

Early access users and teams inside Anthropic have been using dynamic workflows for:

Codebase-Wide Audits

  • Bug hunts: Claude searches the entire service or repo in parallel, then runs independent verification on every finding so the report surfaces real issues
  • Security audits: Hardening passes for auth checks, input validation, and unsafe patterns across an entire codebase
  • Performance optimization: Profiler-guided optimization audits with parallel analysis and verification

Large-Scale Migrations

  • Framework swaps: Migrating from one framework to another across thousands of files
  • API deprecations: Updating deprecated API calls throughout the codebase
  • Language ports: Converting entire codebases from one language to another while maintaining test coverage

Critical Work Verification

When the cost of a wrong answer is high, a workflow gives Claude:

  • Independent attempts at the problem
  • Adversarial agents working to break the result
  • Multiple verification passes before you see the output

Case Study: Rewriting Bun from Zig to Rust

Jarred Sumner used dynamic workflows to port Bun from Zig to Rust—a monumental task that showcases what workflows can unlock at scale:

The Numbers:

  • ~750,000 lines of Rust generated
  • 99.8% test suite passing after port
  • 11 days from first commit to merge
  • Hundreds of agents working in parallel

The Process:

  1. Lifetime mapping workflow: Mapped the right Rust lifetime for every struct field in the Zig codebase
  2. Port workflow: Wrote every .rs file as a behavior-identical port of its .zig counterpart, with two reviewers on each file
  3. Fix loop workflow: Drove the build and test suite until both ran clean
  4. Optimization workflow: Addressed unnecessary data copies overnight and opened PRs for final review

While not yet in production, all of this was handled by dynamic workflows. Jarred will be writing about this more in the future.


How to Enable Dynamic Workflows

Dynamic workflows are available today in research preview for:

  • Claude Code CLI
  • Claude Code Desktop
  • VS Code extension (Max, Team, and Enterprise plans if admin enabled)
  • Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry

Option 1: Direct Request

Ask Claude to create a dynamic workflow:

"Create a workflow to audit all authentication checks in our codebase"

Option 2: Ultracode Mode

Turn on the ultracode setting (accessible through the effort menu):

  • Sets effort level to xhigh
  • Lets Claude decide automatically when to use a workflow
  • Best for ongoing complex work

For the best experience, turn on auto mode when using dynamic workflows.


Important Considerations

Token Consumption

Dynamic workflows can consume substantially more tokens than a typical Claude Code session. Anthropic recommends:

  • Start on a scoped task to get a feel for usage
  • The first time a workflow triggers, Claude Code shows what's about to run and asks you to confirm
  • Organization admins can optionally disable workflows through managed settings

Availability by Plan

PlanDefault StatusNotes
MaxOn by defaultReady to use immediately
TeamOn by defaultReady to use immediately
EnterpriseOff by defaultAdmin can enable in Claude Code settings
APIAvailableAmazon Bedrock, Vertex AI, Microsoft Foundry

When to Use Dynamic Workflows

Perfect For:

  • Migrations touching 100+ files
  • Security/performance audits across entire repos
  • Bug hunts in complex, legacy codebases
  • Critical decisions needing multiple verification passes
  • Language ports requiring test suite validation

Not Ideal For:

  • Single-file changes
  • Simple refactoring
  • Quick bug fixes
  • Exploratory coding

Getting Started

  1. Ensure you're on a compatible plan (Max, Team, or Enterprise)
  2. Enable auto mode for the best experience
  3. Either:
    • Ask Claude to create a workflow directly, or
    • Enable the ultracode setting through the effort menu
  4. Start with a scoped task to understand token usage
  5. Review the plan when Claude asks for confirmation

Read the official documentation to learn more.


What This Means for Engineering Teams

Dynamic workflows represent a fundamental shift in how AI can handle engineering work:

From: Single-threaded AI assistance on isolated tasks To: Orchestrated AI workforce tackling quarter-long projects in days

Impact:

  • Migrations that were previously deferred due to scope become feasible
  • Security audits can be comprehensive rather than sample-based
  • Legacy modernization accelerates from months to weeks
  • Critical architectural decisions get stress-tested before implementation

The coordination happens outside the conversation, so the plan stays on track no matter how big the task gets.


Try Dynamic Workflows Today

curl -fsSL https://claude.ai/install.sh | bash

Or read the documentation to learn more.


Related Reading


Dynamic workflows are available in research preview starting May 28, 2026. Token consumption can be significantly higher than typical sessions—start with scoped tasks to understand usage patterns for your work.

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