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This workflow separates Claude Code’s planning from the model that writes code: Claude Code can start in its documented plan permission mode, while a separately configured local model handles implementation. The split may reduce how much work depends on a hosted model, but the title alone does not identify the local model, runtime, hardware, or usage period behind the claim of never hitting a limit. Treat that outcome as a personal report, not a guaranteed result.
What this workflow means—and what it does not
Claude Code is a client that runs on your machine, but Anthropic says it sends prompts and model outputs over the network to interact with the language model. Running the client locally is not the same as running the model locally. Anthropic’s data-usage documentation explains that distinction.
In this split workflow, Claude Code is used to plan a task, and a distinct local model is used to build or edit the code. Anthropic documents a Claude Code plan permission mode; its documentation does not establish that Claude Code itself hands implementation work to a local model. That second stage needs its own model, runtime, and connection or integration setup.
What Claude Code’s plan mode does
The CLI reference documents --permission-mode plan as a way to begin in plan mode. It is a permission mode within Claude Code—not a setting that switches Claude Code to a local model or proves that another model is performing the implementation. See Anthropic’s CLI reference.
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Use the plan stage to ask for a bounded implementation outline: the files likely to change, key decisions, dependencies, risks, and checks to run. Review that outline before sending the work to the local building stage. This is a practical way to separate design from execution; the documented option alone does not provide or configure the separate local stage.
What the available documentation establishes
- Claude Code needs network access. Anthropic’s setup documentation says an internet connection is required for authentication and AI processing. The client runs locally, but it communicates with an LLM over the network. Setup and connection requirements and data handling cover these points.
- There are multiple documented authentication paths. The setup page lists Anthropic Console, Claude app subscriptions, and enterprise platforms. The available path depends on the account and organization setup.
- Plan mode is not a local-model integration. The CLI reference describes the permission mode, but does not specify how to connect a separate local model for building.
- Usage management is not unlimited access. Anthropic describes gateway capabilities including centralized authentication, usage tracking, cost controls, audit logging, and provider routing. Those controls can help manage usage; they do not promise that a user will never encounter provider limits. Anthropic’s LLM gateway documentation also identifies LiteLLM as a third-party proxy that Anthropic does not endorse, maintain, or audit for security or functionality.
Why the “never hit my usage limits” result cannot be generalized
The claim is personal, and its scope is not specified: there is no named local model or runtime, machine configuration, account type, workload, or observation period. Without those details, it is not possible to reproduce the setup, assess how much work moved off a hosted service, or conclude that another user would avoid limits.
A local building stage could reduce reliance on a hosted model for implementation if that stage really runs inference on the user’s machine. But the documentation cited here does not verify that the title’s setup does so, identify its components, or demonstrate that the hosted planning stage never reaches a limit. Claude Code’s network and authentication requirements remain relevant to its planning stage.
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What to verify before relying on the split
- Identify the local stage. Record the exact model and runtime, and confirm where inference takes place. A local interface or client alone does not establish local inference.
- Check the handoff. Determine how the plan reaches the builder and whether a person reviews it before code is changed. The cited Claude Code plan option does not configure this handoff.
- Know what remains provider-dependent. Claude Code requires network access for authentication and AI processing, so the planning stage still depends on its configured service and account.
- Track actual usage over a defined period. Usage controls and tracking can make consumption more visible, but only a measured period on a specified setup can support a personal claim about avoiding limits.
- Plan for service or machine unavailability. A split workflow relies on distinct stages; establish what work can continue if the hosted planning service or local model runtime is unavailable.
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