claude-code - 💡(How to fix) Fix [BUG] Dispatch burns tokens unnecessarily! Makes me want to move away from Max Plan! Competitor is better! [1 comments, 2 participants]

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anthropics/claude-code#46710Fetched 2026-04-12 13:35:05
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Error Message

Error Messages/Logs

Fix Action

Fix / Workaround

Bug 1: No context compression or session rollover Long Dispatch sessions accumulate tokens until the limit is hit mid-task with no warning, no compression, and no recovery path. There is no way to summarize and continue. Workflows are interrupted and context is lost. Bug 2: No model selection in Dispatch Users on Max 5x ($100/mo) are forced through the heaviest model for every task including trivial ones where Haiku would be sufficient. There is no model selector in the Dispatch UI. This burns limits faster and removes cost/speed control entirely. Bug 3: No new thread option in Dispatch There is no "New Thread" button in Dispatch. When a session hits limits or users need a clean context, there is no in-app reset path. This compounds Bug 1 — context doesn't compress and there's no escape valve. Business impact: I am a Max plan subscriber at $100/month. These three failures together make Dispatch unusable for sustained development workflows. Competing tools at $20/month are delivering more productive output per dollar. I am actively moving my spend to a competitor as a direct result of these unresolved issues. Anthropic is losing a paying Max plan customer over fixable UX gaps.

Long Dispatch sessions accumulate tokens until the limit is hit mid-task with no warning, no compression, and no recovery path. There’s also no model selector (forces heaviest model even for trivial tasks) and no “New Thread” button to reset context, so workflows get interrupted and context is lost.

Start a Dispatch session and keep working until token limit is reached. Observe no compression, no rollover, and no way to summarize and continue. Try to switch model or start a clean context - no UI controls available.

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Preflight Checklist

  • I have searched existing issues and this hasn't been reported yet
  • This is a single bug report (please file separate reports for different bugs)
  • I am using the latest version of Claude Code

What's Wrong?

Bug 1: No context compression or session rollover Long Dispatch sessions accumulate tokens until the limit is hit mid-task with no warning, no compression, and no recovery path. There is no way to summarize and continue. Workflows are interrupted and context is lost. Bug 2: No model selection in Dispatch Users on Max 5x ($100/mo) are forced through the heaviest model for every task including trivial ones where Haiku would be sufficient. There is no model selector in the Dispatch UI. This burns limits faster and removes cost/speed control entirely. Bug 3: No new thread option in Dispatch There is no "New Thread" button in Dispatch. When a session hits limits or users need a clean context, there is no in-app reset path. This compounds Bug 1 — context doesn't compress and there's no escape valve. Business impact: I am a Max plan subscriber at $100/month. These three failures together make Dispatch unusable for sustained development workflows. Competing tools at $20/month are delivering more productive output per dollar. I am actively moving my spend to a competitor as a direct result of these unresolved issues. Anthropic is losing a paying Max plan customer over fixable UX gaps.

Long Dispatch sessions accumulate tokens until the limit is hit mid-task with no warning, no compression, and no recovery path. There’s also no model selector (forces heaviest model even for trivial tasks) and no “New Thread” button to reset context, so workflows get interrupted and context is lost.

What Should Happen?

Context compression/session rollover, model selector, and a New Thread option to continue cleanly.

Error Messages/Logs

Steps to Reproduce

Start a Dispatch session and keep working until token limit is reached. Observe no compression, no rollover, and no way to summarize and continue. Try to switch model or start a clean context - no UI controls available.

Claude Model

Sonnet (default)

Is this a regression?

I don't know

Last Working Version

No response

Claude Code Version

1.1617.0

Platform

Anthropic API

Operating System

macOS

Terminal/Shell

Terminal.app (macOS)

Additional Information

No response

extent analysis

TL;DR

To address the issues with Dispatch, consider implementing context compression, adding a model selector, and introducing a "New Thread" button to improve workflow continuity and control.

Guidance

  • Implement context compression or session rollover: This would allow for the summarization and continuation of workflows without losing context when the token limit is reached.
  • Add a model selector to the Dispatch UI: This would enable users to choose the most suitable model for their tasks, potentially reducing the burn rate of limits and providing cost and speed control.
  • Introduce a "New Thread" button: This feature would offer a reset path for users when sessions hit limits or when a clean context is needed, mitigating the issue of context loss.
  • Review and adjust the default model assignment: Ensure that the default model (currently Sonnet) is appropriately assigned and consider making adjustments to allow for more flexible model selection based on task requirements.

Example

No specific code snippet can be provided without more detailed information on the implementation, but the solution would involve modifying the Dispatch UI and backend logic to incorporate the suggested features.

Notes

The provided information does not specify the technical details of the Anthropic API or the Claude Code implementation, so the guidance is focused on the functional requirements and user experience improvements.

Recommendation

Apply a workaround by manually managing sessions and tasks to minimize the impact of the current limitations until the suggested features are implemented. This could involve regularly starting new sessions or tasks to avoid hitting the token limit and manually selecting the most appropriate model for each task when possible.

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