Context Window Full? Save Progress and Resume Cleanly

A “context window full” error means the AI request exceeds the working space available for that model and app. Save the verified state of the work, reduce unnecessary input, and continue in a supported compacted or fresh conversation.

The immediate goal is a safe continuation, especially if the assistant has edited files or started a process. fenbs can hold the task state and next step outside the chat, so a new connected session can recover the work without receiving the entire old conversation.

What should you do immediately?

1. Pause new work. Keep the error message and identify the app and selected model, rather than repeatedly resending the same oversized request.
2. Check the real state of the work. Look at saved files, documents, or task results; distinguish completed actions from suggestions and failed attempts.
3. Save a short handoff outside the conversation. Include approved constraints, what changed, what was checked, what remains uncertain, and the next safe action.
4. Reduce the request or use the app’s supported context controls. Keep only the material needed for the next step, then resume from the saved record.

If the chat still accepts a small message, ask for a handoff and verify it. If it rejects even that, write the handoff yourself from visible evidence. An error at the end of a long session is not a reason to trust a summary more than the actual deliverables.

Does this error mean your work is gone?

The message alone does not tell you that. It concerns the request’s available space, so inspect each place where the assistant was working. A saved document may still exist even when the next message fails. An unsaved suggestion in a conversation is a different situation from an action successfully completed through a tool.

For a coding task, check the changed files before asking the assistant to repeat an edit. For a research task, retain source links and the claims you verified. For a draft, find the latest saved version and label it clearly. Repeating a completed action can create a second problem while you are trying to solve the first.

Mark uncertain actions as uncertain. “The export may have started; check its status before starting another” is a useful handoff. “Export complete” is unsafe unless you have evidence. The same distinction belongs in a task’s progress record and its fenbs handoff.

Why did a short message exceed the limit?

Your latest message is only one part of the input. Tokens, the small text pieces a model counts, can also come from earlier messages, instructions, file contents, and tool results. Output needs space too, although the exact accounting depends on the provider and model.

Anthropic’s context window documentation↗ (opens in a new tab) describes request material and generated output contributing to Claude’s window. That explains why shortening one sentence may not resolve a request carrying a long history. Check your own service’s rules rather than assuming every client handles overflow identically.

Common triggers include attaching several large documents, pasting complete logs, or carrying many rounds of abandoned approaches. A full-window error is also distinct from an account usage limit or a temporary service outage. Preserve the exact wording so you solve the problem the app is actually reporting.

Our AI context window guide explains the underlying concept; the recovery steps here focus on getting an interrupted task moving again.

What belongs in a reliable recovery note?

Write for someone who has never seen the chat. A useful recovery note says what to do and how to verify it, with enough evidence to avoid repeating work. Keep a pointer to the underlying file or source whenever a short summary cannot safely preserve the detail.

• Goal: the specific deliverable the person requested.
• Constraints: approved rules and actions that still need permission.
• Current state: what exists, where it is saved, and what changed.
• Verification: checks actually performed and their results.
• Uncertainty: failed attempts, missing evidence, and unresolved questions.
• Next step: the first action to take, including a status check for anything still running.

Say a design assistant revised a checkout screen before the session stopped. The note should identify the saved design, the approved fields, and the review still needed. “Continue improving checkout” discards the useful boundary and invites another round of changes nobody asked for.

Should you trim, compact, or restart?

Trim when the current request has obvious unnecessary attachments. Use the client’s supported summarizing controls when you want to continue the same task with less history. Start fresh when obsolete approaches and corrections make the conversation harder to trust than a checked recovery note.

For example, Claude Code documents automatic compaction and manual context controls↗ (opens in a new tab). Those controls are specific to that app; do not paste its commands into an unrelated product. Read the resulting summary and recheck any requirement whose exact wording matters before continuing.

Use the separate context window compaction guide for how summarizing history works. Whatever control you choose, keep essential source material available. A shorter account of a contract clause is not a substitute for the clause when the wording is the task.

How do you confirm the restart worked?

Ask the new session to state the goal, governing constraints, verified progress, and next action before it acts. Compare its answer with the recovery note. If it misses an approval or treats an untested change as finished, correct the record at once.

Then give it one bounded step. For example, ask it to inspect the saved design against the approved fields before proposing another edit. A successful reply to a general question does not prove that the assistant recovered the project correctly. The first useful check concerns the work you are resuming.

If the same task fills immediately, inspect what is loaded at startup and which attachment is being added again. Persistent irrelevant context can undermine the session before a limit is reached; AI context rot explains that separate quality problem.

How to do this with fenbs

1. Create a free account. Start a project for the interrupted work; one person can use fenbs free, with no credit card.
2. Add or update the affected tasks with their actual state. Record completed checks, failures, and remaining uncertainty rather than copying the conversation.
3. Save the project’s Where we left off. Name the next step, anything still running, and what needs a person’s answer.
4. Connect your supported AI app from Integrations, then ask the fresh session to read the project context and explain its starting point before acting.

fenbs does not recover inaccessible chats or increase a model’s limit. For a one-time question with no ongoing work, removing an unnecessary attachment may be all you need. For repeated sessions, the context engineering hub covers ways to make a clear starting record routine.