Keep a long autonomous coding task goal-directed by preserving the original objective outside the chat, splitting the work into bounded steps with explicit acceptance checks, and updating progress only after you verify the result. A longer context or a compressed transcript can help an agent continue, but neither proves that it stayed aligned or finished the work.
Why long coding sessions drift
A broad request is not a plan for sustained execution. In an account of its work on long-running agents, Anthropic describes agents attempting too much at once, running out of context mid-implementation, and leaving the next session without a reliable record of what had happened. A later session could then mistake visible partial progress for completion. Anthropic’s engineering article on long-running agents
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That failure pattern has three parts: the objective becomes less salient than the latest subtask; important decisions or unfinished work disappear at a context boundary; and progress is recorded as a claim rather than as verified state. Context compaction addresses only the amount of conversation an agent can carry forward. As Anthropic puts it, “However, compaction isn’t sufficient.”
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Store the durable objective and constraints somewhere the next run can read them, such as a project brief or task-state file. Keep it distinct from the current step: the overall goal should remain stable, while the next action can change as implementation and verification reveal new information.
#1 Best Overall
- Goal: the user-visible outcome the project must deliver.
- Constraints: requirements that must remain true, including scope boundaries and relevant technical or compatibility limits.
- Current task: one small change the agent is expected to make now.
- Acceptance checks: observable results that would demonstrate the task is complete.
This separation reflects the task-state approach described in the LongHorizon-Harness paper: a manager derives a bounded subtask from the original objective and verified state, an executor works on it, and an auditor checks the resulting environment independently.
Turn the next action into a bounded work unit
Before execution, define the expected change, how to check it, and what is explicitly outside the step. This makes it easier to detect when an agent is expanding scope or stopping at an incomplete intermediate result.
Example task brief
Overall goal: Add a CSV export option to the reports page without changing existing report behavior or permissions constraints described in the project brief.
Current task: Add the export control and connect it to the existing report data.
Expected result: A user can download the displayed report as CSV.
Acceptance checks: The export contains the displayed report's columns and rows; existing report behavior remains unchanged; relevant tests pass.
Out of scope: Changing report filters, permissions, or other export formats.
On failure: Record the failing check and evidence; do not mark this task complete.The example illustrates a format, not a claim about a particular application. Adapt the checks to the actual codebase: identify expected behavior, relevant tests or other evidence, and work that must wait for a separate step.
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Run each step, inspect it, then record progress
- Give the agent one bounded task. Include the durable goal and constraints, but ask it to focus on the current step rather than to finish the entire project in one run.
- Inspect the change. Review the resulting diff or other artifacts for scope, unintended changes, and consistency with the task brief.
- Run relevant checks. Use the project’s applicable tests or checks and inspect their results. A claim in the conversation that a check passed is not the same as evidence that it did.
- Update state only after verification. Record what is complete, the evidence supporting that status, failures or unresolved issues, and the next bounded task.
- Revise or retry when checks fail. Keep the failure evidence and adjust the task or implementation instead of silently treating the step as done.
Verification can expose residual risk and help recover from some delivery failures, but it cannot guarantee success. The OneDayAgent paper reports a 0.821 overall score for GLM-5.2 on its 104-task AgentIF-OneDay benchmark; that result is specific to the system and evaluation, not a general estimate of coding-task success.
Make context-boundary handoffs actionable
When a run ends, the next one should be able to resume from durable state and inspectable project artifacts, not from a compressed recollection of every conversation turn. Anthropic describes an initializer that prepares the environment and an agent that makes incremental progress while leaving useful artifacts for a later session.
A practical handoff records the objective, verified state, remaining work, and how to proceed. For example:
Rank #4
Objective: [state the durable project outcome and constraints]
Verified complete: [steps and the evidence checked]
Current state: [relevant files, behavior, or environment facts]
Open work: [remaining bounded tasks]
Known failures or risks: [check, observed result, and unresolved issue]
Next step: [one task with its acceptance checks]
Do not assume: [unfinished or unverified claims]The bracketed text here indicates fields to fill in; it is not a literal instruction to the coding agent. Keep the handoff concise enough to use, but specific enough that a new run can distinguish verified facts from assumptions.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsChoose how much harness structure the task needs
For a small task, a durable brief, a bounded prompt, and manual review may be enough. Longer or more consequential work benefits from stronger separation between planning, execution, state updates, and auditing. The long-horizon agents survey groups harness functions into loops and workflows, context and memory, tools, orchestration, hooks, and verification. These are design dimensions to consider, not a requirement to add every mechanism to every project.
Best Value
Compare an approach by whether it preserves the goal across sessions, defines a testable next step, keeps compact verified state and useful artifacts, independently inspects results, and recovers cleanly when a step fails. The LongHorizon-Harness paper reports results for Qwen 3.7-Plus with its harness of 80.7% versus 51.8% on WeaveBench, 77.2% versus 69.7% on Terminal-Bench 2.1, and 8.3% versus 2.8% on OSWorld 2.0. These are results for the named model, harness, and benchmark setups; they do not establish that the same gains will occur in an everyday software project.
Manage context without confusing compression with progress
Keep immediate execution detail available while preserving a shorter, stable record of the task’s meaning and verified state. At milestones, update that durable record and remove conversational detail that is no longer needed. The goal is not to retain every token; it is to retain the information required to continue correctly.
The 2025 paper “Context as a Tool” describes a workspace combining stable task semantics, condensed long-term memory, and high-fidelity short-term interactions, with proactive context folding at milestones. It reports a 57.6% solved rate for SWE-Compressor on SWE-Bench-Verified. That is a paper-reported result for that system and benchmark, not an expected improvement for a typical project or proof that context folding alone prevents drift.
Use a progress ledger that distinguishes evidence from claims
A simple ledger can prevent the next run from treating an attempted change as a verified result. Use explicit status labels and attach the evidence that justifies each completed item.
- Planned: not yet attempted.
- In progress: work has begun, but acceptance checks are incomplete.
- Verified: the expected behavior or artifact was inspected and the relevant checks passed.
- Blocked: an obstacle remains; record what failed and what information or change is needed.
Do not mark a task verified just because code exists, a test was attempted, or the agent says the change is complete. If the environment cannot support a check, record that limitation and leave the status unverified rather than implying a result.
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