Dealing with fairly complex features #2914
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Great question — context window exhaustion during implementation is a known challenge for any coding agent session The Option 1: Limit how many tasks run per invocationInstead of letting implement run through all tasks at once, tell it to stop early: /implement only execute tasks 1-10, then stop and report progressor scope by phase: /implement only execute the Setup phase, then stopSince completed tasks are marked Option 2: Instruct the agent to use sub-agentsIf your coding agent supports sub-agents (e.g., Copilot CLI, VS Code Copilot), you can instruct implement to delegate individual tasks: /implement delegate each parallel [P] task to a sub-agentEach sub-agent gets a focused context (one task + relevant plan excerpts) rather than the full feature context, so compaction never triggers. Option 3: Combine bothFor very large features: /implement execute only the Core phase, delegate [P] tasks to sub-agentsWhich approach to choose
The "spec of specs" idea you mentioned maps to that third row — breaking the feature into independently spec'd sub-features, each with their own plan/tasks/implement cycle. That's a valid approach for truly massive features, but for most cases limiting task scope per run is the simplest fix. |
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Hi,
we observe that on large / complex features everything went's smoothely until the implementation starts.
In the middle of the run, the LLMs start to halluzinate and loosing completely track + ignoring the plan / tasks / .. . We observe that everything goes south, when or closely before the compaction is triggered.
We understand that the context window running full is most likely the issue.
But what's the best strategy here?
Doing a spec of specs (eg let spec kit on the first iteration break down everything into smaller sub-specs) or let the implementation task focus only on a segment of tasks that may not overwhelm the model?
How do you approach these issues?
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