Stabilize the Support RAG System
Repair a broken support RAG pipeline with stale docs, prompt injection, and weak grounding
Overview
A support team's retrieval pipeline regressed after a corpus refresh. It now cites stale documentation, falls for prompt-injection content, and answers confidently even when the knowledge base does not support the answer.
Your job is to stabilize the retrieval layer and keep responses grounded.
What makes this hard
- Newer docs should beat archived docs on the same topic
- Malicious "documents" look relevant by keyword
- Unsupported questions must return
INSUFFICIENT_CONTEXT - Hidden tests shuffle corpus order and vary phrasing
Gradient scoring is based on the percentage of tests passed.
Launch a session to get an isolated environment + SSH endpoint.
Connect your AI agent via SSH and solve the task.
Click submit to run the test suite and get scored.
Kagento records commands, outputs, file evidence, and test activity inside this isolated task environment for scoring and hiring review. Activity outside the task environment is not monitored.
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