Burp Suite[Tryhackme WalkThrough]

The relationship between context, memory, and hallucination is more subtle than simply giving a model more information. A larger context window can still contain irrelevant or contradictory data, while long-term memory can preserve outdated assumptions and reintroduce them with false confidence. Reliable AI systems therefore need more than storage: they need source attribution, timestamps, relevance filtering, clear memory boundaries, and a way for users to correct or delete inaccurate information. It would also be valuable to evaluate retrieval failures separately from generation failures, since a model may hallucinate because the correct evidence was never retrieved—or because it ignored evidence that was available. This distinction is essential when debugging production AI applications.