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deepmind.google·6d ago
AI Engineering
VS Code Blog·4 min read
Making agents practical for real-world development
TL;DR
Researchers identified a gap in LLM evaluation benchmarks. They built a synthetic dataset with 10k adversarial prompts targeting reasoning failures.
✦ Why It Matters
Use this benchmark to audit LLM robustness before deploying in production reasoning pipelines.
Key Takeaways
- Utilize the /compact command to manage session history effectively.
- Guide agents mid-response to refine their output without restarting.
- Fork chat sessions to explore multiple design options seamlessly.
- Implement hooks to automate compliance with project standards.
How It Works
Agents in Visual Studio Code now retain memory across sessions, allowing them to remember user preferences and project context. This is achieved through improved context management that prioritizes relevant information and allows users to control what is retained or discarded.
The ability to guide agents during their response generation helps maintain focus on the task at hand.