Implement agent interfaces as classes for specialist roles and orchestrate them via a 'chain of debate' logic to collaboratively solve complex tasks.

Using Shift+Tab in the CLI toggles between 'ask' mode (research only) and 'agent' mode (action execution) in Claude, allowing controlled orchestration...Show more

Replicate a published agent study architecture by wiring LangGraph to LangChain and LangSmith, creating a chat-based agent in TypeScript.

Use the SD bench dataset as an evaluation set to benchmark agent vs physician performance in a controlled study.

The system applies Bayesian probability by iteratively eliminating least probable diagnoses until a confidence threshold is reached.

A two-agent swarm architecture uses a gatekeeper agent to filter cases and a diagnostic agent to adjudicate final diagnoses, coordinating via a define...Show more

Combine graph-based data structures with LangChain to build an interactive medical questioning agent that can be turned into a product.

Use publicly available test cost databases and open question sets from journals to replicate medical AI research with existing LLMs.

Their Mai DXO ensemble achieved 80% diagnostic accuracy at ~$2.5K test cost, versus $8K for a single O3 model, and 50% accuracy with only question-bas...Show more

They overlaid standardized US medical test pricing plus a $300 consult fee per patient query to jointly evaluate diagnostic accuracy and incurred test...Show more

A gatekeeper agent synthesizes and returns real or fabricated test results to prevent reward hacking when an LLM swarm infers lack of data as negative...Show more

They designed a swarm of O3-based LLM personas (challenger, checklist, hypothesis generator, test-ordering, stewardship) orchestrated via a chain-of-d...Show more

Researchers built SDbench, a 304-case sequential diagnostic benchmark from New England Journal of Medicine case proceedings to evaluate iterative AI d...Show more

Use publicly available medical case datasets—such as those from the New England Journal of Medicine or Hugging Face benchmarks—and evaluate AI agent p...Show more

Adopt a modular multi-agent pipeline where each agent specializes in steps like data extraction, reasoning, and diagnosis, as demonstrated by Microsof...Show more

Use a small offline LLM with limited context window to handle upfront tasks like categorization before routing to a larger model.

The MLX framework provides an adapter to run the Gemma 3N multimodal model on Apple devices by integrating into on-device deployment pipelines.

Gemma 3N uses a nested architecture with 2 billion active parameters out of 4 billion total to drastically cut computational requirements while retain...Show more

Use Cloudflare’s AI House of Mirrors pattern to detect AI crawlers and serve self-referencing garbage content that wastes their tokens and keeps them ...Show more

Adopt a microtransaction-based API gating pattern to monetize real-time LLM crawler requests and control content ingestion using an infrastructure lay...Show more