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Decision frameworks

When to use what: agents vs prompts, build vs buy. 6 on file.

Agents and automation5Coding5Planning and PM4Learning and teaching1Writing1ChatGPT1
30 min Harnessed Agentic RL for AI Agent Training Use the actual agent harness during RL training to avoid reimplementation and ensure consistency. Harnessed Agentic RL is a training paradigm where the agent harness used in deployment is directly involved in reinforcement learning. This avoids the need to reimplement the agent within the training framework, reducing costs and ensuring the trained agent behaves like the deployed one. Agents and automation Microsoft Research Blog
2 min RCTC framework for structured prompt generation A structured approach to prompt engineering using Role, Context, Task, and Constraint. The Role-Context-Task-Constraint (RCTC) framework helps create structured prompts. It guides users to define the AI's role, provide context, state the task, and set constraints, improving prompt clarity and AI output quality. Writing Google Cloud Tech on YouTube

More decision frameworks

5 min Choose between workflows and agents based on task predictability. Use workflows for predictable tasks and agents for flexible, model-driven decision-making at scale. Agents and automation Anthropic Engineering
60 min Framework for routing AI coding agent prompts using a custom classifier Use a custom router with a classifier to label prompts and direct them to the appropriate AI agent or model. Coding arXiv cs.AI
10 min When to use agents versus regular chat or API workflows Use agents for repeatable workflows, regular chat for one-off tasks, and APIs for deterministic processes. ChatGPT Agents and automation OpenAI News
5 min When to use Triton for GPU programming Use Triton for writing efficient GPU kernels when performance is critical and CUDA expertise is limited. Coding OpenAI News