Principles of Building AI Agents
Building effective agents
anthropic.com
An agent can be thought of as a logical wrapper around an LLM, allowing us to add several features to our AI systems, primarily:
- Tool usage, such as calling APIs for info, executing code,
- Internal thoughts over multiple generation steps
- Ability to use various tools and reasoning steps to answer more complex queries.
- Parallel agents can go and complete
James Briggs • LLMs Are Not All You Need | Pinecone
Agentic workflows are loops —they can run many times in a row without needing a human involved for each step in the task. A language model will make a plan based on your prompt, utilize tools like a web browser to execute on that plan, ask itself if that answer is right, and close the loop by getting back to you with that answer. If you ask, “What ... See more
Evan Armstrong • What Are AI Agents—And Who Profits From Them?
The Complete Beginners Guide To Autonomous Agents
mattprd.com
A practical guide to building agents
Guide to building AI agents using large language models, covering agent definition, use case selection, design components, single/multi-agent orchestration, tool integration, instruction setup, safety guardrails, and deployment best practices.
cdn.openai.comAutonomous agents are programs, powered by AI, that when given an objective are able to create tasks for themselves, complete tasks, create new tasks, reprioritize their task list, complete the new top task, and loop until their objective is reached.