ElevenAgents Introduces 'Procedures' for AI Agent Playbooks



Key takeaways
- ElevenAgents now offers "Procedures" for defining AI agent behavior.
- Procedures can be structured for fixed steps or free-form for adaptability.
- Existing SOPs can be imported to create agent playbooks.
- The feature aims to improve customer outcomes and operational efficiency.
Who benefits
Summary
ElevenAgents has launched 'Procedures,' a new feature allowing users to define how AI agents operate through structured or free-form playbooks. This enables agents to follow standard operating procedures for tasks ranging from customer refunds to upsell conversions.
Why it matters
This innovation allows businesses to standardize AI agent behavior, ensuring consistent service delivery and improved operational efficiency in customer interactions. It directly impacts customer satisfaction and business metrics like conversion and resolution rates.
How to implement this in your domain
- 1Define specific customer interaction scenarios that require standardized responses or actions.
- 2Import existing Standard Operating Procedures (SOPs) into ElevenAgents to automatically draft agent procedures.
- 3Customize and refine the drafted procedures, choosing between structured steps or free-form adaptability based on task complexity.
- 4Deploy the new procedures to AI agents to automate responses for common queries like refunds or upsells.
- 5Monitor agent performance and customer outcomes to continuously optimize and iterate on the defined procedures.
Original post by @ElevenLabs
"Introducing Procedures in ElevenAgents - packaged playbooks that let you define how agents operate. Just as employees follow standard operating procedures (SOPs), Procedures provide agents with a set of instructions to follow in common scenarios. Procedures enable agents to handl…"
View on XPrimary sources
Originally posted by @ElevenLabs on X · view source
Want to go deeper?
Turn these trends into skills with Learnijoy's hands-on AI & tech courses.
Explore coursesMore in AI Engineering & DevTools
Zapier vs. Tray: Enterprise Automation Platform Comparison for 2026
This post compares Zapier and Tray.io, evaluating which platform is better suited for enterprise automation needs by balancing power and ease of use. It argues that the best tools scale for complex requirements while remaining intuitive for all users.
Designing Custom Reward Functions for Multi-Turn RL in Amazon Nova Forge
This post details how to create composite multi-turn reward functions for Amazon Nova Forge, including safe execution of model-generated code and instrumentation to prevent reward function failures. It emphasizes the critical role of reward functions in guiding model learning in multi-turn reinforcement learning.
Multi-Agent Workflows with SageMaker AI and Bedrock AgentCore
This post demonstrates how to construct multi-agent workflows by integrating OpenAI-compatible endpoints on Amazon SageMaker AI with Amazon Bedrock AgentCore. It highlights the ability to assign specialized agents to specific tasks using optimal models and provides methods for achieving token-level observability from SageMaker endpoints.