Not all AI agents are created equal

2026-04-14 · Source: Lenny's Newsletter · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Project & Product Management · Depth: Intermediate, long

Summary

This guide, developed by Hamza Farooq and Jaya Rajwani, categorizes AI agents into three architectural types to help organizations prioritize development initiatives effectively. Many teams struggle with agent prioritization because they compare fundamentally different systems using the same metrics. The framework outlines Deterministic Automation (Category 1) for predefined workflows with AI handling content, Reasoning and Acting Agents (Category 2) where AI dynamically decides actions using tools, and Multi-Agent Networks (Category 3) involving multiple specialized agents coordinating tasks. The article details the characteristics, suitable tools (e.g., n8n for Category 1, LangGraph for Category 2), prioritization criteria, and evaluation metrics for each category, emphasizing that categorization is crucial for determining complexity, required skills, timelines, operational costs, and success measurement.

Key takeaway

For AI Product Managers and Directors of AI/ML struggling to prioritize agent initiatives, first categorize your backlog ideas into Deterministic Automation, Reasoning and Acting, or Multi-Agent Networks. This will clarify complexity, resource needs, and timelines, preventing misallocation of effort and ensuring you select the right tools and metrics for each project. Focus on Category 1 projects for early wins and measurable ROI before tackling more complex Category 2 or 3 systems.

Key insights

Categorizing AI agents by architecture is crucial for effective prioritization and resource allocation.

Principles

• Prioritize agent initiatives based on architectural complexity.
• Match agent type to problem scope for optimal outcomes.
• Over-engineering solutions adds unnecessary complexity and cost.

Method

The proposed decision framework involves a 5-minute triage process to categorize agent ideas into one of three architectural types, then selecting appropriate tools, defining success metrics, and identifying warning signs for re-evaluation.

In practice

• Start with Category 1 agents for quick ROI and limited AI engineering capacity.
• Use n8n or Zapier for deterministic automation workflows.
• Evaluate Category 1 agents by workflow completion rate and cost per workflow.

Topics

• AI Agent Categorization
• Deterministic Automation
• Reasoning and Acting Agents
• Multi-Agent Networks
• AI Project Prioritization

Code references

• traversaal-ai/agents-in-action

Best for: AI Product Manager, Director of AI/ML, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Lenny's Newsletter.