Binu Babu

AI Product Consultant

AI & Gen AI Agents Playbook

Strategic Framework for Agentic Orchestration

AI & Gen AI Agents Playbook

Cross-Cutting Themes → Strategy → Engineering → Orchestration → Scale

Comprehensive framework for building production-ready agentic systems in an era of rapid disruption

Strategic Context: The AI Revolution

The Shift to Agentic AI

We are moving beyond text generation to autonomous execution. Defensibility no longer comes from the model itself (which is commoditized), but from the orchestration of agentic workflows that integrate with proprietary data.

Focus on building systems that solve complex, multi-step business problems through reliable tool-calling and recursive state management.

Engineering for Reliability

90% of Gen AI experiments fail because they aren't engineered for production. This playbook focuses on the rigorous engineering required to make agents reliable, observable, and safe for enterprise deployment.

Build products that fundamentally change how work gets done, creating new value chains through agentic autonomy.

How to Use This Playbook

  • Start with Cross-Cutting Themes: These foundational elements should be established before Phase 1
  • Sequential but Iterative: Follow phases in order, but expect to loop back as you learn
  • Customize for Context: Not every item applies to every product. Prioritize based on your needs
  • Metrics-Driven: Define success metrics at each phase and track religiously
  • Cross-Functional: This requires engineering, design, sales, marketing, and support throughout

Strategic Success Factors

Customer Centricity

Always start with customer needs, validate continuously, and iterate based on feedback. In AI products, this means understanding not just what customers want, but how AI can fundamentally change their workflows and outcomes.

Data-Driven Decisions

Define metrics early, measure everything, let data guide your strategy. AI products require sophisticated measurement frameworks that capture both technical performance and business impact.

Speed & Iteration

Ship fast, learn quickly, and iterate. Perfect is the enemy of good. In AI development, rapid iteration is crucial for model improvement and feature validation.

Cross-Functional Collaboration

Break down silos, align teams, and work together toward shared goals. AI products require deep collaboration between product, engineering, data science, and business teams.