PIs built for humans often fail when consumed by AI agents.
They rely on documentation instead of contracts, return unpredictable structures, and break silently when upgraded. Large Language Models (LLMs) and autonomous agents need something different: machine-discoverable, deterministic, idempotent, and lifecycle-managed APIs.
This session introduces a five-phase API readiness framework—from discovery to deprecation—so you can systematically evolve your APIs for safe, predictable AI consumption.
You’ll learn how to assess current APIs, prioritize the ones that matter, and apply modern readiness practices: function/tool calling, schema validation, idempotency, version sunset headers, and agent-aware monitoring.
Problems Solved
What “AI-Readiness” Means
Common Failure Modes Today
Agenda
Introduction: The Shift from Human → Machine Consumption
Why LLMs and agents fundamentally change API design expectations.
Examples of human-centric patterns that break agent workflows.
Pattern 1: Assessment & Readiness Scorecard
How to audit existing APIs for AI-readiness.
Scoring dimensions: discoverability, determinism, idempotency, guardrails, lifecycle maturity.
Sample scorecard matrix and benchmark scoring.
Pattern 2: Prioritization Strategy
How to choose where to start:
Key Framework References
Takeaways
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.