Your API Is Not Ready for AI (Yet): A Lifecycle Readiness Guide

APIs designed for humans break when consumed by LLMs and autonomous agents. Documentation isn’t enough—endpoints must be machine-discoverable, deterministic, idempotent, and versioned with clear deprecation signals. This talk gives you a pragmatic lifecycle readiness framework: assess your current APIs, prioritize the ones that matter, and execute a phased roadmap (discovery → redesign → versioning → monitoring → deprecation). We’ll align with current best practices for function/tool calling, prompt-injection defenses, idempotency, and version sunset/deprecation headers, and show how to instrument agent traffic so you can govern cost and risk. You’ll leave with a scorecard, checklists, and KPIs to move from “works for humans” to agent-friendly, enterprise-grade APIs.

What “AI-Readiness” Means

  • Machine-discoverable: APIs described in OpenAPI 3.1 + JSON Schema, not just prose docs.
  • Deterministic: Same input → same output shape every time.
  • Idempotent: Agents can retry safely without duplicate side effects.
  • Guardrailed: Schema validation, quotas, and prompt-injection defenses at the edge.
  • Lifecycle managed: Versioning, Sunset/Deprecation headers, contract tests, and migration guides.

Common Failure Modes Today

  • Polymorphic responses (different shapes → agent confusion).
  • Ambiguous error messages with no codes or remediation.
  • Missing idempotency → duplicate orders, payments, claims.
  • Hidden side effects not documented → agents fail or loop.
  • Silent breaking changes → long-lived agents stop working.

Assessment Framework (API Readiness Scorecard)

Prioritization Strategy

  • High traffic + high risk APIs first (payments, claims, healthcare, orders).
  • Partner & customer-facing APIs over internal ones.
  • Regulated domains (HIPAA, PCI) before non-regulated.
  • Consolidate changes (schema + idempotency + security) together to reduce churn.

Roadmap Phases

  1. Discovery: Audit specs, tag agent traffic, collect gaps.
  2. Redesign: Harden schemas, add idempotency keys, fix error grammar, add prompt-injection guardrails.
  3. Versioning: Adopt SemVer, support multiple versions, emit Deprecation/Sunset headers.
  4. Monitoring: Dashboards for agent vs human usage, retries, anomalies.
  5. Deprecation: Communicate timelines, progressive throttles, safe fallback modes.

Case Studies / Examples

  • Stripe Idempotency: Solved duplicate charge risk with Idempotency-Key.
  • Deprecation Done Right: APIs with Sunset headers → agents migrated smoothly.
  • Agent Tools: Mapping operationId=ReserveInventory directly to an LLM tool with strict schema.

Takeaways

  • Docs aren’t enough → agents need contracts, determinism, and schemas.
  • Most APIs today will fail agents (polymorphism, hidden side effects, poor errors).
  • Use the Readiness Scorecard to measure and prioritize which APIs to fix first.
  • Follow the 5-phase roadmap: Discovery → Redesign → Versioning → Monitoring → Deprecation.
  • With checklists and KPIs, you can evolve from human-centric APIs to agent-ready, enterprise-grade APIs.

Rohit Bhardwaj

About Rohit Bhardwaj

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.

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