AI-Augmented Microservices Design - Agent friendly APIs - Full day
AI agents and LLMs are no longer side clients—they are becoming primary API consumers. Traditional API design isn’t enough. APIs must now be machine-parsable, agent-aware, retry-safe, and resilient under autonomous orchestration.
This full-day workshop gives you a step-by-step playbook to design APIs that are:
Discoverable (introspectable contracts, JSON-LD hints).
Secure (agent-specific guardrails, rate limits, prompt-injection protection).
Resilient (idempotency, retry safety, observability).
Domain-ready (patterns for e-commerce, healthcare, insurance, and manufacturing).
Audience: API & Platform Architects, Backend Engineers, Cloud-native teams, Product API leaders
Outcomes: Participants leave with 10 AI themes + checklists for building agent-ready, enterprise-resilient APIs.
Module 1 – Foundations of AI-Ready Microservices
- AI as the New API Consumer → Why APIs must evolve.
- From Human-Friendly to Machine-Parsable → Contracts, schemas, and discoverability.
Module 2 – Designing Agent-Aware Endpoints
- Guardrails for Intelligent Agents → Policy as code, abuse prevention, prompt-injection safety.
- Idempotency as a Survival Skill → Retry safety and compensations.
Module 3 – Security & Observability in the Age of AI
- Security for Human vs Agent Clients → Auth strategies, scopes, and quotas.
- Observability for AI Traffic → Tagging, tracing, anomaly detection, effectiveness metrics.
Module 4 – Domain-Specific AI Microservice Patterns
- Domain-Aware AI Patterns →
- E-commerce: Carts, orders, inventory.
- Manufacturing: IoT ingestion, MES/ERP integration.
- Insurance: Claims, underwriting, explainability.
- Healthcare: FHIR APIs, HIPAA compliance, consent.
Module 5 – Lifecycle & Tooling for AI-Integrated APIs
- Evolving API Contracts for AI Lifecycles → Versioning, CDC testing, deprecation policies.
- LLM Toolchain Integrations → OpenAI function calling, LangChain, Bedrock Agents.
Module 6 – Resilience & Enterprise-Scale Adoption
- Enterprise Resilience in the Age of AI → Bulkheads, degraded modes, regional failover.
- Maturity model for AI-augmented APIs.
- End-to-end architecture example.
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of AI & Data Architecture at Salesforce, where he focuses on enterprise AI, agentic systems, cloud-native architecture, distributed systems, data platforms, security, and large-scale transformation.
Over his career, Rohit has designed and led complex enterprise platforms across AWS, Google Cloud, microservices, real-time data, API ecosystems, resilient distributed systems, and AI-enabled architectures. His work increasingly focuses on the challenges enterprises face as software evolves from deterministic services to AI-native and agentic systems—particularly around reliability, governance, evidence, security, observability, cost, and safe autonomy.
Rohit is the author of System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems, published by Apress. The book presents a modern approach to system design covering scalability, distributed systems, AI architecture primitives, security, reliability, economics, agentic systems, and real-world architectures including e-commerce, ride sharing, payments, fraud detection, messaging, video streaming, file storage, and search. (Springer Link)
Book:
Amazon: https://a.co/d/09Zs1twa
Publisher / Springer Nature: https://link.springer.com/book/10.1007/979-8-8688-2782-2
O'Reilly: https://learning.oreilly.com/library/view/system-design-with/9798868827822/
Rohit is also an O’Reilly instructor and a frequent speaker at technology conferences including No Fluff Just Stuff, UberConf, GIDS, and other international events. His talks focus on practical architecture lessons from building and operating complex systems, including AI control planes, trusted agents, inference at scale, evidence-first RAG, AI security, distributed-system failure, and AI-era software architecture.
As a trusted advisor and architecture leader, Rohit works at the intersection of business strategy and deep technical architecture—helping teams translate complex business problems into scalable, resilient, secure, and economically sustainable systems.
Rohit holds an MBA in Corporate Entrepreneurship from Babson College and graduate-level education in Computer Science from Boston University and Harvard University.
Connect with Rohit:
LinkedIn: http://linkedin.com/in/rohit-bhardwaj-cloud
X / Twitter: @rbhardwaj1