Agentic Systems Engineer — Claude Cert Academy

Architect autonomous agents that ship.

The engineering certification for developers who build production-grade agentic systems. Five domain modules covering memory architecture, agent evaluation, advanced orchestration, production reliability, and safety at scale — each mapped to a 60-question proctored exam.

What you'll learn

• Design and implement memory architectures (RAG, episodic, semantic caching) for long-running agents
• Build evaluation harnesses that catch regressions before they reach production
• Apply advanced orchestration patterns: critic agents, swarms, dynamic routing, and circuit breakers
• Instrument agentic systems with distributed tracing, SLOs, and cost budgets
• Implement guardrails, audit trails, and human-in-the-loop approval gates for regulated environments

Course content

01. Advanced Multi-Agent Orchestration

• Swarm patterns & emergent coordination
• Critic agents & adversarial review patterns
• Dynamic routing & capability-based dispatch
• Agent specialization & role contracts
• Control plane design for large agent networks
• Cross-agent shared state protocols
• Failure cascades & circuit breakers in agent networks
• Scenario: Debug a distributed agent pipeline silently dropping tasks

02. Memory & Knowledge Architecture

• Memory taxonomy: working, episodic, semantic, procedural
• RAG pipeline design, chunking strategies & evaluation
• Vector store selection & embedding strategies
• Semantic caching & deduplication at scale
• Episodic memory & session persistence across restarts
• Retrieval ranking, re-ranking & hybrid search
• Memory staleness, invalidation & refresh cycles
• Scenario: Fix a RAG agent hallucinating on stale retrieval

03. Agent Evaluation & Quality Engineering

• Evaluation taxonomy: output-level vs. trajectory-level
• Building ground truth datasets for agentic tasks
• LLM-as-judge: patterns, calibration, and bias
• Regression testing across agent versions
• Red-teaming: adversarial inputs & agentic attack surfaces
• Confidence calibration & uncertainty quantification
• A/B testing agents in production safely
• Scenario: Design an eval harness for a customer-service agent

04. Production Reliability & Observability

• Distributed tracing for agent chains
• SLOs and error budgets for agentic systems
• Structured logging & canonical event schemas
• Alerting patterns & anomaly detection
• Token budget enforcement & cost guardrails
• Incident response playbooks for autonomous agents
• Canary deployments & rollback for agent systems
• Scenario: Diagnose a silent cost blowout in a production agent

05. Safety, Alignment & Compliance at Scale

• Constitutional AI and alignment techniques
• Prompt injection defenses
• Data privacy: PII handling and data residency
• Compliance frameworks: HIPAA, SOC 2, EU AI Act
• Bias auditing and fairness measurement
• Human oversight patterns: escalation, veto, and explainability
• Responsible deployment: staged rollout, kill switches, and governance
• Scenario: Build a compliance-ready agent deployment checklist

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