Certified Agentic AI Developer (CAAD) Certification Program by Tonex
The Certified Agentic AI Developer (CAAD) program equips professionals to design, build, and operate autonomous AI agents that plan, act, and learn across complex workflows. You’ll master agent architectures, tool-use orchestration, multi-agent collaboration, and robust guardrails that align outcomes with business goals.
The curriculum blends systems thinking with practical implementation patterns so you can translate intents into reliable automations that scale. Security is integral: you will learn secure-by-design patterns for agents, enforce policy-aware actions, and harden toolchains against prompt injection and model compromise.
You’ll also map threats unique to agentic systems—such as delegated misuse and long-horizon drift—then implement mitigations, auditing, and continuous assurance to protect data, models, and decision integrity. By completion, you’ll be fluent in building measurable, governed autonomy that accelerates delivery while preserving trust and compliance.
Learning Objectives:
- Explain agent architectures and planning strategies
- Implement tool-use, memory, and reflection loops
- Orchestrate multi-agent workflows and negotiation
- Measure reliability with evaluation and telemetry
- Deploy governance, safety, and alignment guardrails
- Apply cybersecurity controls to agent design and operations
Audience:
- Software Developers
- ML/AI Engineers
- Solution Architects
- Product Managers
- Cybersecurity Professionals
- DevOps/SRE Engineers
Program Modules:
Module 1: Agent Foundations
- Agent types: reactive, deliberative, hybrid
- Planning: chain-of-thought, tree search, planners
- Memory models: short/long-term, vector stores
- Tool-use adapters and function calling
- Observation, action, and feedback loops
- Evaluation basics: task success and latency
Module 2: Tooling & Orchestration
- Action schemas and tool contracts
- Workflow engines and state management
- API mediation and rate governance
- Error handling, retries, and fallbacks
- Context windows and retrieval patterns
- Structured logging and tracing
Module 3: Multi-Agent Systems
- Roles, protocols, and handoffs
- Coordination patterns and blackboards
- Negotiation and conflict resolution
- Task decomposition and ownership
- Shared memory and knowledge graphs
- Performance tuning for swarms
Module 4: Guardrails & Safety
- Policy enforcement and allow/deny lists
- Prompt hardening and input sanitation
- Output filters and sensitive data controls
- Human-in-the-loop checkpoints
- Abuse prevention and escalation paths
- Red-teaming and safety tests
Module 5: Reliability & Ops
- SLIs/SLOs for agent workloads
- Offline evals and canary releases
- Drift, regression, and rollback plans
- Cost/latency optimization tactics
- Observability dashboards and alerts
- Incident response runbooks
Module 6: Security & Compliance
- Threat models for agent autonomy
- Identity, authZ, and least privilege
- Secrets, tokens, and key rotation
- Data residency and retention rules
- Audit trails and evidence collection
- Regulatory alignment and DPIA
Exam Domains:
- Agent Architectures and Planning
- Tool-Use and Workflow Orchestration
- Multi-Agent Coordination and Communication
- Governance, Safety, and Ethics
- Reliability Engineering and MLOps for Agents
- Security, Compliance, and Risk Management
Course Delivery:
The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, and project-based learning, facilitated by experts in the field of Certified Agentic AI Developer (CAAD). Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification:
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified Agentic AI Developer (CAAD).
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified Agentic AI Developer (CAAD) Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to build secure, reliable autonomous agents? Enroll in CAAD by Tonex and accelerate your impact.