Advanced Agentic AI + AEP: 30-Hour Lab Series
Thirty one-hour labs on Agentic AI with Adobe Experience Platform: journey agents, MCP pipelines, decisioning, CJA attribution, governance and a CDP capstone.
The Advanced Agentic AI + AEP lab series is 30 one-hour hands-on sessions for people who already know the basics of Adobe Experience Platform. Each hour pairs a use case with a task and a deliverable, covering agents, MCP pipelines, multi-agent flows, AI decisioning, personalisation, Data Distiller, predictive analytics, governance, security and a BFSI and retail capstone.
Program at a glance
- 30 one-hour hands-on labs
- Four mini projects and a capstone
- A deliverable per lab
- Governance, security and cost modules
- Final assessment with interview and portfolio review
No payment is taken on this site. Outcomes depend on participation and practice; no job, salary or certification outcome is guaranteed.
What you'll learn
- Design agent workflows for journey optimisation and troubleshooting
- Build MCP pipelines and multi-agent flows
- Create decisioning and personalisation flows
- Apply Data Distiller and dynamic datastreams
- Build attribution and predictive analytics
- Apply AI governance, security, scaling and cost control
Course content
Hours 1-6: agents and mini project 1 · 3 topics
- Agentic AI in Adobe
- Journey, governance and support agents
- Marketing copilot
Hours 7-12: MCP, decisioning, personalisation · 3 topics
- MCP integration and multi-agent systems
- AI decisioning and next best offer
- Experimentation and mini project 2
Hours 13-18: data and collection · 3 topics
- Data Distiller and datastreams
- Identity stitching at scale
- AI data layer, sendEvent optimisation, mini project 3
Hours 19-24: analytics · 3 topics
- CJA attribution and pathing
- Predictive analytics and segments
- Lifecycle intelligence, mini project 4, validation
Hours 25-30: governance and capstone · 3 topics
- Governance and security
- Performance and cost optimisation
- Capstone and final assessment
Who this program is for
AEP practitioners
People who have used AEP and want to add AI-assisted delivery.
Architects
Architects designing governed AI on customer data.
Consultants
Delivery consultants preparing for AI-heavy Adobe engagements.
Hour-by-hour plan
| Hour | Module | Advanced topic | Use case | Hands-on task | Deliverable |
|---|---|---|---|---|---|
| 1 | Agentic AI in Adobe | Experience Platform agents and orchestrator | Automate journey optimisation | Explore AI agents | Agent workflow document |
| 2 | Journey agent | AI-driven journey orchestration | Cart abandonment automation | Create a journey using AI | Journey flow |
| 3 | Brand governance agent | Automated compliance and governance | Consent and GDPR automation | Define governance rules | Governance model |
| 4 | Product support agent | AI troubleshooting automation | Debug AEP and AJO issues | Resolve an issue using AI | Debug report |
| 5 | Marketing copilot | AI insights via a copilot | Marketing decision automation | Query insights | Insights report |
| 6 | Mini project 1 | AI agent setup | End-to-end agent workflow | Build an agent flow | Working agent system |
| 7 | MCP deep integration | Agent orchestration via MCP | Multi-agent CDP workflows | Create an MCP pipeline | MCP system |
| 8 | Multi-agent systems | Agent collaboration | Journey and analytics automation | Build a multi-agent flow | Agent system |
| 9 | AI decisioning | Real-time decision engine | Next best offer engine | Build a decision model | Decision engine |
| 10 | AI personalisation | Hyper-personalisation | Dynamic content targeting | Create a personalisation flow | Personalised journey |
| 11 | Experimentation agent | AI-driven experimentation | A/B testing automation | Run an experiment | Experiment result |
| 12 | Mini project 2 | AI personalisation system | End-to-end personalisation | Build a personalisation engine | Working system |
| 13 | Data Distiller | Advanced data transformation | Data enrichment pipelines | Transform a dataset | Enriched dataset |
| 14 | Dynamic datastreams | Multi-destination routing | Analytics, Target and AEP routing | Configure routing | Routing configuration |
| 15 | Real-Time CDP advanced | Identity stitching at scale | Unified customer view | Build an identity graph | Unified profile |
| 16 | AI data layer | Auto-generate a data layer | Schema automation | Generate JSON | Data layer JSON |
| 17 | sendEvent optimisation | Payload optimisation | Performance tuning | Optimise a payload | Optimised payload |
| 18 | Mini project 3 | AI data pipeline | End-to-end pipeline | Build a pipeline | Working pipeline |
| 19 | CJA advanced analytics | Attribution and pathing | Multi-touch attribution | Build an attribution model | Attribution report |
| 20 | Predictive analytics | ML models on AEP data | Churn prediction | Train a model | Prediction output |
| 21 | AI segmentation | Real-time predictive segments | High-value user prediction | Create a segment | Segment output |
| 22 | Customer journey intelligence | Full lifecycle tracking | Banking lifecycle | Map the lifecycle | Journey map |
| 23 | Mini project 4 | AI analytics system | End-to-end analytics | Build an analytics system | Analytics dashboard |
| 24 | Validation | Debug analytics | Fix attribution issues | Validate reports | Validation document |
| 25 | AI governance | Data privacy and compliance | GDPR consent automation | Implement governance | Governance document |
| 26 | AI security | Secure AI workflows | Access control | Define policies | Security model |
| 27 | Performance scaling | Optimise large systems | High-traffic system | Optimise a system | Performance report |
| 28 | Cost optimisation | Token and infrastructure optimisation | Reduce AI cost | Optimise cost | Cost report |
| 29 | Capstone project | End-to-end AI CDP system | BFSI and retail implementation | Build the full system | Working architecture |
| 30 | Final assessment | Interview and portfolio | Scenario solving | Solve scenarios | Assessment result |
Fees and enquiry
Paid program fees are confirmed in writing before payment. The flagship Career Accelerator is ₹60,000 and, as stated by the founder, includes Adobe sandbox access and mentoring. Pricing for this track is shared on request.
Tool and product names (including Adobe AI features and MCP-based integrations) change quickly. We verify them against current Adobe documentation before each cohort, and training does not guarantee jobs, salary or certification.
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Frequently asked questions
What should I know first?
AEP basics: XDM, datasets, profiles and audiences. If you are new, start with the weekend batch or the Career Accelerator.
Are the AI tools specified?
Labs name the tools used per hour, such as Claude-based assistants alongside AEP and AJO. Tool availability and licences depend on your own accounts and are verified before the cohort.
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Request details: Advanced Agentic AI + AEP
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