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Context Engineering and Memory for AI Agents: Beyond Prompting

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An advanced program for AI/ML engineers and software engineers building agents and LLM applications who want to move beyond prompting toward the systematic engineering of context and memory. You learn to treat the context window as a finite resource that must be budgeted and kept clean, to decompose the anatomy of context (system prompt, instructions, examples, conversational history, tool results, retrieved data) and to design memory layers for agents: working/short-term, semantic, episodic and procedural. Covers memory managers and persistence (extraction, consolidation, LangMem-style memory store patterns), retrieval strategies for context (vector vs graph vs relational and the hybrid approach), compaction and window management (summarization, pruning, sliding window, context offloading), context engineering for multi-step agents and multi-agent systems, plus reliability evaluation, cost and token economics, prompt caching and optimization. Everything anchored in official Anthropic, OpenAI and LangChain (LangMem and LangGraph) documentation and the DeepLearning.AI course, with 2026 models (Claude Opus 4.7/4.8, GPT-5.6 Sol, Gemini 3.1 Pro) and a capstone project: an end-to-end agent with persistent memory, evaluated for reliability. The technical content is informational and versions the APIs and models, which may change.

10 modules
25 lessons
~24h duration
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What you will learn

Practical skills you gain by completing this course

Why Context Engineering: Beyond Prompting
The Anatomy of Context: The Components of the Inference Window
Memory Types for AI Agents
Memory Managers and Persistence: Extraction, Consolidation, Store
Retrieval Strategies for Context: Vector, Graph, Relational, Hybrid
Compaction and Context Window Management
Context Engineering for Multi-Step and Multi-Agent Systems
Evaluating and Debugging Context and Memory
Cost, Latency, Optimization and the Capstone Project
Appendix: Official Resources, 2026 Updates and Learning Paths

Who it is for

Developers Software engineers Solution architects CTOs / Tech Leads Data Scientists ML Engineers DevOps Engineers

Recommended level

Advanced

Assumes hands-on experience with AI and complex scenarios.

Updates

Regular

Last update: Aug 8, 2026. Content kept up to date.

Category

IT & Engineering

A technical course for IT professionals — available with individual course access or the IT Pro / All Access bundle.

Advanced level

Hands-on experience required

Assumes practical experience with AI. Covers complex scenarios and advanced strategies.

Always up to date

Last update: Aug 8, 2026

The course is updated regularly with the latest information, tools and practices from the industry.

Practical and applied

25 lessons with real examples

Each lesson includes practical scenarios, actionable checklists and quizzes to check your understanding.

Certificate of Completion

You leave with proof anyone can check

for the course Context Engineering and Memory for AI Agents: Beyond Prompting

A private attestation with a unique number and a QR code. A recruiter confirms it is authentic in a second, on the public verification page — no account, no cost.

What your certificate states for this course

  • Why Context Engineering: Beyond Prompting
  • The Anatomy of Context: The Components of the Inference Window
  • Memory Types for AI Agents
  • Memory Managers and Persistence: Extraction, Consolidation, Store
  • Retrieval Strategies for Context: Vector, Graph, Relational, Hybrid
  • Compaction and Context Window Management
Verify a certificate Certification policy →

A private attestation of course completion. It is NOT a diploma or a state-recognised qualification under Romanian Laws 198/2023, 199/2023 or Government Ordinance 129/2000; employers may take it into account at their own discretion. Certification policy.

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Public verification page, QR code and cryptographic fingerprint — no account and no cost for the person checking.

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Transparent

It shows exactly what it attests: the course, the modules covered, the assessment score and the completion date.

Curriculum

10 modules, 25 lessons — structured to learn step by step.

10 modules
25 lessons
~24h of content
Interactive quizzes
Free preview available The Limits of Prompting and Context as a New Discipline in 2026
Read the preview
1 Free preview lesson The Limits of Prompting and Context as a New Discipline in 2026
Read the preview
2 The Context Window as a Finite Resource: Context Rot, Attention, and Budgeting
54 min
3 What "Context" Means in 2026: From Static Prompt to Dynamic Agent State
50 min
1 System Prompt and Instructions: The Stable Layer of the Context
52 min
2 Examples, Conversation History, and Messages: The Accumulated Context
52 min
3 Tool Results and Retrieved Data: Dynamic Context at Runtime
54 min
1 Working/Short-Term Memory vs Long-Term: The Taxonomy of Agent Memory
52 min
2 Semantic Memory: Facts, Profiles, and Persistent Knowledge
52 min
3 Episodic and Procedural Memory: Experiences and Learned Behavior
52 min
1 Memory Stores and Persistence: Where and How Memory Lives
54 min
2 Extraction: How to Turn Conversations into Durable Memories
52 min
3 Consolidation: Deduplication, Updating, and Resolving Memory Conflicts
52 min
1 Retrieval for Memory: What You Bring Into Context, and When
52 min
2 Vector vs Graph vs Relational: Three Memory Models and Their Trade-offs
54 min
3 The Hybrid Approach: Combining Strategies for Robust Memory
52 min
1 Summarization and Pruning: Compressing History Without Losing Signal
52 min
2 Sliding Window, Context Offloading, and External Notes
54 min
1 Multi-Step Agents: Context on Long-Horizon Tasks
54 min
2 Multi-Agent Systems: Context Isolation, Sub-Agents, and Handoff
54 min
1 How to Measure Whether Memory and Context Improve Reliability
52 min
2 Context Debugging: Observability, Traces, and Failure Modes
52 min
1 Token Economics of Context: Cost, Latency, and Prompt Caching
54 min
2 Optimization Strategies: Token Budgeting and Trade-offs in Production
52 min
3 Capstone: An End-to-End Agent with Persistent Memory, Evaluated for Reliability
56 min
1 Official Resources, 2026 Updates, and Learning Paths
34 min
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