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Learn deeply
Build a durable mental model, then transfer it into a working application.
Safe write foundations
Stage purpose: Establish the vocabulary and first working mental model.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Explain the core idea and use it in a small example.
Estimated time: 70 minutes
Lesson · Estimated time: 35 minutes
Outcomes
Explain why agent writes require stronger controls than reads Design an idempotent write tool that returns an auditable receipt
Prerequisites: No prerequisite topics
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Set Not started
Set Learning
Set Practised
Set Applied
Reset status
Recommended next: Secure Financial Write Operations — Transfer the safe-write contract to a higher-consequence financial example and compare the additional controls.
Lesson · Estimated time: 35 minutes
Outcomes
Calibrate write controls to irreversibility and blast radius Diagnose duplicate financial actions and missing tool receipts
Prerequisites: Safe Write Operations in Agentic Systems
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Set Not started
Set Learning
Set Practised
Set Applied
Reset status
Recommended next: Human in the Loop for Agentic Write Operations — Add a human decision boundary before the write so high-risk actions cannot execute autonomously.
Human control
Stage purpose: Connect the concepts into a repeatable problem-solving model.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Apply the model to a representative exercise without copying a recipe.
Estimated time: 35 minutes
Lesson · Estimated time: 35 minutes
Outcomes
Place a human gate at the correct write decision boundary Implement and diagnose checkpointed approve, edit, and deny flows
Prerequisites: Secure Financial Write Operations
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Set Not started
Set Learning
Set Practised
Set Applied
Reset status
Recommended next: Persistent Agents & Context Management — Follow suspended execution into persistent history, rewind, and recovery across long-running agent threads.
Recovery and defense
Stage purpose: Transfer the concepts into a realistic implementation task.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Produce a small artifact that proves the decision works.
Estimated time: 75 minutes
Lesson · Estimated time: 40 minutes
Outcomes
Use checkpoint history to rewind, branch, and resume an agent Choose a bounded context policy for persistent threads
Prerequisites: Human in the Loop for Agentic Write Operations
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Set Not started
Set Learning
Set Practised
Set Applied
Reset status
Recommended next: Securing Agentic AI Systems — Complete the production boundary with ingress and egress defenses against adversarial instructions and sensitive data leakage.
Lesson · Estimated time: 35 minutes
Outcomes
Distinguish direct and indirect prompt injection Design ingress and egress guardrails for PII and domain enforcement
Prerequisites: Persistent Agents & Context Management
Evidence: Practise the outcome in code and record what you learned.
Current status: Not started
Set Not started
Set Learning
Set Practised
Set Applied
Reset status
Recommended next: Complete this path by applying these outcomes in your own project.
Prepare for interviews
Prioritise high-frequency material, retrieve it quickly, and practise explaining it clearly.
Essential
Stage purpose: Secure the concepts that recur in most interviews.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Give a concise, accurate explanation with one concrete example.
Estimated time: 24 minutes
Lesson · Estimated time: 12 minutes
Outcomes
Explain why agent writes require stronger controls than reads Design an idempotent write tool that returns an auditable receipt
Prerequisites: No prerequisite topics
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Set Weak
Set Revising
Set Can explain
Set Interview ready
Reset status
Recommended next: Secure Financial Write Operations — Contrast reversible and financial writes, then justify how irreversibility changes the control surface.
Lesson · Estimated time: 12 minutes
Outcomes
Calibrate write controls to irreversibility and blast radius Diagnose duplicate financial actions and missing tool receipts
Prerequisites: Safe Write Operations in Agentic Systems
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Set Weak
Set Revising
Set Can explain
Set Interview ready
Reset status
Recommended next: Human in the Loop for Agentic Write Operations — Move from mechanical write safety to the placement and lifecycle of a human approval gate.
Frequently asked
Stage purpose: Rehearse implementation choices that invite common follow-up questions.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Walk through a realistic API decision and defend the trade-offs.
Estimated time: 12 minutes
Lesson · Estimated time: 12 minutes
Outcomes
Place a human gate at the correct write decision boundary Implement and diagnose checkpointed approve, edit, and deny flows
Prerequisites: Secure Financial Write Operations
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Set Weak
Set Revising
Set Can explain
Set Interview ready
Reset status
Recommended next: Persistent Agents & Context Management — Connect approval checkpoints to persistent state, forensic inspection, and time-travel debugging.
Advanced
Stage purpose: Prepare the details that distinguish a deeper answer.
Required background: Complete the linked prerequisites below or bring equivalent experience.
Expected outcome: Connect the concept to reliability, complexity, or production behavior.
Estimated time: 27 minutes
Lesson · Estimated time: 15 minutes
Outcomes
Use checkpoint history to rewind, branch, and resume an agent Choose a bounded context policy for persistent threads
Prerequisites: Human in the Loop for Agentic Write Operations
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Set Weak
Set Revising
Set Can explain
Set Interview ready
Reset status
Recommended next: Securing Agentic AI Systems — Finish with the security sandwich and explain why prompts alone cannot enforce a trust boundary.
Lesson · Estimated time: 12 minutes
Outcomes
Distinguish direct and indirect prompt injection Design ingress and egress guardrails for PII and domain enforcement
Prerequisites: Persistent Agents & Context Management
Evidence: Answer aloud, give a concrete example, and identify the relevant trade-off.
Current status: Weak
Set Weak
Set Revising
Set Can explain
Set Interview ready
Reset status
Recommended next: Complete this path by applying these outcomes in your own project.