Future Directions, Open Problems, and Course Wrap-Up
Looking Ahead
What Remains Hard
Open problems include long-horizon planning, robust memory, trustworthy tool use, better evaluation, stronger security against adversarial inputs, and balancing autonomy with control.
Likely Directions
Future systems will likely become more modular, more environment-aware, better at using feedback, and more integrated with human workflows. Progress will depend as much on system engineering as on model capability.
Big Takeaway
Agentic AI is a systems problem: success depends on the model, the tools, the memory, the controls, and the evaluation strategy working together.
Which statement best captures the main lesson of this course?
Agentic AI is broader than prompting; it is an integrated system design discipline.
Correct answer: Agentic AI is a systems approach combining reasoning, tools, memory, and control
Name one open problem in agentic AI.
Other valid answers include memory, evaluation, security, and human control.
Correct answer: Long-horizon planning.
Review Checklist
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1
Step 1: Identify the goal and success criteria.
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2
Step 2: Decide which parts require tools and memory.
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3
Step 3: Add verification and safety controls.
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4
Step 4: Test edge cases and failures.
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5
Step 5: Iterate on the workflow rather than assuming the first design is best.
What Makes Agentic AI Work
Model Capability
- Reasoning and language understanding
- Instruction following
- Summarization and decomposition
System Design
- Tools and memory
- Control loops and guardrails
- Evaluation and recovery
Why is agentic AI considered a systems problem?
Agents emerge from the interaction of models, tools, memory, and controls.
Correct answer: Because the outcome depends on multiple interacting components