Top 10 Agentic AI Interview Questions with Answers
The Agentic AI Developer Program by AppliedTech Academy is a structured 24-hour training designed for developers, architects, and tech professionals who want to master the art of building intelligent AI agents. The program blends theory with practice, starting from the fundamentals of autonomous systems and gradually moving into advanced topics such as reasoning, planning, multi-agent workflows, and reflection-based learning.
What sets this course apart is its dual-track approach you’ll learn to design and deploy AI agents both through coding and with low-code/no-code tools. This means the program caters equally to engineers seeking deep technical knowledge and professionals who prefer faster, tool-driven development.
Learners also gain hands-on experience with industry-relevant platforms like LangGraph and AutoGen, while exploring real-world use cases in software development, enterprise automation, and domain-specific applications. The curriculum emphasizes practical design labs, interactive projects, and deployment best practices with a strong focus on scalability, security, and observability in cloud environments.
To support career growth, the program includes mentorship, internship certifications, and placement support, preparing participants not just to understand agentic AI, but to apply it effectively in their professional journeys.
1. What is Agentic AI, and how does it differ from traditional AI?
Answer: Agentic AI refers to autonomous systems capable of perceiving their environment, making decisions, and acting toward goals—learning and adapting over time. Unlike traditional AI that follows predefined rules, Agentic AI operates with autonomy, adaptability, and contextual learning.
2. What are the real-world applications of Agentic AI?
Answer:
- Software Development: Agents can write and review code.
- Customer Support: Chatbots that adapt to context and learn.
- Enterprise Workflows: Automate complex tasks across systems.
- Cybersecurity: Detect and respond to threats autonomously.
- Business Intelligence: Generate analytics and insights via natural language interaction
3. What are the key components of an Agentic AI system?
Answer:
- Perception Module: Gathers data from the environment.
- Reasoning Engine: Analyzes inputs and determines actions.
- Planning Module: Decomposes goals into actionable steps.
- Action Module: Executes decisions.
- Learning Module: Improves with feedback.
- Memory: Maintains context and knowledge over time.
4. Which tools and frameworks are commonly used for building Agentic AI agents?
Answer: Tools include:
- LangGraph and AutoGen from AppliedTech’s curriculum.
- Others in the landscape: LangChain, AutoGPT, BabyAGI, ReAct, AgentGPT.
5. What ethical and security considerations are important for Agentic AI systems?
Answer:
- Ethics: Transparency, accountability, fairness, and privacy are essential.
Security Risks: Vulnerabilities include data breaches, adversarial manipulation, and unauthorized actions. Mitigations involve robust authentication, regular security audits, and anomaly monitoring
6. How does memory enhance Agentic AI?
Answer: Memory enables:
- Temporary context awareness (short-term memory).
- Knowledge retention across interactions (long-term memory).
- Refined decision-making through reflection.
More personalized and consistent agent behavior.
7. What role does planning play in Agentic AI?
- Programming (Python, Java, C++)
- Strong AI and ML understanding
- System design and architecture
- Ethical awareness
- Communication and teamwork
AppliedTech’s program supports skill development across these domains via hands-on labs, mentorship, and real-world scenarios.
8. What skills are essential to work effectively in Agentic AI?
Answer:
- Programming (Python, Java, C++)
- Strong AI and ML understanding
- System design and architecture
- Ethical awareness
- Communication and teamwork
AppliedTech’s program supports skill development across these domains via hands-on labs, mentorship, and real-world scenarios.
9. What are some core design patterns in Agentic AI?
Answer: Key patterns include:
- Reflection: Self-evaluation for continuous improvement.
- Tool/Function Calling: Invoking APIs or services.
- Planning: Strategy formulation steps.
- Multi-Agent Collaboration: Agents working together toward complex tasks.
10. What is the future outlook of Agentic AI?
Answer:
Expect the rise of personalized AI agents, multi-agent systems, and deeper integration into enterprises. The focus will intensify on regulation, robustness, scalability, and ethical alignment. Agentic AI is poised to reshape industries through autonomous decision-making and adaptation.
Final Takeaway
AppliedTech Academy’s Agentic AI Developer Program offers a comprehensive, hands-on learning journey into the world of autonomous AI agents. Paired with these 10 strategic interview questions and answers, you’ll be well-positioned to master the technical, ethical, and practical dimensions of Agentic AI—and stand out in interviews or professional settings.