Intermediate~3h
ReAct, Chain-of-Thought & Planning Architectures in Agentic AI EngineeringInterview Readiness Check
ReAct (Reasoning + Acting) from the original paper to production implementation. Explicit vs implicit chain-of-thought. Step-back prompting. The Plan-and-Execute pattern. Tree of Thoughts for complex multi-path problems. Reflexion for iterative self-improvement. LATS (Language Agent Tree Search). How each pattern performs, fails, and when to choose one over another..
ReActchain-of-thoughtCoTPlan-and-ExecuteTree of ThoughtsReflexionLATSplanningreasoningself-improvement
Learning path
What Agents Actually Are→ReAct, Chain-of-Thought & Planning Architectures ← you are here→Task Decomposition & Hierarchical Planning
Try a sample question
What does 'CoT' stand for in the context of LLM reasoning, and what does it instruct the model to do?
A.Context of Thought — it expands the model's active context window so it can process longer reasoning chains without truncation
B.Chain-of-Tools — it defines the ordered sequence of tools the agent must call to complete a multi-step task
C.Cost of Tokens — it measures and reports the token budget consumed per individual reasoning step in the agent loop
D.Chain-of-Thought — it prompts the model to produce intermediate reasoning steps before the final answer
Sign up free to take the full check and see the answer with an explanation.
What this module tests
- Conceptual understanding of react, chain-of-thought & planning architectures fundamentals
- Trade-offs and design decisions in real system scenarios
- ReAct and chain-of-thought — applied knowledge
- Interview-style reasoning and explanation quality
Free to start
Take the ReAct, Chain-of-Thought & Planning Architectures check →
10 questions · Dimension scoring · AI coach feedback · Shareable result
Test your knowledge — free →No credit card · Takes 10–15 min
Frequently asked questions
- What does the ReAct, Chain-of-Thought & Planning Architectures check test?
- The check covers react (reasoning + acting) from the original paper to production implementation. explicit vs implicit chain-of-thought. step-back prompting. the plan-and-execute pattern. tree of thoughts for complex multi-path problems. reflexion for iterative self-improvement. lats (language agent tree search). how each pattern performs, fails, and when to choose one over another.. Questions span beginner to advanced difficulty and test both conceptual understanding and practical trade-off reasoning.
- What keywords should I know for ReAct, Chain-of-Thought & Planning Architectures?
- Key concepts include: ReAct, chain-of-thought, CoT, Plan-and-Execute, Tree of Thoughts, Reflexion, LATS, planning, reasoning, self-improvement. These frequently appear in agentic ai engineering interviews at product and infrastructure companies.
- How many questions are in the check?
- Each check has 10 questions — a mix of MCQ and short-answer. You get scored by dimension (e.g., scalability, consistency) so you know exactly where to focus.
- How long does it take to study ReAct, Chain-of-Thought & Planning Architectures?
- Most engineers spend around 3 hours on this module. The check itself takes about 10–15 minutes. You can retake it up to 3 times per day.
- What prerequisite knowledge do I need before ReAct, Chain-of-Thought & Planning Architectures?
- ReAct, Chain-of-Thought & Planning Architectures builds on What Agents Actually Are. Complete those first for the best results.
- Is ReAct, chain-of-thought, CoT covered?
- Yes. The ReAct, Chain-of-Thought & Planning Architectures module covers ReAct, chain-of-thought, CoT among other key concepts. The check includes questions that reflect real agentic ai engineering interview patterns.