IVQ 851-900
Section 86: Agent Memory & Context Management (10 Questions)
How do you differentiate between short-term and long-term memory in LLM agents?
How would you build episodic memory for a multi-session assistant?
What is vector-based memory injection, and how does it affect generation quality?
How do you avoid memory pollution when storing prior interactions?
How can memory be personalized across users while using shared infrastructure?
How do you implement memory expiration or pruning in LLM agents?
What are best practices for context window budgeting in multi-task agents?
How do you store task-specific memories that evolve with each conversation?
How would you integrate user, session, and tool memories in a unified architecture?
How do you evaluate memory fidelity and recency bias in agent recall?
Section 87: Temporal Awareness & Reasoning (10 Questions)
How can LLMs be made aware of current dates or time-based context?
What techniques help LLMs reason over sequences or timelines?
How do you represent temporal facts in embeddings for better retrieval?
How would you prompt an agent to schedule tasks with future-state dependencies?
What are common errors LLMs make with calendar math and how can you fix them?
How do you manage day/week/month context in recurring GenAI agents?
How do you teach an agent to ask for clarification when date ranges are ambiguous?
How would you benchmark an LLM’s understanding of past/future event chains?
How do you simulate time progression in memory-augmented workflows?
How do you connect time-aware prompts with external calendar or log systems?
Section 88: Collaborative Agents & Teamwork (10 Questions)
How do you structure communication between multiple LLM agents working on one task?
What is an agent role taxonomy, and how does it support team-based reasoning?
How do you coordinate a drafting agent, reviewing agent, and formatting agent in a content workflow?
How can agents challenge or critique each other to improve overall performance?
What are safe arbitration strategies when agents disagree?
How do you avoid knowledge overlap or redundancy in agent teams?
How do agents use shared memory to maintain context across roles?
What are protocols for agent handoff and task completion verification?
How would you monitor and log multi-agent decisions for audit and explainability?
How can human reviewers participate in multi-agent decision loops?
Section 89: Automated Content Generation & Validation (10 Questions)
How do you build GenAI workflows that generate, critique, and finalize documents?
How do you validate generated content against tone, length, or brand guidelines?
What tools help you automatically test LLM output for grammar, style, or logic?
How do you insert structured metadata into unstructured generated output?
How do you maintain factual consistency across long-form generated articles?
How do you incorporate human feedback to train GenAI content validators?
How would you design a pipeline to generate newsletters from company activity logs?
How do you evaluate content diversity vs. repetitiveness in GenAI systems?
What is your retry or fallback strategy for low-confidence content outputs?
How do you integrate SEO guidelines into LLM content generation prompts?
Section 90: Multi-Modal & Cross-Input Reasoning (10 Questions)
How do LLMs reason over image + text inputs in a document layout task?
How can you use CLIP or BLIP for grounding LLMs in visual context?
How would you handle table + paragraph reasoning using GenAI?
What’s the architecture for combining OCR → captioning → Q&A?
How do you chunk and embed multi-modal documents (e.g., PDFs with charts)?
How do you evaluate whether multi-modal reasoning was performed correctly?
How do you fine-tune multi-modal agents for domain-specific visual tasks (e.g., radiology, maps)?
How would you build a GenAI pipeline that processes video transcripts with speaker turns?
How can agents refer back to visual or spatial memory during a dialogue?
What are safe UX patterns for presenting multi-modal GenAI outputs?
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