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AI Agent Evaluation and Testing
Context Simulation vs. Manual QA: When Each Works for AI Agents
Compare context simulation and manual QA for AI agents using scenario volume, failure stakes, coverage, and human judgment in production testing.
Contributing author
Karthik Pasupathy
Contributing Writer — AI Context & Agents
Karthik Pasupathy is a product marketer and the founder of Rampkit, with over a decade spent helping B2B SaaS and AI-infrastructure companies explain complex products to enterprise buyers and practitioners. He has led marketing for early-stage companies across FinTech, CCaaS, and mortgage technology. At Atlan, he writes on AI context, agentic systems, and RAG metadata.
/ Profile
About Karthik.
Karthik Pasupathy is a technical writer turned product marketer and founder of Rampkit, where he helps technical B2B SaaS and AI infrastructure companies explain complex products to the people they are built for. His work sits at the intersection of content, product understanding, and market education — turning dense technical ideas into clear narratives for enterprise buyers, practitioners, and technical decision-makers.
Over the last decade, Karthik has worked with SaaS companies across AI infrastructure, DevOps, APIs, FinTech, CCaaS, mortgage technology, and enterprise software. His writing focuses on helping teams communicate why their product matters, how it fits into a larger technical workflow, and what problems it solves for specific user personas.
His current work explores AI context, agentic systems, RAG metadata, and how enterprises can make AI outputs more relevant, grounded, and useful. He brings a content-first lens to technical topics without stripping away the nuance that makes them valuable.
Press, talks & code
Recent articles by Karthik Pasupathy.
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- 02AI Agent Skills
Custom vs Public Agent Skills: A Decision Framework
Use Atlan's framework to choose a public, adapted, or custom AI agent skill based on workflow fit, risk, ownership, licensing, and drift over time.
- 03Knowledge Graphs for AI Agents
Active vs. Static Knowledge Graph: What's the Difference?
Compare active and static knowledge graphs for AI agents. See why freshness architecture affects hallucination rates and how to evaluate mutability.
- 04AI Agent Architecture
ReAct vs. Plan-and-Execute: Two Agent Architectures
Compare ReAct and Plan-and-Execute across adaptability, token cost, latency, failure modes, and the enterprise context both require to work correctly.
- 05AI Agent Memory
How AI Agents Read and Write Memory: The Mechanics
How do AI agents read and write memory? Learn the mechanics behind short-term, long-term, episodic, and semantic memory, and why context matters.
- 06AI Agent Guardrails
Are Agent Skills Safe for Enterprise? Yes, With a Context Layer
Agent skills can be safe for enterprise use when governed well. Learn the real risks, the controls that work, and why every skill needs its…
- 07Agent Skills
What Is an Agent Skills Registry? Publishing, Discovery, Trust
Learn what an agent skills registry is, how it publishes and versions skills, and why a clean security scan never guarantees accurate business context.
- 08AI Agent Evaluation
How to Measure Task Success Rate in AI Agents
Learn how to measure task success rate in AI agents by defining success criteria, building pass/fail rubrics, and grading against real business outcomes.
- 09AI Agent Evaluation
How to Measure Agent Trajectory: The Path, Not the Answer
Learn how to measure agent trajectory by scoring tool correctness, step efficiency, plan adherence, and safety against real business context.
- 10AI Agent Context Layer
Claude Code and Codex in the Enterprise: The Context Gap
Claude Code and Codex have enterprise controls. But a safe agent is not the same as an agent that knows your business. Learn what context…
- 11AI Agents
Types of AI Agents: Reflex, Multi-Agent, ReAct and Autonomous
Learn the types of AI agents, from reflex to multi-agent and autonomous, and why architecture alone does not guarantee the agent will be right.
- 12AI Agent Context Management
Agent Context Management: The Control Plane for AI Agents
Agent context management controls what AI agents retrieve, use, cite, revoke, and audit through identity checks, entitlement rules, and audit trails.
Transparency
Editorial relationship
Freelance contributor agreement
Karthik contributes to Atlan as an independent consultant under a freelance content agreement. He reviews and approves every article published under his byline before publication. Atlan does not pay for placement of any external coverage.
Reach Karthik