01
AI Agents
Agentic Software Factory: Specs, Agents, and Enterprise Context
Learn how an agentic software factory works, where humans approve, and why data products need business context alongside specifications and code.
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.
12 showing
- 02Google Cloud and the Context Layer
Google Agentic Data Cloud vs Context Layer: Who Owns the Meaning?
Compare Google Agentic Data Cloud with a neutral context layer: current feature status, business meaning, agent access, portability, and coexistence.
- 03Ontology
How Do AI Agents Use an Ontology? One Request Traced Step by Step
Trace how AI agents use an ontology at runtime to resolve terms, plan queries, apply policy context, coordinate handoffs, and explain each answer.
- 04AI Agents
Why a Neutral Ontology Layer Matters: Own Your Business Meaning
Learn why a neutral ontology layer keeps business meaning owned, portable, and consistent across every AI agent, model, and platform you run.
- 05AI Agents
Why AI Grounding Is Driving Ontology Demand for Enterprise Agents
Learn why AI grounding put ontologies back on the enterprise roadmap, what ungrounded agents get wrong, and why a first ontology draft is now cheaper…
- 06AI Agents
Ontology and Context Layer: How They Fit in Your AI Architecture
See where the ontology sits inside a context layer and how binding, approval, versioning, and delivery keep enterprise meaning current for AI.
- 07AI Agents
Ontology Vendor Evaluation: 30 Questions to Expose Manual Work
Use these 30 ontology vendor evaluation questions to expose manual modeling, schema-change work, review hours, and hidden services costs before signing.
- 08AI Agents
What Is an Operational Ontology? Objects, Links, and Actions
Learn how an operational ontology connects business objects to governed actions, how write-back works, and why AI agents need current context underneath it.
- 09AI Agents
MCP and the Semantic Layer: How AI Agents Get Governed Metrics
How MCP connects AI agents to a semantic layer's metric definitions, what a semantic layer's MCP server leaves out, and where a context layer fits.
- 10AI Readiness
How to Evaluate an AI Readiness Platform in 2026
Evaluate an AI readiness platform by testing context, certification, runtime delivery, traceability, and portability, not a one-time readiness score.
- 11AI Agents
RAG Pipeline vs. Context Layer: What Custom Retrieval Costs
See how RAG pipeline vs. context layer total cost of ownership breaks down across engineering, maintenance, permissions, evaluation, and scale for AI teams.
- 12AI Agents
ROI of AI Agent Governance: Governed vs. Ungoverned Access
Calculate the ROI of AI agent governance: faster deployment, less review and rework, reusable context, and lower failure exposure from governed access.
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