Pratik Kulkarni

Pratik has spent a decade specializing in AWS infrastructure and cloud economics, delivering projects across startups and mid-size companies. He holds AWS Solutions Architect Professional and FinOps certifications.

Over the last few years, he has focused that expertise on AI systems and workloads deployed on cloud — and runs ThotStack, an AI product deployed on AWS. He started ThinkXL to help startups build a strong foundation on cloud for their AI workloads.

AgentCore vs Bedrock Agents vs Roll-Your-Own on Fargate

There are three realistic ways to run an AI agent on AWS, and they sit on a spectrum from "AWS does almost everything" to "you do almost everything." Bedrock Agents has AWS define and orchestrate the

Connect Claude Code to Live AWS Tools with the Agent Toolkit

AI coding agents are getting remarkably capable — but they have a blind spot. The models powering them were trained on data that's months or years old. When you ask your agent about Amazon S3 Tables,

Why Your AWS Bedrock Bill Makes No Sense (And How to Fix It)

When a startup says "our AWS bill is too high," the conversation almost always starts at the aggregate level — total monthly spend, a few large services, maybe a spike someone noticed. That's not wher

AWS Bedrock Cost Structure: What You're Actually Paying For

AWS Bedrock looks simple from the outside — call an API, get a response, pay per token. The reality is that a production Bedrock setup has several distinct cost layers, and they behave very differentl

AWS Bedrock vs SageMaker: How to Pick the Right One

If you're building an AI product on AWS, you'll hit this question early: Bedrock or SageMaker? The short answer is that they solve different problems, and most startups only need one. What Each Se

Stretch Your Claude Code Budget with Bedrock Prompt Caching

Anthropic recently tightened usage limits on Claude Code — and if you're doing serious development work, you feel it. Long refactoring sessions, codebase-wide architecture questions, iterative debuggi

Deploying Engineering Resource Management Knowledge Graph on AWS

Resource planning in engineering orgs is a multi-hop problem. The data is there — skills, project history, availability — it's just stored in flat tables that you need to join on demand. This post wal

RAG, GraphRAG, and Knowledge Graphs: What's Actually Different

LLMs are stateless. They don't know your documents, your internal data, or what changed last week. They're only as good as what you put in front of them. This gave rise to what's now called context en

Model Evals: How to Know If You Can Use a Cheaper Model

An eval, in the AI FinOps context, is a structured comparison: run a representative sample of real production inputs through your current model and a cheaper candidate, score both against a defined qu

What Is a Knowledge Graph?

A knowledge graph stores information as entities and the relationships between them — not rows and columns, but a web of connected facts. The Idea Is Simple Three building blocks:Nodes —

What Is AI FinOps?

AI FinOps is the practice of making AI workload costs visible, attributable, and optimizable — applied to the specific economics of model inference, where the unit of cost is the token, not the instan

What Is Amazon Bedrock AgentCore? (And When to Use It)

Amazon Bedrock AgentCore is a managed platform for deploying and operating AI agents you've already built — in any framework, with any model — without managing the runtime, memory, identity, or observ