Category: Thought Leadership

Introduction If you already work with an AI coding agent, you know how much they can do. Tools like Kiro, Claude Code, and Cursor read repositories, reason over code, and drive multi-step tasks from an IDE or terminal. They’re excellent general-purpose AI coding agents, built to help with everyday software development tasks. But planning and […]

Independent Software Vendors (ISVs) with established SaaS products face a pivotal modernization decision. While enterprise customers demand intelligent automation through AI agents, they still require complete control over their data. For ISVs already serving regulated industries, the challenge isn’t building a new product, but it’s evolving existing SaaS architecture to incorporate autonomous AI agents while […]

Pratikkumar Chunawala, Principal Consultant, Professional Services, Amazon Web Services (AWS) Introduction This post presents a diagnostic framework for sustaining migration velocity, covering the velocity curve model, two structural forces that cause deceleration, and three leading indicators to detect the pattern early. Migration velocity stalls between waves 20 and 35 in most large-scale programs, not because […]

When AI initiatives stall, the instinct is to look at the model, the data, or the team. But more often, the constraint is underneath all of those — in the infrastructure itself. And running in the cloud doesn’t automatically remove that constraint. If the architecture was designed around pre-AI assumptions, it carries the same limitations […]

Most enterprise engineering organizations have deployed AI tooling broadly across teams. The per-team productivity gains are real. But end-to-end improvement hasn’t followed. Backlogs aren’t shrinking. Cycle times haven’t compressed. Tech debt is still growing. The tools aren’t broken. The problem is structural: each team accelerated independently, and the spaces between them are now the entire […]

Every domain in a large-scale migration has tools. The network still has people: a handful of them, overbooked, carrying decades of accumulated decisions in their heads. That has just changed. It starts with the network When approaching a large-scale migration to the cloud, nothing moves until the network is ready. Not the database. Not the application. Not […]

A month ago, I shared our learnings from AWS Transform’s first year—4.5 billion lines of code processed, 1.6 million hours saved for customers. We’ve continued to scale rapidly: now at 7 billion lines of code and an estimated 2 million hours saved. But it’s not just the numbers. I’m even more excited to share several […]

Introduction Lift-and-shift has a reputation problem. Ask any enterprise architect and you’ll get a wince. “We just moved our problems to the cloud.” That criticism has a grain of truth – but only when migration is treated as the end goal. The real question is whether it’s the right first step. Often, it is. Here’s […]

Traditional VMware migrations have long suffered from fragmentation and inflexibility. Enterprises had to cobble together disconnected tools for discovery, planning, network configuration, and rehosting, each requiring specialized expertise and lengthy manually orchestrated handoffs. These rigid, rules-based tools can’t adapt to each customer’s unique environment, resulting in compounding costs, expensive customizations, and timelines that stretch into […]

A year ago, we launched AWS Transform with one mission: modernize the world’s infrastructure and applications. 12 months in, here’s what 4.5+ billion lines of code processed, hundreds of thousands of servers migrated, and saving customers 1.6+ million hours taught us about migration, modernization, and why this work cannot wait. Why this matters more than […]