Sidu Ponnappa

If you take AI transformation advice at face value, the work looks done once the tools are bought — and the business still moves like it did a year ago. The Playground is the pattern that turns the tools into a business that moves differently.

Going AI Native means one thing: your customers get superhuman speed and superhuman quality no competitor can humanly match. A Head of AI and a Centre of Excellence won't get you there — Parnas, Conway, and Jevons explain why.

The "SaaS is dead" debate is fixated on pricing. The real shift is deeper: AI is converting one class of software after another from a scarce asset into cheap, replicable inventory — and below that line, there is no product.

The AI Effort Paradox: Why trying harder costs more

AI is transforming IT services' economic model by decoupling revenue from headcount

Salesforce is a powerful tool, but traditional implementations often lead to data chaos within months. An AI-first Salesforce implementation changes that.

Agents that can do work asynchronously will be crucial to make GenAI scalable and viable for enterprise workloads.

realfast Vayu is an orbital shift in how you deliver Salesforce.

A problem evaluation framework we've developed over the past year for both GenAI founders and investors.

Faster implementations are the Hero USP for AI-based tooling, not cost savings.

You want your agents to be just smart enough to do the task consistently and reliably, and not any smarter than that.

It actually helps to be less ambitious when starting out with AI transformation and take small, meaningful steps towards increasing velocity and throughput.

Foundational AI and Applied AI operate on entirely different planes. So, the approach you take to build an applied AI company will also be very different.

We're talking 12-16x faster test creation, with 95%+ code coverage.

For typical enterprise workloads, LLMs are raw material. You will need software engineering to turn them into a scalable resource.

Evaluating an AI tool's performance in real-world workflows is inherently more complex than benchmarking the models themselves on established datasets.

If you think slapping together a basic interface and calling an API is all it takes, then you're clueless about what's really involved.

The Industrial Revolution for IT Services is here, and we are leading the charge.