Notes From Chairing a Session at CSCE 2026

A morning of AI research, from rocket design to AI governance, and what stood out from the chair's seat.

The AI-Era PM: Becoming a Strategic Technology Leader

Upcoming: I'm speaking at a PMI San Francisco Bay Area session on how PMs can move beyond execution to become strategic technology leaders in the AI era. Friday, July 24, 5:30-6:30 PM PDT, via Zoom.

On CTO Sync: Winning Support to Pay Down Technical Debt

CTO Sync featured my approach to winning stakeholder support for technical debt paydown: weighing blast radius, exposing consequences to leadership, and reserving a fixed slice of every cycle for paydown.

CloudX 2026: How Do You Forecast Hardware at Billion-User Scale?

Invited speaker at CloudX 2026 (Santa Clara, Sept 1-3), co-located with API World + AI TechWorld. Speaking on how to forecast hardware capacity for AI infrastructure at billion-user scale.

The TPM Operating System Behind Large-Scale Program Execution

How a technical program manager actually runs a large program, from the first funding conversation to the hundredth status update.

On Mashable: Building AI Infrastructure at Billion-User Scale

Mashable profiled my work leading AI infrastructure at billion-user scale: lifting model deployment success from 60% to 99%, cutting scale-up time from three days to two hours, and a GPU efficiency redesign worth an estimated $20M in savings.

Kong API + AI Summit 2026: Operational Lessons from Running Large-Scale AI Inference

Invited speaker at the Kong API + AI Summit 2026 in Los Angeles (Sep 30 – Oct 1). A practitioner session on the operational realities of running large-scale AI inference: deployment coordination, GPU and infrastructure constraints, performance tuning, and reliability under rapid model iteration.

Leading Without Authority: The Operating System of a Technical Program Manager

Every technical program manager eventually runs into the same uncomfortable fact: you are accountable for outcomes you cannot command. The engineers do not report to you. The architects do not need your sign-off. The executive who set the deadline will not write a line of the code that meets

AI Infra Summit 2026: What It Takes to Run AI Infrastructure at Billion-User Scale

Upcoming: I'm speaking at AI Infra Summit 2026 (Santa Clara, Sept 15-17) on what it takes to run AI infrastructure at billion-user scale.

Session Chair, IEEE CONIT 2026

I'm serving as Session Chair at the Sixth IEEE International Conference on Intelligent Technologies (CONIT 2026) in Hubballi, India, on June 20, 2026.

IEEE MetroInd 2026: Characterizing GPU Capacity and Computational Cost in Production AI Inference

My paper on a replica-centric capacity-planning framework for GPU and Multi-Instance GPU (MIG) based AI inference platforms was accepted at IEEE MetroInd 4.0 & IoT 2026 in Rome, Italy.

Budapest Data + AI Forum 2026: How to Engineer Reliability at Scale

I spoke at the Budapest Data + AI Forum 2026 on why ML deployments fail in production and how to engineer reliability at scale. Session abstract, key takeaways, and links.

Highlights

How automation is changing managerial roles

I recently sat down with Business Standard for their Manager's Mantra series (BSmart). What started as a conversation about automation and managerial roles turned into a wide-ranging discussion: enterprise cloud strategy, the economics of AI infrastructure, how to build data platforms people actually use, modernizing legacy systems,

Highlights

IEEE CSNT 2026: Operationalizing Site Reliability in Large-Scale Distributed Systems

I presented our paper "Operationalizing Site Reliability in Large-Scale Distributed Systems: Shifting Ownership Left" at IEEE CSNT 2026 (Al-Khobar, Saudi Arabia): predictive models that forecast failures to keep large-scale distributed systems reliable.

Highlights

AI Infra TPM: Deploying Mission-Critical Models Faster Than Ever

OneIndia profiled my work on AI model deployment: cutting deploy times from days to hours, lifting success rates from roughly 60% to nearly 99%, and serving about 4x more requests per GPU.

Highlights

On Zee Business: Why AI Hallucinates, and How to Use It Responsibly

I joined a Zee Business India 360° panel (Feb 2026) on AI hallucinations: why models confidently make things up, how to verify their output, practical prompt techniques, and where AI regulation stands across the EU, US, and India.

System Design

Vector Databases: Storing Meaning for the Age of AI

Every database we've met so far stores facts: a user's name, an order's total, a sensor's reading, a word in a document. The newest member of the family stores something stranger and more powerful: meaning itself. Vector databases are the data system

System Design

Time-Series Databases: The Data That Only Moves Forward

There's a kind of data that has quietly exploded in volume over the last decade, and you generate it constantly without thinking. Every time a server reports its CPU usage, every time an app records how long a request took, every time a thermostat notes the temperature, every

System Design

Search Engines: Finding the Needle in the Haystack

Type a few words into a search box and, in a fraction of a second, you get back the most relevant results out of millions or billions of documents, ranked best-first, with your typos forgiven and suggestions appearing as you type. We're so used to this that

System Design

Analytical Systems: Warehouses, Hadoop, and the Lakehouse

Every database we've covered so far has one job: running an application. They store orders as they're placed, serve profiles as they're viewed, accept writes as they happen. This is the live, operational heartbeat of a product, and it's called OLTP, online

System Design

Graph Databases: When the Connections Are the Point

Every database family we've covered so far treats relationships as a secondary concern. Relational databases reconstruct them with joins at query time. Document databases mostly avoid them by nesting data. Key-value and wide-column stores barely acknowledge them. But for a whole class of important problems, the

System Design

Key-Value Stores and Caching: The Simplest, Fastest Idea in Data

After the elaborate machinery of relational, document, and wide-column databases, the key-value store is almost a relief. It is the simplest possible database, and that simplicity is exactly where its power comes from. There is no schema to design, no query language to learn, no joins to reason

System Design

Wide-Column Databases: Built for an Avalanche of Writes

Some data does not arrive politely. It pours. Think of every tap and swipe in a mobile app, every message in a chat platform, every reading from a fleet of sensors, every location ping from a fleet of vehicles, every line of a log from thousands of servers. This is

System Design

Document Databases: When Your Data Wants to Be Whole

The relational database we covered in the last deep-dive is brilliant at one thing above all: taking your data apart into tidy, non-repeating tables. That is its great strength. But it is also, for some kinds of work, its great inconvenience. A lot of the time, the thing