Talks
A running list of conference talks, meetups, and community appearances — Kafka, vector search, Git, platform engineering, org change, whatever I was deep in at the time.
2026
When Semantic Search Breaks in Your RAG Systems: RAM Walls, Silent Failures, and the Architecture Decisions
The team shipped semantic search and it worked — then 100M vectors tripled the RAM bill overnight and filtered queries started silently returning zero results. The RAM math to run before any architecture decision, quantization that hits 32x compression at 95%+ recall, why filtered search is the #1 silent production failure, and when DiskANN, hybrid BM25+vector, or a specialized vector DB actually earns its place — trade-offs in plain English, with live demos.
Kafka & Time: The Hardest Dependency
Distributed systems are hard not because they span machines, but because they span time. A look at real production outages caused by partition keys, timestamp modes, and windowing contracts nobody consciously chose.
How Startups Transform Legacy Organisations from the Inside
How a small acqui-hired startup team, dropped into a 4,000+ person legacy organisation, actually changed the way it worked from the inside — years of setbacks, small wins, and the slow work of building trust rather than pushing best practices.
OWASP Top 10 for LLM Applications — live breaking and fixing
A live, hands-on session breaking and fixing LLM applications against the OWASP Top 10 for LLM risks — prompt injection, misinformation, excessive agency, supply chain, and more, each with a real demo and a real fix.
Vector Search & Storage in PostgreSQL with pgvector
Inside pgvector: how embeddings get stored (and TOASTed), why B-trees can't index vectors, and how IVFFlat and HNSW trade off build time, recall, and speed — plus quantization and the production gotchas that show up past the demo.
From Text to Vector: How High Dimensional Data Gets Stored, Searched & Retrieved
What actually happens after you call an embedding API — how text becomes vectors, how they're stored, and how semantic search finds the closest match. Starts with a brute-force scan across 50,000 vectors, then shows how IVFFlat and HNSW deliver 50–150x speedups, all in plain SQL you can run on your laptop.
Storing high-dimensional data at scale
What breaks when you push vector search to 100M+ rows on Postgres, how IVF/HNSW and quantization help, and why DiskANN plus hybrid BM25/vector search mattered in production.
2025
Git internals beyond add, commit, push
A practical deep dive into Git internals, for using Git with more confidence than the everyday porcelain commands give you.
Inside pgvector: how PostgreSQL stores and manages high-dimensional data
How pgvector represents and indexes high-dimensional embeddings inside PostgreSQL, and what that means for query performance at scale.
2024
Unlocking Efficiency and Collaboration: How Backstage Solves Key Developer Challenges
How Backstage, the open-source developer portal, tackles knowledge discovery, code ownership, system interfaces, dependency mapping, tech radar, and service creation.
Effective data consumption from Kafka
Configuring consumers for reliability and speed — fetch size, session timeouts, rebalancing, consumer lag, and the tradeoffs between throughput, latency, and resource use.
2023
Why, what, and how of practically working with Apache Kafka®
What problems Kafka actually solves, when to reach for it, and a long walk through common use cases — the knobs to turn and the tradeoffs that come with them.
2022
GitLab Bengaluru — first in-person meetup
Spoke at GitLab's first in-person Bengaluru meetup, alongside a full house on a rainy Saturday morning.