Talk to Udayan about
- Voice AI inference scaling
- AI ads masterclass
- Women‑focused AI GTM workflows
How Udayan thinks
Listen to market signals
Believes the market loudly indicates its needs, yet many ignore it.
For you: You should pay close attention to what the market is demanding.
First‑principles evaluation
Advocates layering microbenchmarks and observability to iteratively optimize AI system metrics.
For you: You can improve AI reliability by adding granular evaluation layers.
Balance speed, quality, cost
Frames voice AI projects around a single latency goal while constraining cost per minute and preserving quality.
For you: You should aim for sub‑second response while keeping cost low and quality high.
Ask this first
- How do you achieve sub‑second latency for voice AI on a single GPU?
- What key metrics do you focus on when teaching AI ads in your masterclass?
- Can you share insights on building AI‑led GTM workflows for women leaders?
Udayan's brain
Recently updated
In my September 2026 X posts I outlined how to scale voice‑based LLM inference on a single GPU for many concurrent callers.
In early October 2026 I posted a series of public X updates covering product development metrics, fundraising news, event expertise…
In September 2026 I shared a series of LinkedIn updates covering a quick reference on inference engineering, a partnership with Convex for…
In early October 2026 I posted a series of LinkedIn updates to promote GrowthX initiatives: an open‑access AI ads masterclass, a hiring…
I am a serial growth marketer and entrepreneur based in San Francisco CA, originally from Bengaluru, India. I co‑founded GrowthX, a global…