The Engineering Leadership Podcast

Scaling TensorFlow, Navigating Startup Pivots, ML Edge Infrastructure and AI Inference Strategy w/ Rajat Monga #256

21 snips
Apr 28, 2026
Rajat Monga, Corporate VP leading AI frameworks and edge inference at Microsoft and former TensorFlow co-founder, recounts scaling deep learning and founding Inference.io. He discusses refounding vs rebuilding systems, open source impact, startup pivots and hidden user incentives, and strategies for edge ML and large-scale inference infrastructure.
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ADVICE

Use Many Conversations To Find Product Market Fit

  • Talk to many real users; each conversation yields small nuggets that reshape the product iteratively.
  • Rajat ran design‑partner cycles during COVID, iterated UX, then tested willingness to pay across verticals like marketing and experimentation.
INSIGHT

Usefulness Loses To Established Workflows

  • Being useful isn't enough; adoption depends on how the product fits existing workflows and whether it truly replaces entrenched tools like dashboards.
  • Inference.io found customers used coping workflows and resisted switching unless the new tool aligned tightly with daily processes.
INSIGHT

Hidden Incentives Block Automation Adoption

  • Hidden incentives determine adoption: automation can threaten the power or growth of the teams that would deploy it, slowing buys.
  • Rajat notes data team leaders worry automation reduces their influence or headcount, creating resistance despite product merit.
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