This story was originally published on HackerNoon at:
https://hackernoon.com/beyond-the-hype-pranav-pawar-on-how-to-build-reliable-ai-in-production.
How engineer Pranav Pawar builds reliable, scalable AI systems for real-world production—from healthcare automation to marketing agents at Kalos.
Check more stories related to machine-learning at:
https://hackernoon.com/c/machine-learning.
You can also check exclusive content about
#ai-infrastructure,
#ml-models,
#reliable-ai-systems,
#ai-in-production-engineering,
#multi-agent-ai-orchestration,
#healthcare-ai-automation,
#b2b-marketing-ai-agents,
#good-company, and more.
This story was written by:
@jonstojanjournalist. Learn more about this writer by checking
@jonstojanjournalist's about page,
and for more stories, please visit
hackernoon.com.
This piece explores how engineer Pranav Pawar builds AI systems that survive real-world complexity. From deal-sourcing at Bain to healthcare automation and now orchestrating multi-agent marketing systems at Kalos, Pawar focuses on reliability, verification, and long-term scalability. His work shows how AI becomes useful only when built to deliver consistently in production.