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.
