This conversation is a must-listen for engineering leaders, CTOs, and operations professionals who are curious about how to deploy AI in complex, physical systems.
It covers everything from telemetry data to orchestration engines, the role of human validation, AI-assisted SDLC, and team culture in AI adoption. If you're building or managing AI-first systems that interact with the real world, this episode offers hands-on insight and strategic direction.
🔑 5 Major Points
1. AI’s Role in Logistics and Intra-Operations
- AI enables real-time orchestration between warehouses, vehicles, and delivery staff.
- Reduces human coordination and streamlines operations with predictive systems.
- Enhances customer experience by providing accurate delivery insights.
2. Telemetry as the Foundation for AI Decisions
- Combines data from GPS, warehouse cameras, and IoT-enabled locks.
- Acts as the “eyes and ears” of the system, feeding live context to AI agents.
- Helps in tracking, routing, and setting correct customer expectations.
3. Engineering Culture and AI Adoption
- Engineers are encouraged to treat AI as an assistant, not a competitor.
- Tools like Cursor, Claude, and v0.dev are used with flexibility.
- Sprint retros help decide the most effective tools through team feedback.
4. Testing and Validation of Probabilistic AI Systems
- Early deployments involve human cross-validation of AI decisions.
- Ground teams train models through lived operational feedback.
- AI models are penalized/rewarded to improve through reinforcement learning.
5. Mindset and Leadership for AI Transformation
- Focus on understanding problems deeply before building solutions.
- AI should be used to explore nuances and dimensions of real-world challenges.
- Leaders must give vision, not tasks—empowering teams to explore and learn.
💬 5 Memorable Quotes
- “If I got even a one rupee for every time I heard ‘Where is my shipment?’, I’d be enjoying life on a beach.”
- “Think of telemetry as the eyes and ears of the ecosystem.”
- “You can’t win against AI. Use it as your assistant.”
- “Backend engineers leaned toward Cursor, frontend folks preferred V0.dev. It happened naturally.”
- “I'm looking for a time when orchestration will be so automated, two vehicles compete with each other for faster delivery.”
What you'll listen
- 00:00Introduction
- 01:37SMILE & Sarang's role in it
- 02:18Applying AI to logistics
- 04:44Applying AI to customer queries
- 06:33Telemetries for logistics
- 07:26AI models in logistics
- 11:33Validating AI model output
- 16:13Impact of AI on SDLC
- 18:47SDLC AI Tools
- 19:41Choosing between multiple AI Tools
- 22:27Looking forward
- 23:35Resources that helped Sarang in AI journery
- 24:47Writing on LinkedIn
- 25:39If you are starting today on AI journey
- 28:06Manager's work in AI era
- 29:52Kindest thing anyone has done for you
- 30:18Best leadership quality
- 30:50What is the definition of living a good life
Connect with meHave a life of WINS.