The Digital Executive Podcast: Ani Mishra on Scaling Logistics and Engineering Leadership at DoorDash | Ep 1087

Date: July 22, 2025
Guest: Ani Mishra, Head of New Verticals Logistics Engineering, DoorDash
Host: Brian (Coruzant Technologies)

Episode Overview

In this episode, Brian welcomes Ani Mishra, a Seattle-based software engineering leader heading DoorDash’s New Verticals Logistics Engineering. The discussion centers on building scalable logistics platforms across diverse sectors (grocery, retail, convenience, alcohol), establishing and leading high-performing engineering teams, translating lessons from startups to large tech environments, and the transformative impact of AI—particularly large language models (LLMs)—on logistics.

Key Discussion Points & Insights

1. Designing a Scalable, Multi-Vertical Logistics Platform

Timestamp: 01:19–03:00

• Start Small, Think Big: Ani emphasizes beginning with a deep understanding of the customer problem within one vertical, launching quickly, and iteratively expanding to broader use cases.
  • "My philosophy for building systems that can solve many customer problems in a scalable way is to start with one of the categories of customers... build a solution that solves the problem for one category... get it out as soon as possible." (Ani, 01:24)
• Evolution Through Iteration: After identifying a solution for a specific segment, focus shifts to adaptability for other verticals. Solutions gradually evolve from addressing one problem set to supporting many.
• Balance Speed and Scale: Initial optimization is for velocity; generalization for scale and robustness happens after initial product-market fit is demonstrated.

2. Building and Sustaining High-Performing Engineering Teams

Timestamp: 03:40–06:06

• Recruit Passionate Talent: Seek engineers deeply motivated to solve customer and large-scale system problems, in addition to technical expertise.
• Understand Individual Motivations: Team members may be driven by technical challenges, leadership, project management, or career progression. Ani prioritizes personal growth and matching scope to ambitions.
• Forward Planning: Constantly look ahead 1–2 years to set up the organization for future challenges and growth.
• Clarity and Autonomy: Clear focus, performance expectations, and autonomy enable engineers to excel.
  • "Giving people focus... and autonomy to make decisions of their own is really critical for people to do their best work." (Ani, 05:15)
• Reliability Shared Ownership: Responsibility for operational excellence and reliability (e.g., 'four nines', 'five nines' uptime) is distributed among all team members, not siloed or top-down.
  • "The product should also be reliable for the customers. That is kind of like how I think about building high performing teams in fast paced cultures operating at really large scale." (Ani, 05:50)

3. Lessons From Startups: Influence on Innovation and Leadership

Timestamp: 06:53–08:45

• Startup Grit and Versatility: Early roles as founding engineer and core team member at startups taught Ani to build products from scratch, scale systems, and wear many hats.
  • "I really embraced what it takes to... write the first line of code for building a product where we don't know where we are going and then going from there to a stage where the product is mature..." (Ani, 07:15)
• On-Call Experience as Learning: Proactively took on operational responsibilities to deeply understand complex systems (e.g., volunteering for a month-long on-call rotation at Phoenix).
• Leadership and Inclusive Cultures: Learned how to lead teams and foster inclusion—principles carried forward to DoorDash.
• Advice: Strongly encourages all technologists to experience early-stage startups for rapid learning and broader appreciation of product development.

4. The Future of Logistics Technology: Automation, AI, and LLMs

Timestamp: 09:25–12:53

• AI’s Growing Role: Technologies like computer vision, robotics, and LLMs are increasingly central. LLMs, in particular, unlock new capabilities across logistics actors.
  • "The emergence of large language models have made a lot more possible now because now everybody has access to world knowledge." (Ani, 09:42)
• Real-World Impact of LLMs:
  • In-Store Associates: LLMs help workers identify and locate obscure items and optimize shopping paths, reducing mistakes and speeding up order prep.
  • Customer Experience: LLMs discern customer intent—suggesting missing items (e.g., nudging a customer ordering for Thanksgiving dinner if a key ingredient seems missing).
  • Operational Safety: LLMs parse real-time text data (weather, traffic), automatically pausing and resuming delivery operations to enhance the safety of dashers.
  • Demand Prediction: AI assists logistics firms in capacity planning and predicting demand, crucial for efficient fulfillment.
• Broader Trends: AI and LLMs will further automate autonomous vehicles, drones, and last-mile delivery optimization. The next years will unlock even broader innovation and safer, faster, more reliable delivery services.
  • "We are just starting to see it all happen. And I think in future we'll discover a lot more use cases and a lot more applications..." (Ani, 12:25)

Notable Quotes & Memorable Moments

• "Start simple, start small, go to market fast, learn from there, iterate and then think about building the platform..."
  — Ani Mishra (02:40)

• "It's very important for me to continuously keep looking one year, two year out and thinking about the problems that I want to solve in the future and start to set the stage for solving these problems..."
  — Ani Mishra (04:44)

• "Even today I apply some of those learnings in enhancing my team and building a very inclusive culture here at DoorDash..."
  — Ani Mishra (08:28)

• "LLMs are also playing an important role in safety for workers who are transporting goods for last mile delivery... it can automatically shut down a market and get it back on really fast based on the real time conditions..."
  — Ani Mishra (11:32)

Key Timestamps

• 01:19: Ani’s approach to scalable platform design
• 03:40: Building and motivating high-performing teams
• 06:53: Startup lessons applied at DoorDash
• 09:25: The evolving future of logistics tech and AI/LLMs
• 11:32: LLMs in operational safety
• 12:25: AI for predictive demand and broader innovation

Episode Tone & Style

Throughout, Ani is earnest, insightful, and practical. The conversation is rich in actionable leadership advice and grounded in real-world challenges, celebrating both technical rigor and the people behind the systems.

For listeners seeking actionable strategies on platform scaling, team leadership, or the AI-driven future of logistics, this concise but content-rich episode distills valuable expert insight and candid experience.