In this episode of The Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Harpinder "Happy" Singh, AI/ML Engineer at DevRev, to explore the future of AI and machine learning in business automation. Happy, who joined DevRev in 2021, shares his journey from computer science to AI, discussing how DevRev is leveraging cutting-edge technologies like large language models (LLMs) and function calling to streamline enterprise workflows.

Happy breaks down the key concepts of AI-driven workflows, the debate between federated and integrated systems, and the growing importance of Python in AI. He also shares insights from the CodeAct paper, which proposes using Python code execution for more efficient and flexible LLMs. The conversation highlights the transformative potential of AI in enterprise automation and how it is reshaping industries.

They also cover:

• The evolution of AI at DevRev: From workflows to AI-driven automation
• The role of Python in executing complex tasks for LLMs
• Understanding the user-agent-environment model in AI systems
• How federated vs. integrated systems impact AI performance
• The future of AI in enterprise automation and DevRev’s innovations
• Happy’s decision to stay in India and the growing tech ecosystem in India

This episode provides valuable insights into how AI is transforming business operations, making complex workflows more efficient and accessible. Whether you're an AI enthusiast, a developer, or a business leader, this conversation is a must-listen for anyone interested in the next wave of AI-driven innovation.

Key Topics & Timestamps:

00:00 – Introduction to Harpinder "Happy" Singh & His Journey into AI

03:00 – Happy’s Early Background: From Shahjahanpur to BITS Pilani

06:30 – Transition to AI at DevRev

09:30 – Bangalore Life and Growing with DevRev

13:00 – AI in India vs. the US

18:00 – Federated vs. Integrated Systems: Which Approach Works Best for AI?

25:00 – The Role of Python in AI

32:00 – User, Agent, and Environment Model in AI

39:30 – The CodeAct Paper: Replacing Tool Calls with Python Code Execution

47:00 – AI in Enterprise Automation: How DevRev Uses AI to Streamline Workflows

54:00 – Looking Ahead at DevRev’s AI Innovations

1:00:00 – Final Reflections: The Future of AI in Business and Automation

Hosts:
Dheeraj Pandey: Co-founder and CEO at DevRev, formerly CEO of Nutanix, a tech visionary passionate about AI and systems thinking.
Amit Prakash: Co-founder and CTO at ThoughtSpot, former engineer at Google and Microsoft, and expert in distributed systems and machine learning.

Guest:
Harpinder Jot Singh: AI/ML Engineer at DevRev, working on the cutting edge of large language models (LLMs), AI-driven workflows, and integrating AI into enterprise systems.

Follow the Host and the Guest:

Dheeraj Pandey: LinkedIn | X

Amit Prakash: LinkedIn | X

Harpinder Singh: LinkedIn

Have questions or thoughts on AI? Drop us a mail at [email protected]

Don’t forget to like, comment, and subscribe for more insights into the future of AI, business automation, and enterprise technology!

Episode 13 | The Effortless Podcast

In this episode of The Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Dr. Sonika Johri, Founder and CEO of Coherent Computing, to dive deep into the revolutionary world of quantum computing. Dr. Johri, a physicist with a PhD in condensed matter physics from Princeton University, takes us on her journey from engineering physics at IIT Delhi to becoming a leading figure in the quantum industry, having worked at Intel and IonQ.

Sonika explains the core concepts of quantum computing—superposition, entanglement, and the quantum state space—and how they fundamentally change how we approach complex problems in fields like chemistry, material science, and AI. She discusses the future potential of quantum technologies, including the exciting prospects for Quantum AI and the shift in programming paradigms as we move from low-level machine code to higher-level abstractions.

They also cover: 

• The evolution of quantum hardware: From small qubits to scaling quantum systems
• What makes quantum computing different from classical computing
• The intersection of quantum computing and artificial intelligence 
• Sonika’s mission to democratize quantum through Coherent Computing
• The current state of quantum software and the tools that will shape the future

This episode offers insights into quantum computing, AI, and how these emerging technologies will reshape the future of computing. Whether you’re a tech enthusiast, developer, or entrepreneur, this conversation is a must-listen for anyone curious about the next frontier in technology.

Key Topics & Timestamps:
[00:00] – Introduction to Dr. Sonika Johri & Her Journey into Quantum Tech

[03:00] – Sonika’s early influences: Einstein and IIT Delhi

[06:30] – Understanding Condensed Matter Physics

[12:00] – Quantum Computing vs Classical Computing

[20:00] – How Quantum Can Solve Complex Problems (Chemistry, Optimization, AI)

[28:00] – Quantum Hardware: The Role of Qubits and Their Physical Realization

[35:00] – Programming Quantum Computers: From Low-Level Gates to High-Level Abstractions

[43:00] – Building Quantum Applications: Real-World Use Cases from IonQ and Coherent Computing

[52:00] – The Future of Quantum AI: Machine Learning and Quantum Reasoning

[1:00:00] – Quantum's Impact on Cryptography and Data Security

[1:05:00] – The Mission of Coherent Computing: Making Quantum Accessible

[1:12:00] – Looking Ahead: Future Episodes on Quantum Computing and AI

[1:20:00] – Wrap-Up and Final Thoughts

Hosts:
Dheeraj Pandey: Co-founder and CEO at DevRev, formerly CEO of Nutanix, a tech visionary passionate about AI and systems thinking.
Amit Prakash: Co-founder and CTO at ThoughtSpot, former engineer at Google and Microsoft, and expert in distributed systems and machine learning.

Guest:
Dr. Sonika Johri: Founder and CEO of Coherent Computing, a quantum software startup aiming to make quantum models accessible through developer-friendly tools. Formerly at Intel and IonQ, Sonika brings her experience in building quantum software and applications for industries like finance, chemistry, and optimization.

Follow the Host and the Guest:

Dheeraj Pandey: LinkedIn | X

Amit Prakash: LinkedIn | X

Dr. Sonika Johri: LinkedIn | X

Have questions or thoughts on quantum computing? Drop us a mail at [email protected]

Don’t forget to like, comment, and subscribe for more deep dives into the future of technology, AI, and quantum computing!

In this episode of The Effortless Podcast, host Dheeraj Pandey sits down with Bipul Sinha, co-founder and CEO of Rubrik, to explore the power of relentless innovation, first-principles thinking, and continuous reinvention.

Bipul shares his journey from Oracle to venture capital, his transition from investor to entrepreneur, and the bold thinking behind Rubrik’s evolution from backup and recovery to cybersecurity and AI-driven data protection. He and Dheeraj reflect on lessons from Larry Ellison, the shifting tech landscape, and the importance of being non-consensus in building transformative businesses.

They also discuss:
🔹 The power of controversial ideas and why misunderstanding is a sign of innovation
🔹 How converging backup and security is reshaping enterprise cyber resilience
🔹 Why businesses must think backwards to execute forwards
🔹 The role of AI in simplifying cybersecurity and data management
🔹 Insights on US Federal, global markets, and the changing economic landscape

This episode is packed with wisdom on leadership, risk-taking, and the mindset needed to challenge the status quo. If you're a founder, investor, or technologist, this conversation will redefine how you think about disruption and reinvention.

• [00:00] – Are you creating the future or burdened by the past?
• [02:00] – Oracle memories: The Larry Ellison mindset & first-principles thinking
• [09:00] – The leap from venture capital to entrepreneurship
• [16:00] – Why big ideas must be controversial to create true value
• [24:00] – The evolution of Rubrik: From backup to cybersecurity to AI
• [31:00] – The power of change & why businesses must continuously reinvent
• [40:00] – AI & cybersecurity: Why protecting data is the new frontier
• [50:00] – Lessons from global markets, US Federal, and economic shifts
• [58:00] – Adhogami vs. Urdhogami: The danger of relying on the past

Host:

Dheeraj Pandey: Co-founder and CEO at DevRev, formerly Co-founder and CEO of Nutanix. A tech visionary with a deep interest in AI and systems thinking.

Guest:

Biplu Sinha: Co-founder and CEO of Rubrik, and former venture capitalist at Lightspeed and Blumberg. Bipul is an entrepreneur and investor with deep expertise in enterprise software, cybersecurity, and data management. Passionate about building enduring institutions and pioneering first-principles innovation.

Follow the Host and the Guest:

Dheeraj Pandey:

LinkedIn - https://www.linkedin.com/in/dpandey

Twitter - https://x.com/dheeraj

Bipul Sinha:

LinkedIn -https://linkedin.com/in/bipulsinha

Twitter - https://x.com/bipulrsinha
 

Share Your Thoughts:

Have questions, comments, or ideas for future episodes? Email us at [email protected]

Don’t forget to Like, Comment, and Subscribe for more in-depth discussions on AI, technology, and innovation!

In this episode, Amit and Dheeraj dive deep into the world of AI reasoning models with Alex, an AI researcher involved in OpenThinker and OpenThoughts. They explore two recent groundbreaking papers—SkyT1 and S1 (Simple Test Time Scaling)—that showcase new insights into how large language models (LLMs) develop reasoning capabilities.

From structured reasoning vs. content accuracy to fine-tuning efficiency and the role of active learning, this conversation highlights the shift from prompt engineering to structured supervised fine-tuning (SFT) and post-training techniques. The discussion also touches on open weights, open data, and open-source AI, revealing the evolving AI landscape and its impact on startups, research, and beyond.

• [00:00] Introduction – Why reasoning models matter & today's agenda
• [05:15] Breaking Down SkyT1 – Structure vs. Content in reasoning
• [15:45] Open weights, open data, and open-source AI
• [22:30] Fine-tuning vs. RL – When do you need reinforcement learning?
• [30:10] S1 and the power of test-time scaling
• [40:25] Budget forcing – Making AI "think" more efficiently
• [50:50] RAG vs. SFT – What should startups use?
• [01:05:30] Active learning – AI asking the right questions
• [01:15:00] Final thoughts – Where AI reasoning is heading next

📄 Papers Discussed:

• SkyT1: "LLMs Can Easily Learn to Reason from Demonstrations"
• S1: "Simple Test-Time Scaling"

Hosts:

Dheeraj Pandey: Co-founder and CEO at DevRev, formerly Co-founder and CEO of Nutanix. A tech visionary with a deep interest in AI and systems thinking.

Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, with extensive expertise in analytics and large-scale systems.

Guest:

Alex Dimakis: Professor at UC Berkeley and co-founder of Bespoke Labs, Alex has made significant contributions to deep learning, machine learning infrastructure, and the development of AI reasoning frameworks.

Follow the Hosts and the Guest:

Dheeraj Pandey:

LinkedIn - https://www.linkedin.com/in/dpandey

Twitter - https://x.com/dheeraj

Amit Prakash:

LinkedIn - https://www.linkedin.com/in/amit-prakash-50719a2/

Twitter - https://x.com/amitp42

Alex Dimakis:

LinkedIn - https://www.linkedin.com/in/alex-dimakis-b1b20320

Twitter - https://x.com/AlexGDimakis

Share Your Thoughts:

Have questions, comments, or ideas for future episodes? Email us at [email protected]

Don’t forget to Like, Comment, and Subscribe for more in-depth discussions on AI, technology, and innovation!

This is the second part of episode 10 of Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Alex Dimakis, a renowned AI researcher and professor, to discuss one of the biggest breakthroughs in open AI models—DeepSeek R1. They explore how DeepSeek’s innovations in reasoning, reinforcement learning, and efficiency optimizations are reshaping the AI landscape.

The conversation covers the shift from large, proprietary AI models to open-source alternatives, the role of post-training fine-tuning, and how reinforcement learning (GRPO) enables reasoning capabilities in LLMs. They also dive into KV caching, mixture of experts, multi-token prediction, and what this means for NVIDIA, hardware players, and AI startups.

Key Topics & Timestamps:

[00:00] - Introduction & Why DeepSeek Matters

[01:30] - DeepSeek R1: Open-Source AI Disrupting the Industry

[03:00] - Has China Become an AI Innovator?

[07:30] - Open Weights vs. Open Data: What Really Matters?

[10:00] - KV Caching, Mixture of Experts & Model Optimizations

[21:00] - How Reinforcement Learning (GRPO) Enables Reasoning

[32:00] - Why OpenAI is Keeping Its Reasoning Traces Hidden

[45:00] - The Impact of AI on NVIDIA & Hardware Demand

[1:02:00] - AGI: Language Models vs. Multimodal AI

[1:15:00] - The Future of AI: Fine-Tuning, Open-Source & Specialized Models

Hosts:

Dheeraj Pandey: Co-founder and CEO at DevRev, formerly Co-founder and CEO of Nutanix. A tech visionary with a deep interest in AI and systems thinking.

Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, with extensive expertise in analytics and large-scale systems.

Guest:

Alex Dimakis: Professor at UC Berkeley and co-founder of Bespoke Labs, Alex has made significant contributions to deep learning, machine learning infrastructure, and the development of AI reasoning frameworks.

Follow the Hosts and the Guest:

Dheeraj Pandey:

LinkedIn - https://www.linkedin.com/in/dpandey

Twitter - https://x.com/dheeraj

Amit Prakash:

LinkedIn - https://www.linkedin.com/in/amit-prak...

Twitter - https://x.com/amitp42

Alex Dimakis:

LinkedIn - https://www.linkedin.com/in/alex-dima...

Twitter - https://x.com/AlexGDimakis

Share Your Thoughts:

Have questions, comments, or ideas for future episodes? Email us at [email protected]

Don’t forget to Like, Comment, and Subscribe for more in-depth discussions on AI, technology, and innovation!

In this episode of the Effortless Podcast, hosts Dheeraj Pandey and Amit Prakash sit down with Alex Dimakis, a renowned AI researcher and professor at UC Berkeley. With a background in deep learning, graphical models, and foundational AI frameworks, Alex provides unparalleled insights into the evolving landscape of AI.

The discussion delves into the detailing of foundation models, modular AI architectures, fine-tuning, and the role of synthetic data in post-training. They also explore practical applications, challenges in creating reasoning frameworks, and the future of AI specialization and generalization.

As Alex puts it, "To deep seek or not, that’s the $1 trillion question." Tune in to hear his take on how companies can bridge the gap between large generalist models and smaller specialized agents to achieve meaningful AI outcomes.

Key Topics and Chapter Markers:

• Introduction to Alex Dimakis & His Journey [0:00]
• From Foundation Models to Modular AI Systems [6:00]
• Fine-Tuning vs. Prompting: Understanding Post-Training [15:00]
• Synthetic Data in AI Development: Challenges and Solutions [25:00]
• The Role of Reasoning and Chain of Thought in AI [45:00]
• AI's Future: Specialized Models vs. General Systems [1:05:00]
• Alex’s Reflections on AI Research and Innovation [1:20:00]

Hosts:

• Dheeraj Pandey: Co-founder and CEO at DevRev, formerly Co-founder and CEO of Nutanix. A tech visionary with a deep interest in AI and systems thinking.
• Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, with extensive expertise in analytics and large-scale systems.

Guest:
Alex Dimakis: Professor at UC Berkeley and co-founder of Bespoke Labs, Alex has made significant contributions to deep learning, machine learning infrastructure, and the development of AI reasoning frameworks.

Follow the Hosts and the Guest:

• Dheeraj Pandey:
  
  • LinkedIn: Dheeraj Pandey
  • Twitter: @dheeraj
     
• Amit Prakash:
  
  • LinkedIn: Amit Prakash
  • Twitter: @amitp42
     
• Alex Shtoyanov:
  
  • LinkedIn: Alex Dimakis
  • Twitter: @AlexGDimakis

Share Your Thoughts:
Have questions, comments, or ideas for future episodes? Email us at [email protected]

Don’t forget to Like, Comment, and Subscribe for more in-depth discussions on AI, technology, and innovation!

In this special guest episode of the Effortless Podcast, Amit Prakash sits down with Rajat Monga, the creator of TensorFlow and current Corporate Vice President of Engineering at Microsoft. With a career spanning Google Brain, founding Inference, and leading AI inferencing at Microsoft, Rajat offers a unique perspective on the evolution of AI. The conversation dives into TensorFlow’s revolutionary impact, the challenges of building startups, the rise of PyTorch, the future of inferencing, and how transformative tools like GPT-4 and OpenAI’s Gemini are reshaping the AI landscape.

Key Topics and Chapter Markers:

Introduction to Rajat Monga & TensorFlow Legacy [0:00]

The inflection points in AI: TensorFlow's role and challenges [6:00]

PyTorch vs. TensorFlow: A tale of shifting paradigms [16:00]

The startup journey: Building Inference and lessons learned [27:00]

Exploring O1 and advancements in reasoning frameworks [54:00]

AI inference: Cost optimizations and hardware innovations [57:00]

Agents, trust, and validation: AI in decision-making workflows [1:05:00]

Rajat’s personal journey: Tools for resilience and finding balance [1:20:00]

Host:

Amit Prakash: Co-founder and CTO at ThoughtSpot, formerly at Google AdSense and Bing, and a PhD in Computer Engineering. Amit has a strong track record in analytics, machine learning, and large-scale systems.

Follow Amit on:

LinkedIn - https://www.linkedin.com/in/amit-prakash-50719a2/  

X (Twitter) - https://x.com/amitp42

Guest:

Rajat Monga: He is a pioneer in the AI industry, best known as the co-creator of TensorFlow. He has held senior roles at Google Brain and Microsoft, shaping the foundational tools that power today’s AI systems. Rajat also co-founded Inference, a startup focused on anomaly detection in data analytics. At Microsoft, he leads AI software engineering, advancing inferencing infrastructure for the next generation of AI applications. He holds a Btech Degree from IIT, Delhi.

Follow Rajat on:

LinkedIn - https://www.linkedin.com/in/rajatmonga/  

X (Twitter) - https://twitter.com/rajatmonga

Share Your Thoughts: Have questions or comments? Drop us a mail at [email protected]

Email: [email protected]

In this episode, Amit and Dheeraj dive deep into the transformative world of AI agents and enterprise workflows. They explore the concept of “AgentOS”—a platform enabling modular agents, each equipped with specific skills to tackle distinct challenges within workflows. Drawing parallels between AI advancements and real-world enterprise needs, Amit and Dheeraj discuss the importance of balancing both probabilistic AI-driven nodes with deterministic workflows to enhance efficiency without losing context or accuracy.

Together, they examine industry needs, like reducing redundancy in incident management through vector databases, and predict the impact of AI agents on collaboration platforms, employee workflows, and customer support. This episode is a rich, thought-provoking journey through the latest in AI, where Amit and Dheeraj also offer their insights into enterprise AI adoption, future trends, and their forecasts for the next decade of AI-driven business transformation.

Key Topics and Timestamps:

• The Rise of AI Agents [0:14]
• System 1 and System 2 Thinking in AI [1:50]
• Workflows in Enterprise Automation [3:51]
• Handling Context and Intent in Workflows [10:32]
• Incident Management and Reducing Redundancy [43:57]
• Collaboration Platforms’ Future [49:13]
• Optimizing Enterprise Workflows with Agentic Systems [1:03:46]
• The Enterprise AI Landscape and Predictions [1:13:18]

Share Your Thoughts: Have questions or comments? Drop us a mail at [email protected]

In Episode 07 of The Effortless Podcast, Amit and Dheeraj embark on a deep dive into the world of analytics, unpacking its evolution, present state, and future in a tech landscape transformed by AI and cloud computing. The episode explores how analytics has grown from complex, on-premise systems to dynamic, cloud-powered solutions, accessible to anyone with a query. Amit and Dheeraj, with decades of combined experience in data architecture, share personal stories from their journeys at companies like Google, Oracle, and ThoughtSpot, alongside their perspectives on the transformations analytics has undergone over time. They highlight the shift from structured SQL-based data systems to the unstructured, AI-driven models of today.

Key Topics and Chapter Markers:

• The Foundations of Modern Analytics [00:03:00]
• Cloud Computing’s Impact on Analytics [00:15:30]
• Data Warehouse Wars: Snowflake vs. Databricks [00:26:15]
• AI, LLMs, and the Future of Analytics [00:41:10]
• Visualization as the Next Frontier in Analytics [00:45:00]
• Reflections on the Path to AI [00:52:30]
   

Share Your Thoughts: Have questions or comments? Drop us a mail at [email protected]

This episode continues the journey from Part 1, where hosts Amit Prakash and Dheeraj Pandey mapped out AI’s evolution from its inception in the 1950s to the transformative hardware advancements that laid the groundwork for modern machine learning. In Part 2, Amit and Dheeraj pick up the thread to explore the key concepts that have defined AI’s development in the past two decades. They delve into the significance of neural network embeddings, vector representations, and the role of innovative frameworks like TensorFlow and PyTorch, shedding light on how these tools have driven modern AI forward.

Listeners will gain unique insights into the breakthroughs that made today’s language models possible—from the introduction of attention mechanisms to the 2017 release of the transformer model, which fundamentally reshaped natural language processing. Amit and Dheeraj also discuss the scaling of AI with powerful hardware, including GPUs, and the impact of transfer learning and reinforcement learning with human feedback (RLHF). This episode is an invaluable listen for anyone curious about the mechanics behind modern AI and the future of intelligent systems.

Key Topics & Chapter Markers:

• Recap from Part 1: The Early Years of AI [00:00:00]
• AI Architecture & Oracle’s Innovation in Hash Joins [00:02:00]
• Impact of Nature in Creative and Collaborative Work [00:05:00]
• The Rise of Neural Networks: Language and Image Processing [00:10:00]
• Sparse and Dense Vectors Explained [00:15:00]
• Google Translate’s Early Approaches & Statistical Methods [00:20:00]
• TensorFlow vs. PyTorch: Defining the Modern AI Framework [00:30:00]
• Dot Products, Similarity, and the Concept of Attention [00:35:00]
• Transformers & The Attention Mechanism Revolution [00:42:00]
• BERT, GPT, and the Dawn of Transfer Learning [01:00:00]
• The Road to ChatGPT and OpenAI’s Innovations [01:10:00]
• The Future of AI and Computational Scaling [01:15:00]
   

Share Your Thoughts: Have questions or comments? Drop us a mail at [email protected]