Discover how Radical AI is revolutionizing material science using self-driving labs.

About the episode:

Nataraj hosts Joseph Krause, CEO of Radical AI, to explore how they're speeding up material R&D by combining AI, engineering, and robotics. Joseph shares his journey from material science to venture capital, highlighting Radical AI's mission to create a self-driving lab that autonomously designs tests and discovers new materials. The episode dives into Radical AI's materials flywheel concept, their open-source engine, and how they're attracting funding to drive innovation in material science. Discover how Radical AI is set to revolutionize industries from aerospace to energy with cutting-edge material discovery.

What you’ll learn

 * Understand the traditional challenges hindering the commercialization of new materials and how Radical AI is overcoming them.
 * Discover the materials flywheel concept and how it accelerates the speed of material discovery.
 * Learn about the types of customers who are seeking new materials and the diverse applications across various industries.
 * Explore the role of AI in simulating and experimenting with materials, and the importance of experimental validation.
 * Understand the types of AI models Radical AI uses, including machine learning, generative AI, and computer vision.
 * Identify Radical AI’s hiring strategy to build an interdisciplinary team across machine learning, software engineering, robotics, and material science.
 * Comprehend the importance of experimental data in materials science and how self-driving labs capture and utilize this data.
 * Learn about Radical AI’s stepwise approach to focus on customer-driven problems and enabling technologies.

About the Guest and Host:

Guest Name: Joseph Krause, Co-founder and CEO of Radical AI, aiming to revolutionize material science with AI, engineering, and robotics.

Connect with Guest: 

→ LinkedIn: https://www.linkedin.com/in/josephfkrause

→ Website: https://www.radical-ai.com/

Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor. 

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/  

→ Substack: ⁠https://startupproject.substack.com/⁠



In this episode, we cover  

 *  (00:01) Introduction to Radical AI and Joseph Krause
 * (01:15) Joseph’s diverse background and how it led to Radical AI
 * (05:01) Traditional ways preventing commercialization of new materials
 *  (09:06) Radical AI’s product: novel materials for aerospace, defense, and energy
 * (11:36) Customers seeking new materials and the advantage of speed in the materials flywheel
 * (13:39) Challenges in digital research and the importance of physical experimentation
 * (16:18) How Radical AI picks directions for new material discovery
 * (23:48) The AI part of Radical AI: hiring and AI models used
 * (27:13) Predicting crystal structures with AI
 * (31:57) Why New York is the best place for Radical AI
 * (33:37) Joseph’s best AI use case for personal research
 * (37:35) Material research happening at Apple



Don’t forget to subscribe and leave us a review/comment on YouTube [https://www.youtube.com/@thestartupproject] Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2] or wherever you listen to podcasts.



#RadicalAI #AI #MaterialScience #Rob

How AI Is Unlocking Materials We’ve Never Been Able to Build | Radical AI

Unlock the secrets to Decagon AI's $1.5 billion valuation and AI-powered customer support.

Ashwin Sreenivas is the co-founder of Decagon AI, a company revolutionizing enterprise customer support with AI agents. Founded in 2023, Decagon has rapidly grown to a $1.5 billion valuation, automating support workflows for brands like Duolingo and Notion. Ashwin, previously co-founder of Helio (acquired by Scale AI), shares insights into Decagon's product-market fit, secret sauce, and tangible business impact, revealing how AI is transforming customer interaction. If you're curious about the future of AI in enterprise solutions, this episode is a must-listen.



Listen now YouTube [https://www.youtube.com/@thestartupproject] | Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] | Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2]



Quotes from the episode

 * Traditional chatbots relied on rigid decision trees, leading to frustrating customer experiences, but Decagon's AI agents are trained like humans, enabling fluid, natural conversations.
 * Decagon's AI agents follow Agent Operating Procedures (AOPs), which are similar to human SOPs, and this allows them to handle customer interactions across chat, phone, SMS, and email.
 * The key is to focus on building AI agents that can follow instructions effectively, allowing businesses to offer personalized customer concierge services and seamless user experiences.
 * Instead of predicting what customers want, AI should learn customer preferences and remember them, making interactions more seamless and efficient, enhancing overall satisfaction.



What you’ll learn

 * Understand how Decagon AI is transforming customer support by using AI agents that can handle conversations across various channels.
 * Learn about Agent Operating Procedures (AOPs) and how they enable AI agents to follow instructions and interact with customers like humans.
 * Discover how Decagon AI helps businesses expand their support offerings, leading to higher retention and happier customers through increased support access.
 * Explore the importance of solving customer problems quickly and seamlessly, regardless of whether the interaction is with a human or an AI agent.
 * See how Decagon AI is expanding beyond customer support to offer customer concierge services, enabling personalized and friction-free interactions.
 * Learn how focusing on customer needs and building something people will pay for can simplify early-stage company challenges.

Takeaways

 * Decagon AI's agents use Agent Operating Procedures (AOPs) to mimic human-like interactions, which contrasts with older chatbot tech that relied on rigid decision trees.
 * Unlike traditional approaches, Decagon AI focuses on creating a single agent adept at following instructions, improving onboarding and iteration for customers.
 * Training smaller, fine-tuned models can outperform larger models on specific tasks, providing better performance and lower latency for customer interactions.
 * Customer support is evolving into a brand differentiator, with companies like Amazon and American Express setting the standard for excellent service and customer trust.
 * By making support more affordable, businesses can reinvest savings into providing more extensive support, leading to higher customer retention and satisfaction.
 * Early customer acquisition requires manual effort, including networking, cold emailing, and LinkedIn messaging, with a focus on charging for the software from day one.
 * Con

How Decagon Built Human-Level AI Support: Ashwin Sreenivas on customer obsession, early traction, enterprise complexity, and the AI concierge future

Discover the evolving roles of traditional vs. new media in tech and gain insights into effective content creation strategies.

About the episode:

In this episode, Nataraj hosts Alex Konrad, founder and editor of Upstart Media, to explore the shifting dynamics of tech media. Alex shares his experiences at Forbes, defines the roles of traditional and new media, and discusses the challenges and opportunities for new tech publications. He also dives into storytelling trends, content creation strategies, and the impact of AI on the media landscape. Learn how new media publications can thrive in a decentralized ecosystem and why staying close to the "engine room" of innovation is crucial for success.

What you’ll learn

 * Identify the key differences between traditional and new media in the tech landscape.
 * Understand the challenges and opportunities for new tech publications in a decentralized media ecosystem.
 * Discover effective content creation and distribution strategies for building a successful media brand.
 * Learn how to build a pipeline of stories and get sources as a media startup without the brand of a larger publication.
 * Explore the impact of AI on the media landscape and its potential to empower independent creators.



About the Guest and Host:

Alex Konrad: Founder and editor of Upstart Media, a tech publication focused on the startup ecosystem.Connect with Alex: → LinkedIn: https://www.linkedin.com/in/alexrkonrad/→ Website: https://www.upstartsmedia.com/Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor. → LinkedIn: https://www.linkedin.com/in/natarajsindam/ → Substack: ⁠https://startupproject.substack.com/⁠In this episode, we cover

 * (00:01) Introduction to Alex Konrad and Upstart Media
 * (01:24) Alex’s experience at Forbes and its role in today’s tech media
 * (03:43) Defining traditional vs. new media and the rise of independent content creators
 * (06:25) The challenges and differences between working at a large publication vs. running a startup media company
 * (07:01) The components of a new tech publication in 2025: Substack, YouTube, podcasts, and events
 * (08:41) Content strategy: balancing consistency, quality, and multiple platforms
 * (11:05) Admired content creators and their successful practices in the media space
 * (13:12) The importance of an existing brand and network for new media ventures
 * (15:49) The creator economy's power law and the challenges of standing out
 * (16:56) Distribution strategies: leveraging LinkedIn, X, and Substack recommendations
 * (18:56) The evolving landscape of social media and the rise of Threads
 * (22:16) Bandwidth challenges and the need for AI-powered tools for content creation and distribution
 * (25:05) The Midas List: its methodology, significance, and controversies
 * (30:41) Other influential lists and their impact on the tech industry
 * (32:45) Identifying potential niches and innovative approaches in the media space
 * (36:04) Alex’s insights on AI-driven workflows and automation in various industries
 * (38:48) Nataraj’s perspective on AI as a transformative force and its potential impact
 * (41:11) The importance of being close to the "engine room" of innovation
 * (42:55) Building a pipeline without a big brand name and leveraging word-of-mouth



Don’t forget to subscribe and leave us a review/comment on YouTube [https://www.youtube.com/@thestartupproject] Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2] or wherever you listen to podcasts.



#

From Forbes to Founder: Alex Konrad on new media, creator economy, AI tools for journalists, Midas List secrets, and why traditional media is losing to independent voices

This week we are republishing one of our favourite conversations that didn't get much visibility when it first came out.

About the episode:

Nataraj hosts Pedro Domingos, a distinguished figure in AI and machine learning, to discuss the current state of AI, hype cycles, and future trends. Pedro shares insights from his early career, his widely-read book "The Master Algorithm," and his satirical novel "2040." He offers a critical perspective on LLMs, the AI safety debate, and what truly drives progress in the field, while providing guidance on navigating the complex information landscape and choosing impactful research problems. The discussion dives deep into the societal impact of AI, the importance of critical thinking, and the future of AI research, offering a unique blend of technical insights and thought-provoking commentary. Why should you care? Understand the reality behind the AI hype, identify future trends, and learn how to navigate the complex world of AI research.

What you’ll learn  

    - Understand the reality of AI progress, separating it from the hype and misconceptions surrounding LLMs and AGI [1, 2].

    - Learn about the history of AI, including Herb Simon's Nobel Prize and the evolution of machine learning as a subfield of AI .

    - Discern the truth about AI, including the importance of machine learning, reasoning, and other AI fields .

    - Identify the key factors driving investment in AI and the potential risks of the current AI bubble, including how technological progress can be shaped using S-curves .

    - Gain insights into the future of AI research, exploring the limitations of transformers and the need for diverse research directions .

    - Explore the concept of "The Master Algorithm" and how it provides a comprehensive view of AI, beyond narrow slivers of research .

    - Learn practical tips for navigating the information landscape, including identifying reliable sources, being a critical consumer of information, and maximizing your "Sharpe ratio" in terms of impact .

    - Discover the importance of mentorship and community in AI research, including attending conferences, engaging in discussions, and learning the empirical method of machine learning .

About the Guest and Host:

Guest Name: Pedro Domingos is a professor emeritus of computer science and engineering from the University of Washington and a leading expert in artificial intelligence.

Connect with Guest: 

→ LinkedIn: https://www.linkedin.com/in/pedro-domingos-77b183/



Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor. 

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/  

→ Twitter: https://x.com/natarajsindam

→ Substack: ⁠https://startupproject.substack.com/⁠

→ Website: ⁠⁠⁠https://thestartupproject.io⁠⁠⁠



In this episode, we cover  

    (00:01) Introduction and Guest Introduction

    (01:26) Pedro's early career and why he chose machine learning

    (03:51) Nobel Prizes and AI

    (07:12) AI vs Machine Learning

    (08:53) LLMs and the current AI hype cycle

    (14:17) Comparing Models to Human Intelligence

    (16:56) Investment in AI and progress

    (21:22) Thoughts on OpenAI

    (25:56) Investing in talent

    (29:05) AI Safety

    (35:10) Master Algorithm

    (40:27) Jensen Wong and NVIDIA's Pivot

    (43:59) AI Chip Projects

    (47:05) 2040

    (52:19) How AI Will Change Society

    (55:12) Recommendation Systems

    (59:56) Sources of

AI Hype, Future Trends & Research Trends with Best Selling Author of The Master Algorithm Pedro Domingos

We are republishing one of our favorite episode with the co-founder of Momento this week, we will be publishing a brand new episode next week.

Discover how a NASA engineer leveraged AWS to build a serverless caching solution.

About the episode:

Join Nataraj as he speaks with Khawaja Shams, co-founder and CEO of Momento, a serverless caching solution that just closed a $15 million Series A round. Khawaja shares his journey from processing images for Mars rovers at NASA to leading engineering teams at Amazon and now revolutionizing caching with Momento. He discusses the challenges of building scalable infrastructure, the importance of developer productivity, and how Momento is simplifying real-time data infrastructure for enterprises. Learn how Momento addresses the complexities of traditional caching solutions, enabling developers to focus on building interactive experiences.

What you’ll learn

- Hear Khawaja's experience at NASA, working on image processing for Mars Rovers and his transition to AWS to accelerate image processing.

- Find out how AWS inspired Khawaja to join Amazon and contribute to the growth of cloud computing and its impact on innovation.

- Learn how Momento addresses the complexities of traditional caching solutions, enabling developers to focus on building interactive experiences.

- Understand Momento's accidental discovery of a two-tier caching system that evolved into a web server, enhancing developer productivity and scalability.

- Discover the initial steps from zero to one in building Momento, including team hiring and partnering with design partners for customer feedback and product grounding.

- Hear about target customers for Momento's solutions, focusing on media, entertainment, gaming, and fintech companies with spiky traffic and mission-critical needs.

- Explore Khawaja's perspective on Amazon's leadership principles and Momento's core leadership values, emphasizing customer centricity and psychological safety.

- Gain insights into building a company culture that attracts top talent and addresses the challenges of convincing individuals to join a startup.

About the Guest and Host:

Khawaja Shams: CEO and Co-Founder of Momento, previously at NASA and AWS, building serverless and low-latency solutions.

Connect with Guest: 

→ LinkedIn:  https://www.linkedin.com/in/kshams/

Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor. 

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/  

→ Twitter: https://x.com/natarajsindam

→ Substack: ⁠https://startupproject.substack.com/⁠

→ Website: ⁠⁠⁠https://thestartupproject.io⁠⁠⁠



In this episode, we cover

(00:00) Introduction and Guest Introduction

(01:14) Khawaja's Early Career at NASA

(03:27) Transitioning Image Processing to AWS

(05:59) Joining Amazon and the Cloud Computing Revolution

(08:00) Early Days at Amazon and AWS Culture

(10:08) Roles and Products at Amazon: DynamoDB and Elemental

(13:58) The Vision Behind AWS's Growth

(15:55) The Genesis of Momento: Identifying a Gap in Caching Solutions

(19:07) Insights from DynamoDB Customers

(21:30) Building Momento: From Zero to One

(24:46) Ideal Design Partners and Target Verticals

(27:24) Validating Product-Market Fit

(28:43) B2B Marketing and Growth Strategies

(31:19) Amazon's Leadership Principles and Company Culture

(34:27) Building a Unique Culture at Momento

(36:56) Attracting Talent to a Startup

(39:26) Khawaja's Current Consumption (Books,

The Invisible Layer Powering the AI Infrastructure | Co-Founder and CEO of Momento | Khawaja Shams

Discover how WebAI is revolutionizing AI by enabling powerful models to run directly on devices.

About the episode:

Nataraj chats with David Stout, founder of WebAI, about bringing AI infrastructure to edge devices. David shares his journey from a Michigan farm to pioneering techniques for compressing AI models onto phones, laptops, and even airplanes. They discuss the importance of data privacy, real-time processing, and the shift from cloud-based AI to a web of interconnected, specialized AI systems working across devices. Learn about WebAI's vision for the future of AI and how they achieved a $700 million valuation.

What you’ll learn

- Understand the limitations of cloud-based AI and the advantages of edge computing for data privacy and real-time processing.

- Discover how WebAI compresses and optimizes large AI models to run efficiently on everyday devices like phones and laptops.

- Learn about the potential of a decentralized “web of models” and how it could revolutionize various industries.

- Explore the key factors driving WebAI's success, including their focus on horizontal technology and support for diverse AI models.

- Gain insights into the future of AI hardware and software.

About the Guest and Host:

Guest Name: David Stout, Founder of WebAI, pioneering AI infrastructure for edge devices.

Connect with Guest:

→ LinkedIn: https://www.linkedin.com/in/davidpstout/ 

→ Website: https://www.webai.com/

Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/

→ Substack: ⁠https://startupproject.substack.com/⁠



In this episode, we cover

(00:01) Introduction and Guest Introduction

(01:35) David's Journey in AI and Machine Learning

(03:51) Bringing AI Models to Devices

(05:49) Applications of AI on Devices

(08:10) The Thesis for Starting Web AI

(11:16) Optimizing for Specialized Models

(15:02) Web AI's Customers and Use Cases

(17:00) Hardware Optimization for Web AI

(19:12) Lightweight Personal Models

(22:55) The Trajectory of Foundational Model Companies and AGI

(31:48) Emergent Behavior and Intelligence

(35:17) Prompts Don't Pay Bills

(41:22) Meta's Approach to Recruiting and Spending

(44:51) Form Factors in AI

(51:04) Surprising AI Products

(52:42) Breakthroughs in AI Research

(56:31) XAI's Models

(01:03:24) The Future of Google and Search

(01:06:39) Finding David and WebAI



Don’t forget to subscribe and leave us a review/comment on YouTube [https://www.youtube.com/@thestartupproject] Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2] or wherever you listen to podcasts.



#AI #EdgeComputing #MachineLearning #DataPrivacy #WebAI #ArtificialIntelligence #DecentralizedAI #AIInfrastructure #Startup #Technology #Innovation #Podcast #Entrepreneurship #TechStartups #DeepLearning #ModelCompression #AIModels #Inference #NatarajSindam #StartupProject



Offline AI, personal AI assistants, edge computing revolution, compression of neural networks, privacy, compute efficiency, AI infrastructure startups | David Stout, Founder of Web AI

In this episode, Nataraj welcomes Matt Martin, CEO of Clockwise, to explore the science of smart scheduling. Discover how Clockwise uses AI to optimize calendars, reduce meeting overload, and create more focused work time. Matt shares insights on balancing collaboration with individual productivity, the impact of remote work on meeting culture, and the future of AI-powered time management. Learn actionable strategies to transform your workday and boost your team's efficiency. Why care? Because reclaiming your time is the first step to achieving your goals.

### What you’ll learn

- Implement AI-driven tools to analyze and optimize your schedule for peak productivity.

- Balance maker and manager schedules to accommodate different work styles within your team.

- Identify and eliminate unnecessary meetings to free up valuable time for focused work.

- Leverage asynchronous communication methods to reduce the reliance on synchronous meetings.

- Understand the impact of remote work on meeting culture and adapt your strategies accordingly.

- Measure the ROI of productivity tools to ensure they are contributing to your bottom line.

- Explore the potential of AI agents to automate scheduling and optimize workflows.

- Discover the importance of memory and context in AI assistants for the workplace.

### About the Guest and Host:

Guest Name: Matt Martin, CEO of Clockwise, helping individuals and teams create smarter schedules with AI.

Connect with Guest:

→ LinkedIn: https://www.linkedin.com/in/voxmatt/

→ Website: https://www.getclockwise.com/

Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/

→ Twitter: https://x.com/natarajsindam

→ Substack: ⁠https://startupproject.substack.com/⁠



### In this episode, we cover

(00:01) Introduction to Matt Martin and Clockwise

(00:58) What is Clockwise and how customers use it

(02:19) Optimizing meetings in organizations

(02:56) Maker Schedule versus Manager Schedule

(05:38) Trends in non-scheduled meetings

(07:33) The shift in adopting new SaaS products

(08:43) Impact of zero interest rate environment on SaaS buying

(11:32) AI agents and their promises

(12:49) Measuring efficiency gains with AI tools

(14:14) Outcome-based pricing models

(17:46) How Clockwise leverages AI in its product

(20:51) MCP vs APIs

(22:26) The trend of half-baked tools

(24:54) Rethinking fundamental apps with AI

(26:56) Adding AI features on current products

(29:03) Power of products like Zapier and Enneken with AI

(33:08) Categories of AI companies that are likely to succeed

(36:49) AI assistant for your workplace

(39:26) User interface

(46:01) How to discover Matt and Clockwise

Don’t forget to subscribe and leave us a review/comment on YouTube [https://www.youtube.com/@thestartupproject] Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2] or wherever you listen to podcasts.

#Clockwise #AIScheduling #CalendarOptimization #ProductivityTips #TimeManagement #MeetingStrategy #RemoteWork #HybridWork #AITools #SaaS #Entrepreneurship #StartupProject #Nat

Fixing Broken Meetings, Managing Calendars with AI, and Redesigning the Future of Work | Matt Martin CEO & Co-Founder Clockwise

Discover how Glean AI is transforming enterprise productivity with AI-powered search and intelligent agents.

About the episode:

Join Nataraj as he explores the evolution of enterprise AI with Arvind Jain, CEO of Glean. From its roots as an AI-powered search solution, Glean has transformed into a comprehensive AI agent platform, helping companies like Zapier, Carta, and Grammarly boost productivity. Arvind shares his journey, the challenges of building a universal AI assistant, and his vision for the future of AI at work. Discover how Glean is helping enterprises leverage AI to streamline workflows and enhance employee efficiency. Learn how Glean ensures AI delivers value safely and securely.

What you’ll learn

 * Understand the evolution of Glean from an AI-powered search tool to a comprehensive AI agent platform.
 * Discover how Glean helps enterprises address productivity challenges by providing quick access to internal knowledge.
 * Learn about the techniques Glean employs to reduce hallucinations and ensure accurate, reliable AI-driven insights.
 * Explore the diverse use cases of AI agents in sales, customer service, engineering, and legal departments.
 * Gain insights into Arvind Jain's vision for the future of work, where AI proactively assists employees in their daily tasks.



About the Guest and Host:

Arvind Jain: CEO of Glean, work AI platform, and co-founder of Rubrik.

Connect with Guest:

→ LinkedIn: https://www.linkedin.com/in/jain-arvind

→ Website: glean.com [https://glean.com]

Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/

→ Substack: ⁠https://startupproject.substack.com/⁠



In this episode, we cover

 * (00:01) Introduction to Arvind Jain and Glean AI
 * (01:13) What Glean does: AI-powered search and conversational AI assistant
 * (03:43) The origin story of Glean: Solving productivity challenges in fast-growing companies
 * (06:46) The evolution from search to an AI assistant
 * (09:45) The advantages of tackling hard problems in startups
 * (12:37) Techniques to reduce AI hallucinations and ensure accuracy
 * (17:31) Model Hub: The different models Glean uses
 * (20:16) Use cases for AI agent platforms across various departments
 * (24:42) Workflow agents and the importance of integrations
 * (31:59) The future of work: Proactive AI companions
 * (37:14) Glean's cross-platform vision
 * (39:07) How AI is changing the business of fast-growing startups
 * (43:39) How Glean is becoming more AI-first internally
 * (47:04) Ideas Arvind would explore if starting over with AI
 * (49:49) Key metrics Arvind watches at Glean AI



Don’t forget to subscribe and leave us a review/comment on YouTube [https://www.youtube.com/@thestartupproject] Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2] or wherever you listen to podcasts.



#GleanAI #EnterpriseAI #AISearch #AIAgents #FutureofWork #Productivity #ArtificialIntelligence #Innovation #SaaS #Startups #BusinessInsights #Technology #AIPlatform #WorkflowAutomation #MachineLearning #DeepLearning #AIStrategy #DigitalTransformation #AIinBusiness #TechPodcast



The Future of Enterprise AI: $100M ARR, Agents, Company Building, and Scaling Unicorns | Arvind Jain (Co-founder of Glean, Rubrik, ex-Google)

### About the episode:

Join Nataraj as he interviews Matt DeBergalis, CEO of Apollo GraphQL, about the evolution of GraphQL from an open-source project to a product company. Matt shares insights on building and scaling APIs, the challenges of transitioning open-source tech into a viable business, and how AI is reshaping API development. Discover how Apollo is helping companies of all sizes leverage GraphQL to build agentic experiences and modernize their API strategies.

### What you’ll learn

- Understand the journey of GraphQL from open source to a product-driven company.

- Explore the challenges of adopting and scaling GraphQL in enterprise environments.

- Discover how GraphQL simplifies complex data combinations with its declarative language.

- Learn how Apollo GraphQL helps companies accelerate the development of robust APIs.

- Examine the role of GraphQL in building modern agentic experiences powered by AI.

- Understand how to balance short-term shipping pressures with long-term architectural considerations.

- Identify when GraphQL makes sense for a company based on its API size and consumption needs.

- Discover how AI is driving increased API consumption and transforming user interfaces.

### About the Guest and Host:

Guest Name: Matt DeBergalis is the Co-founder and CEO of Apollo GraphQL, previously CTO and Co-founder at Meteor Development Group.

Connect with Guest:

→ LinkedIn: https://www.linkedin.com/in/debergalis/

→ Website: https://www.apollographql.com/

Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/

→ Twitter: https://x.com/natarajsindam

→ Substack: ⁠https://startupproject.substack.com/⁠

→ Website: ⁠⁠⁠https://thestartupproject.io⁠⁠⁠

### In this episode, we cover

(00:01) Introduction to Matt DeBergalis and Apollo GraphQL

(00:37) Matt's journey and the origins of Apollo GraphQL

(03:24) The transition from open source to a company

(05:02) GraphQL as a client-focused API technology

(07:22) Meta's approach to open source technologies

(10:11) Challenges of converting open source to a business

(13:11) Balancing shipping speed with architectural considerations

(15:52) The risk of adopting the wrong technology

(19:13) The evolution of full-stack development

(23:57) When does adopting GraphQL make sense?

(26:45) Apollo's customer scale and focus

(31:48) Acquiring customers and marketing to developers

(33:52) Matt's transition from CTO to CEO

(37:02) Apollo's sales motion and target audience

(40:24) Matt's thoughts on AI and its impact

(47:12) How AI is changing business metrics

Don’t forget to subscribe and leave us a review/comment on YouTube [https://www.youtube.com/@thestartupproject] Apple [https://podcasts.apple.com/us/podcast/startup-project/id1551300319] Spotify [https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq?si=8dbd3150ef4f4ec2] or wherever you listen to podcasts.

#GraphQL #ApolloGraphQL #API #OpenSource #Enterprise #AI #AgenticAI #APIDevelopment #Startup #Technology #SoftwareDevelopment #GraphQLAdoption #Kubernetes #React #FullStack #DataAnalytics #Innovation #DigitalTransformation #TechStrategy #Podcast



 APIs as Graphs not Endpoints, building a company on open source foundations, why VPs of Engineering face impossible trade-offs | Apollo GraphQL CEO Matt DeBergalis

In this episode of Startup Project, Nataraj interviews Ben Kus, CTO of Box, about the critical role of unstructured data in the AI revolution. They discuss the cost structures of adopting and building with AI, and how AI is transforming enterprise businesses. Ben shares Box's unique perspective, managing over an exabyte of data for 120,000 enterprise customers. Learn how AI can understand, automate, and enhance the value of your unstructured data, turning untapped potential into practical benefits. 

What you’ll learn:

 *  Understand what unstructured data is and why it's so critical for AI applications in business.
 * Discover Box's strategic approach to integrating with other platforms and providing AI solutions on top of your data.
 * Learn about the pivotal moment when Box realized the potential of generative AI and how they retrofitted their platform to be AI-first.
 * Explore early AI use cases launched at Box, including chatting with documents and data extraction, and how enterprises are adopting these features.
 * Understand the cost implications of leveraging AI and how Box balances offering AI for free with managing expenses.
 * Dive into Box's perspective on pricing based on usage versus outcomes, and their current subscription model.
 * Learn about Box's approach to AI agents, their definition, and how they are being implemented to solve complex problems.
 * Discover the concept of "context engineering" and its importance in building AI agents that understand user needs.
 * Understand how AI is impacting productivity within Box and the broader enterprise landscape.
 * Find out about the AI models Box is working with and how they ensure security and trustworthiness for enterprise customers.



About the Guest and Host:

Ben Kus: Chief Technology Officer at Box, previously VP of Product at Box and co-founder of Subspace.

Connect with Guest:

→ LinkedIn:   https://www.linkedin.com/in/benkus .

→ Website: https://box.com/



Nataraj: Host of the Startup Project podcast, Senior PM at Azure & Investor.

→ LinkedIn: https://www.linkedin.com/in/natarajsindam/

→ Twitter: https://x.com/natarajsindam

→ Substack: ⁠https://startupproject.substack.com/⁠



In this episode, we cover:

 * (00:01) Introduction

 * (00:35) What is unstructured data and why is Box in the center of AI?
 * (04:05) Box's strategy on building new AI tools and features.
 * (06:55) The moment Box realized AI was a big shift.
 * (11:08) Earliest AI use cases launched at Box.
 * (15:17) The cost of leveraging AI and its impact on profitability.
 * (19:24) Pricing based on usage vs. outcomes.
 * (22:47) Abuse prevention and handling unlimited storage.
 * (24:16) AI products targeted for specific knowledge worker persona.
 * (28:18) Being an AI-first company.
 * (30:55) Defining and implementing AI agents within Box.
 * (36:38) Form factors for agents in an enterprise product sense.
 * (39:59) Productivity improvements with AI.
 * (44:07) Progression in junior developers.
 * (46:17) Document parsing and extraction.
 * (49:16) AI models Box is working with.
 * (52:10) Startup ideas in the AI era.

   

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How to be an AI first company, Enterprise AI adoption, Future of Developers, Cost of AI, Unlocking value from Enterprise Data with AI & more with Ben Kus | CTO of Box

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