This week, we’re joined by <a href='https://www.linkedin.com/in/bgrgndzz'>Buğra Gündüz</a>, Co-Founder and CEO of <a href='https://www.hockeystack.com/'>HockeyStack</a>, an AI-native GTM platform that unifies data and deploys agents to execute across sales and marketing.Buğra breaks down why the future of GTM is shifting from dashboards and attribution toward systems that can actually take action. As companies accumulate more fragmented data and increasingly complex workflows, visibility alone is no longer enough. Teams need infrastructure that understands their pipeline, identifies what matters, and automates execution across the revenue org.We discuss how HockeyStack went from a single product to a multi-layer platform spanning data, intelligence, and workflow agents, why owning the underlying data layer is critical before introducing AI, and what it takes to convince organizations to move off legacy GTM stacks. Buğra also shares lessons from scaling from $1M to $11M ARR, how they approached early distribution, and why the real moat in GTM may come down to data gravity and workflow dependency rather than features.Episode chapters:<ul><li>1:55 - Dropping Out of College</li><li>3:27 - Acquiring Early Users</li><li>6:50 - Building a Single Source of Customer Truth</li><li>9:20 - Product Marketing Strategy</li><li>14:35 - Enterprise Deals and Security</li><li>17:07 - Building a Generalized Platform</li><li>20:18 - Choosing the Right LLM</li><li>22:28 - The Future of the Sales Org</li><li>26:21 - Hiring at HockeyStack</li><li>29:10 - Building Company Culture</li><li>32:50 - Learning Through Trial and Error</li><li>34:44 - Quick Fire Round </li></ul> This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.

<description>&lt;p&gt;This week, we’re joined by &lt;a href='https://www.linkedin.com/in/bgrgndzz'&gt;Buğra Gündüz&lt;/a&gt;, Co-Founder and CEO of &lt;a href='https://www.hockeystack.com/'&gt;HockeyStack&lt;/a&gt;, an AI-native GTM platform that unifies data and deploys agents to execute across sales and marketing.&lt;/p&gt;&lt;p&gt;Buğra breaks down why the future of GTM is shifting from dashboards and attribution toward systems that can actually take action. As companies accumulate more fragmented data and increasingly complex workflows, visibility alone is no longer enough. Teams need infrastructure that understands their pipeline, identifies what matters, and automates execution across the revenue org.&lt;/p&gt;&lt;p&gt;We discuss how HockeyStack went from a single product to a multi-layer platform spanning data, intelligence, and workflow agents, why owning the underlying data layer is critical before introducing AI, and what it takes to convince organizations to move off legacy GTM stacks. Buğra also shares lessons from scaling from $1M to $11M ARR, how they approached early distribution, and why the real moat in GTM may come down to data gravity and workflow dependency rather than features.&lt;/p&gt;&lt;p&gt;Episode chapters:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;1:55 - Dropping Out of College&lt;/li&gt;&lt;li&gt;3:27 - Acquiring Early Users&lt;/li&gt;&lt;li&gt;6:50 - Building a Single Source of Customer Truth&lt;/li&gt;&lt;li&gt;9:20 - Product Marketing Strategy&lt;/li&gt;&lt;li&gt;14:35 - Enterprise Deals and Security&lt;/li&gt;&lt;li&gt;17:07 - Building a Generalized Platform&lt;/li&gt;&lt;li&gt;20:18 - Choosing the Right LLM&lt;/li&gt;&lt;li&gt;22:28 - The Future of the Sales Org&lt;/li&gt;&lt;li&gt;26:21 - Hiring at HockeyStack&lt;/li&gt;&lt;li&gt;29:10 - Building Company Culture&lt;/li&gt;&lt;li&gt;32:50 - Learning Through Trial and Error&lt;/li&gt;&lt;li&gt;34:44 - Quick Fire Round &lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;br/&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.&lt;/em&gt;&lt;/p&gt;</description>

This week, we’re joined by Buğra Gündüz, Co-Founder and CEO of HockeyStack, an AI-native GTM platform that unifies data and deploys agents to execute across sales and marketing. Buğra breaks down why the future of GTM is shifting from dashboards and attribution toward systems that can actually take action. As companies accumulate more fragmented data and increasingly complex workflows, visibility alone is no longer enough. Teams need infrastructure that understands their pipeline, identifies ...

E68: Automating the Modern GTM Engine with Buğra Gündüz (HockeyStack)

This week, we’re joined by <a href='https://www.linkedin.com/in/alexisgauba/'>Alexis Gauba</a>, Co-Founder of <a href='https://www.raindrop.ai/'>Raindrop</a>, an AI native observability platform built for agents in production.Alexis breaks down why operating agents is fundamentally different from monitoring traditional software. As systems shift from deterministic code to probabilistic behavior, dashboards alone are not enough. Teams need to detect unknown issues, track signals like forgetting, and understand long agent trajectories across millions of AI events.We discuss why agent observability has become essential over the past year, what makes agent infrastructure distinct from prior platform shifts, and when internal tooling stops scaling. Alexis also explains Raindrop’s approach to production monitoring, combining explicit signals with automated detection to help teams not just find issues, but fix them.Episode chapters:<ul><li>2:05 - Founding Raindrop</li><li>3:54 - Building with Close Friends</li><li>5:44 - What Raindrop Actually Does</li><li>7:45 - The Reliability Challenge of Agents</li><li>9:55 - Monitoring Agents at Scale</li><li>14:45 - Experiencing the Pain Firsthand</li><li>18:00 - The Rise of Agent Infrastructure</li><li>22:17 - Internal AI Use Cases</li><li>24:07 - Hiring for Initiative and Ownership</li><li>28:30 - The Power of Multitasking</li><li>32:06 - Quick Fire Round </li></ul>This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.

<description>&lt;p&gt;This week, we’re joined by &lt;a href='https://www.linkedin.com/in/alexisgauba/'&gt;Alexis Gauba&lt;/a&gt;, Co-Founder of &lt;a href='https://www.raindrop.ai/'&gt;Raindrop&lt;/a&gt;, an AI native observability platform built for agents in production.&lt;/p&gt;&lt;p&gt;Alexis breaks down why operating agents is fundamentally different from monitoring traditional software. As systems shift from deterministic code to probabilistic behavior, dashboards alone are not enough. Teams need to detect unknown issues, track signals like forgetting, and understand long agent trajectories across millions of AI events.&lt;/p&gt;&lt;p&gt;We discuss why agent observability has become essential over the past year, what makes agent infrastructure distinct from prior platform shifts, and when internal tooling stops scaling. Alexis also explains Raindrop’s approach to production monitoring, combining explicit signals with automated detection to help teams not just find issues, but fix them.&lt;/p&gt;&lt;p&gt;Episode chapters:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;2:05 - Founding Raindrop&lt;/li&gt;&lt;li&gt;3:54 - Building with Close Friends&lt;/li&gt;&lt;li&gt;5:44 - What Raindrop Actually Does&lt;/li&gt;&lt;li&gt;7:45 - The Reliability Challenge of Agents&lt;/li&gt;&lt;li&gt;9:55 - Monitoring Agents at Scale&lt;/li&gt;&lt;li&gt;14:45 - Experiencing the Pain Firsthand&lt;/li&gt;&lt;li&gt;18:00 - The Rise of Agent Infrastructure&lt;/li&gt;&lt;li&gt;22:17 - Internal AI Use Cases&lt;/li&gt;&lt;li&gt;24:07 - Hiring for Initiative and Ownership&lt;/li&gt;&lt;li&gt;28:30 - The Power of Multitasking&lt;/li&gt;&lt;li&gt;32:06 - Quick Fire Round &lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;em&gt;This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.&lt;/em&gt;&lt;/p&gt;</description>

This week, we’re joined by Alexis Gauba, Co-Founder of Raindrop, an AI native observability platform built for agents in production. Alexis breaks down why operating agents is fundamentally different from monitoring traditional software. As systems shift from deterministic code to probabilistic behavior, dashboards alone are not enough. Teams need to detect unknown issues, track signals like forgetting, and understand long agent trajectories across millions of AI events. We discuss why agent ...

E67: Monitoring the Probabilistic Stack with Alexis Gauba (Raindrop)

This week, we’re joined by <a href='https://www.linkedin.com/in/anish-agarwal-io/'>Anish Agarwal</a>, CEO of <a href='https://traversal.com/'>Traversal</a>, an AI-native site reliability platform helping teams detect, diagnose, and remediate incidents before they spiral into prolonged downtime.Anish shares how Traversal is tackling the full lifecycle of reliability work: identifying what caused an incident, determining which signals actually mattered during alert triage, and helping teams plan how their infrastructure should evolve over time. As modern systems grow more complex, spanning microservices, serverless, and multi-cloud environments, the surface area for failure continues to expand, especially as AI-generated code accelerates change faster than humans can reasonably keep up.We talk about why observability has produced some of the largest outcomes in software, why the traditional dashboard-first model is breaking down, and why the next generation of tooling needs agents that can search, reason over, and act on observability data, not just display it. Anish also breaks down where “self-healing systems” are real today, where expectations need to be reset, and why many AI-SRE products risk building faster horses instead of rethinking the experience entirely.Episode chapters:<ul><li>1:50 — Anish’s background and early building</li><li>2:30 — The origins of SRE and why it emerged</li><li>8:40 — Research-driven thinking in product and engineering</li><li>10:07 — Building for large enterprise environments</li><li>13:00 — AI-driven code and the growing infrastructure surface area</li><li>16:11 — Preparing infrastructure for an AI-native future</li><li>20:10 — Fear, trust, and operating critical systems</li><li>23:05 — From detection to automated action</li><li>24:20 — How the SRE role is changing</li><li>26:05 — Hiring and building the right team</li><li>29:08 — Raising capital from Sequoia and KP</li><li>32:38 — Reflections and lessons learned</li><li>35:50 — Quick-fire round </li></ul>This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.

<description>&lt;p&gt;This week, we’re joined by &lt;a href='https://www.linkedin.com/in/anish-agarwal-io/'&gt;Anish Agarwal&lt;/a&gt;, CEO of &lt;a href='https://traversal.com/'&gt;Traversal&lt;/a&gt;, an AI-native site reliability platform helping teams detect, diagnose, and remediate incidents before they spiral into prolonged downtime.&lt;/p&gt;&lt;p&gt;Anish shares how Traversal is tackling the full lifecycle of reliability work: identifying what caused an incident, determining which signals actually mattered during alert triage, and helping teams plan how their infrastructure should evolve over time. As modern systems grow more complex, spanning microservices, serverless, and multi-cloud environments, the surface area for failure continues to expand, especially as AI-generated code accelerates change faster than humans can reasonably keep up.&lt;/p&gt;&lt;p&gt;We talk about why observability has produced some of the largest outcomes in software, why the traditional dashboard-first model is breaking down, and why the next generation of tooling needs agents that can search, reason over, and act on observability data, not just display it. Anish also breaks down where “self-healing systems” are real today, where expectations need to be reset, and why many AI-SRE products risk building faster horses instead of rethinking the experience entirely.&lt;/p&gt;&lt;p&gt;Episode chapters:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;1:50 — Anish’s background and early building&lt;/li&gt;&lt;li&gt;2:30 — The origins of SRE and why it emerged&lt;/li&gt;&lt;li&gt;8:40 — Research-driven thinking in product and engineering&lt;/li&gt;&lt;li&gt;10:07 — Building for large enterprise environments&lt;/li&gt;&lt;li&gt;13:00 — AI-driven code and the growing infrastructure surface area&lt;/li&gt;&lt;li&gt;16:11 — Preparing infrastructure for an AI-native future&lt;/li&gt;&lt;li&gt;20:10 — Fear, trust, and operating critical systems&lt;/li&gt;&lt;li&gt;23:05 — From detection to automated action&lt;/li&gt;&lt;li&gt;24:20 — How the SRE role is changing&lt;/li&gt;&lt;li&gt;26:05 — Hiring and building the right team&lt;/li&gt;&lt;li&gt;29:08 — Raising capital from Sequoia and KP&lt;/li&gt;&lt;li&gt;32:38 — Reflections and lessons learned&lt;/li&gt;&lt;li&gt;35:50 — Quick-fire round &lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;em&gt;This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.&lt;/em&gt;&lt;/p&gt;</description>

This week, we’re joined by Anish Agarwal, CEO of Traversal, an AI-native site reliability platform helping teams detect, diagnose, and remediate incidents before they spiral into prolonged downtime. Anish shares how Traversal is tackling the full lifecycle of reliability work: identifying what caused an incident, determining which signals actually mattered during alert triage, and helping teams plan how their infrastructure should evolve over time. As modern systems grow more complex, spannin...

E66: From Alerts to Action with Anish Agarwal (Traversal)

This week, we’re joined by <a href='https://www.linkedin.com/in/ivanburazin/'>Ivan Burazin</a>, co-founder of <a href='https://www.daytona.io/'>Daytona</a> - a company rethinking developer environments for an AI-native world.We talk about how Daytona creates real value for developers, why the most advanced agent companies are emerging bottom up, and the idea that agents should be treated as first class users with reliable access to compute. Ivan also shares some of Daytona’s most demanding use cases including AI scientists in chemistry and pharma running agents inside massive sandboxes with hundreds of CPUs.We also cover what reliability looks like when customers define success as whether the system works at all, how Daytona maintains sub 90 millisecond latency while spinning up millions of environments per day, and how they support always on usage with no fixed schedule. Finally, we dig into go to market lessons from putting engineers on the front lines early to why Daytona prioritizes in person engagement and intentional events as the most authentic way to build trust with developers.Episode chapters:<ul><li>1:43 – Market timing and why now</li><li>3:18 – Building for developers and dev tools</li><li>4:55 – Global developer communities</li><li>7:55 – Computers as infrastructure for agents</li><li>10:32 – Product-led growth</li><li>12:17 – Enterprise use cases and adoption</li><li>16:25 – Managing cost, performance, and latency</li><li>19:20 – Hiring for resiliency at scale</li><li>20:40 – Internal AI use cases at Daytona</li><li>24:25 – Creating a bottom-up go-to-market motion</li><li>27:42 – Hiring and scaling developer relations</li><li>29:55 – Partnerships and ecosystem strategy</li><li>31:00 – Quick-fire round </li></ul> This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.

<description>&lt;p&gt;This week, we’re joined by &lt;a href='https://www.linkedin.com/in/ivanburazin/'&gt;Ivan Burazin&lt;/a&gt;, co-founder of &lt;a href='https://www.daytona.io/'&gt;Daytona&lt;/a&gt; - a company rethinking developer environments for an AI-native world.&lt;/p&gt;&lt;p&gt;We talk about how Daytona creates real value for developers, why the most advanced agent companies are emerging bottom up, and the idea that agents should be treated as first class users with reliable access to compute. Ivan also shares some of Daytona’s most demanding use cases including AI scientists in chemistry and pharma running agents inside massive sandboxes with hundreds of CPUs.&lt;/p&gt;&lt;p&gt;We also cover what reliability looks like when customers define success as whether the system works at all, how Daytona maintains sub 90 millisecond latency while spinning up millions of environments per day, and how they support always on usage with no fixed schedule. Finally, we dig into go to market lessons from putting engineers on the front lines early to why Daytona prioritizes in person engagement and intentional events as the most authentic way to build trust with developers.&lt;/p&gt;&lt;p&gt;Episode chapters:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;1:43 – Market timing and why now&lt;/li&gt;&lt;li&gt;3:18 – Building for developers and dev tools&lt;/li&gt;&lt;li&gt;4:55 – Global developer communities&lt;/li&gt;&lt;li&gt;7:55 – Computers as infrastructure for agents&lt;/li&gt;&lt;li&gt;10:32 – Product-led growth&lt;/li&gt;&lt;li&gt;12:17 – Enterprise use cases and adoption&lt;/li&gt;&lt;li&gt;16:25 – Managing cost, performance, and latency&lt;/li&gt;&lt;li&gt;19:20 – Hiring for resiliency at scale&lt;/li&gt;&lt;li&gt;20:40 – Internal AI use cases at Daytona&lt;/li&gt;&lt;li&gt;24:25 – Creating a bottom-up go-to-market motion&lt;/li&gt;&lt;li&gt;27:42 – Hiring and scaling developer relations&lt;/li&gt;&lt;li&gt;29:55 – Partnerships and ecosystem strategy&lt;/li&gt;&lt;li&gt;31:00 – Quick-fire round &lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;br/&gt;&lt;em&gt;This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.&lt;/em&gt;&lt;/p&gt;</description>

This week, we’re joined by Ivan Burazin, co-founder of Daytona - a company rethinking developer environments for an AI-native world. We talk about how Daytona creates real value for developers, why the most advanced agent companies are emerging bottom up, and the idea that agents should be treated as first class users with reliable access to compute. Ivan also shares some of Daytona’s most demanding use cases including AI scientists in chemistry and pharma running agents inside massive sandbo...

E65: Infrastructure for AI-First Teams with Ivan Burazin (Daytona)

This week, we’re joined by <a href='https://www.linkedin.com/in/ishangpt/'>Ishan Gupta</a>, co-founder of <a href='https://juicebox.ai/peoplegpt'>Juicebox</a> — a company redefining how recruiting works in an AI-native world.Ishan shares how they pivoted from earlier ideas to focus on the highest value part of hiring: identifying the right people and getting them into process. With Juicebox, you describe what you want in natural language and the platform searches more than 800 million professional profiles, surfaces the best matches, and engages candidates through recruiting agents.Their breakout feature, Autopilot, uses LLMs to semantically evaluate and stack rank candidates based on nuanced criteria, which quickly drove organic growth and strong PMF. We talk about why their data makes the product so sticky, how they see recruiting evolving over the next five years, what led them to raise their Series A, and the culture they are building around moving fast and being intellectually honest.Ishan also shares what they are building next with their memory layer, which will make it clear what the AI is learning over time and how it improves future searches.Episode chapters:<ol><li>1:44 - Competitive programming</li><li>4:35 - Choosing the company name</li><li>5:55 - YC and the pivot</li><li>8:00 - How Juicebox differs from traditional recruiting</li><li>9:51 - The killer feature</li><li>14:30 - What makes the product sticky</li><li>17:15 - Is recruiting a zero sum game</li><li>19:10 - The macro view of hiring</li><li>22:05 - Raising a later Series A</li><li>24:10 - Product expansion</li><li>26:45 - Quick fire round </li></ol> This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.

<description>&lt;p&gt;This week, we’re joined by &lt;a href='https://www.linkedin.com/in/ishangpt/'&gt;Ishan Gupta&lt;/a&gt;, co-founder of &lt;a href='https://juicebox.ai/peoplegpt'&gt;Juicebox&lt;/a&gt; — a company redefining how recruiting works in an AI-native world.&lt;/p&gt;&lt;p&gt;Ishan shares how they pivoted from earlier ideas to focus on the highest value part of hiring: identifying the right people and getting them into process. With Juicebox, you describe what you want in natural language and the platform searches more than 800 million professional profiles, surfaces the best matches, and engages candidates through recruiting agents.&lt;/p&gt;&lt;p&gt;Their breakout feature, Autopilot, uses LLMs to semantically evaluate and stack rank candidates based on nuanced criteria, which quickly drove organic growth and strong PMF. We talk about why their data makes the product so sticky, how they see recruiting evolving over the next five years, what led them to raise their Series A, and the culture they are building around moving fast and being intellectually honest.&lt;/p&gt;&lt;p&gt;Ishan also shares what they are building next with their memory layer, which will make it clear what the AI is learning over time and how it improves future searches.&lt;/p&gt;&lt;p&gt;Episode chapters:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;1:44 - Competitive programming&lt;/li&gt;&lt;li&gt;4:35 - Choosing the company name&lt;/li&gt;&lt;li&gt;5:55 - YC and the pivot&lt;/li&gt;&lt;li&gt;8:00 - How Juicebox differs from traditional recruiting&lt;/li&gt;&lt;li&gt;9:51 - The killer feature&lt;/li&gt;&lt;li&gt;14:30 - What makes the product sticky&lt;/li&gt;&lt;li&gt;17:15 - Is recruiting a zero sum game&lt;/li&gt;&lt;li&gt;19:10 - The macro view of hiring&lt;/li&gt;&lt;li&gt;22:05 - Raising a later Series A&lt;/li&gt;&lt;li&gt;24:10 - Product expansion&lt;/li&gt;&lt;li&gt;26:45 - Quick fire round &lt;/li&gt;&lt;/ol&gt;&lt;p&gt;&lt;br/&gt;&lt;em&gt;This episode is brought to you by Grata, the leading deal sourcing platform for private equity. Grata’s AI powered search, investment grade data, and intuitive workflows help you find and win the right deals faster. Visit grata.com to book a demo.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This episode is also sponsored by Overlap, the AI powered app that uses LLMs to surface the best moments from any podcast. Overlap reads full transcripts, finds the most relevant clips, and stitches them into a personalized stream of insights. Tap into podcasts as a real information source with Overlap 2.0, now available on the App Store.&lt;/em&gt;&lt;/p&gt;</description>

This week, we’re joined by Ishan Gupta, co-founder of Juicebox — a company redefining how recruiting works in an AI-native world. Ishan shares how they pivoted from earlier ideas to focus on the highest value part of hiring: identifying the right people and getting them into process. With Juicebox, you describe what you want in natural language and the platform searches more than 800 million professional profiles, surfaces the best matches, and engages candidates through recruiting agents. Th...

E64: Reinventing How Teams Find Talent with Ishan Gupta (Juicebox)

InProd (fka Partner Path) is a podcast exploring the venture and startup ecosystem through the lens of trailblazing founders and operators building the next wave of AI companies. We feature candid conversations with early-stage leaders, offering practical insights on product execution, GTM, and the messy middle of scaling teams and navigating growth.&nbsp;

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