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3271: Inside Poolside’s Mission to Reinvent Enterprise Software Engineering

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Manage episode 481248916 series 80936
Content provided by Neil C. Hughes. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Neil C. Hughes or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Amid the buzz of the AWS Summit in London, I sat down with Eiso Kant, the CTO and Co-Founder of Poolside, to explore how his team is reshaping the future of software development through AI. This conversation was recorded right on the show floor inside a surprisingly sleek podcast booth at the ExCel, where Eiso unpacked what sets Poolside apart in a space many claim to be in but few truly build for.

Poolside is not just another AI company. It's one of a handful globally that is actually training foundation models from the ground up. While most firms are chasing general-purpose AI, Poolside has chosen a different path. They focus solely on empowering software developers inside high-consequence environments, such as banking, defense, and major global retailers. These are systems where precision and security matter, and where AI can drive measurable gains in productivity and reliability.

What struck me during this discussion is how deliberately Poolside has been built for enterprise use from the start. Their model doesn’t just live in the cloud. It is designed to live within the customer’s own infrastructure, whether that’s in their private AWS environment or even on-prem. This focus on data privacy, security, and customizability is helping Poolside win trust where it counts most. And the partnership with AWS takes this a step further, making it easier for enterprises to deploy Poolside’s AI within existing cloud frameworks while meeting strict governance requirements.

Eiso explained that Poolside doesn’t just throw larger models at problems. Instead, they use reinforcement learning from code execution, training on millions of real codebases and test suites. This approach helps the model go beyond autocomplete and simple bug fixes. It’s now stepping into longer, more complex tasks, nudging us closer to a future where AI could serve as a true teammate for software engineers.

We also tackled one of the most important discussions in AI today: whether this is a cost-cutting tool or a productivity multiplier. Eiso didn't dodge the nuance. While some may use AI to reduce headcount, Poolside’s focus is on enabling companies to build more, ship faster, and innovate with greater speed. That shift is not about replacing people. It's about creating leverage for development teams under pressure to deliver more in less time.

If you're a CTO, CIO, or engineering leader, this episode is packed with practical insights. Whether it's understanding the ROI of AI-assisted development, the importance of retaining control of your own models, or how to think about enterprise-grade security in the age of LLMs, there's a lot here to digest.

So how should we really be thinking about AI in the enterprise? Is it a partner, a tool, or the beginning of an entirely new workforce paradigm? Tune in to find out.

  continue reading

2045 episodes

Artwork
iconShare
 
Manage episode 481248916 series 80936
Content provided by Neil C. Hughes. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Neil C. Hughes or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Amid the buzz of the AWS Summit in London, I sat down with Eiso Kant, the CTO and Co-Founder of Poolside, to explore how his team is reshaping the future of software development through AI. This conversation was recorded right on the show floor inside a surprisingly sleek podcast booth at the ExCel, where Eiso unpacked what sets Poolside apart in a space many claim to be in but few truly build for.

Poolside is not just another AI company. It's one of a handful globally that is actually training foundation models from the ground up. While most firms are chasing general-purpose AI, Poolside has chosen a different path. They focus solely on empowering software developers inside high-consequence environments, such as banking, defense, and major global retailers. These are systems where precision and security matter, and where AI can drive measurable gains in productivity and reliability.

What struck me during this discussion is how deliberately Poolside has been built for enterprise use from the start. Their model doesn’t just live in the cloud. It is designed to live within the customer’s own infrastructure, whether that’s in their private AWS environment or even on-prem. This focus on data privacy, security, and customizability is helping Poolside win trust where it counts most. And the partnership with AWS takes this a step further, making it easier for enterprises to deploy Poolside’s AI within existing cloud frameworks while meeting strict governance requirements.

Eiso explained that Poolside doesn’t just throw larger models at problems. Instead, they use reinforcement learning from code execution, training on millions of real codebases and test suites. This approach helps the model go beyond autocomplete and simple bug fixes. It’s now stepping into longer, more complex tasks, nudging us closer to a future where AI could serve as a true teammate for software engineers.

We also tackled one of the most important discussions in AI today: whether this is a cost-cutting tool or a productivity multiplier. Eiso didn't dodge the nuance. While some may use AI to reduce headcount, Poolside’s focus is on enabling companies to build more, ship faster, and innovate with greater speed. That shift is not about replacing people. It's about creating leverage for development teams under pressure to deliver more in less time.

If you're a CTO, CIO, or engineering leader, this episode is packed with practical insights. Whether it's understanding the ROI of AI-assisted development, the importance of retaining control of your own models, or how to think about enterprise-grade security in the age of LLMs, there's a lot here to digest.

So how should we really be thinking about AI in the enterprise? Is it a partner, a tool, or the beginning of an entirely new workforce paradigm? Tune in to find out.

  continue reading

2045 episodes

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