How We Agent Transistor (https://transistor.fm) https://feeds.transistor.fm/how-we-agent "How We Agent" is Lyzr AI's podcast and video series taking you inside real enterprise AI deployments with sovereign AI, agentic automation, and the production-ready agents actually running in the world's biggest companies. Each episode sits down with industry leaders building (and governing) AI agents at scale © 2026 Lyzr AI da69b3a0-04ae-5e3a-9f5d-b26addd7cd5c yes en Sat, 10 Oct 2026 21:16:47 -0700 Sat, 10 Oct 2026 21:27:13 -0700 https://www.lyzr.ai/podcast/ https://img.transistorcdn.com/A7SkNXilhD9SN7sys7Ze2PT8qntBI8Ma-8Se997H0SE/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9jMGZj/MDExZjAzYTNiOGQ5/ZTE0Y2JjZDE0NDVh/M2FlNy5qcGc.jpg How We Agent https://www.lyzr.ai/podcast/ episodic Lyzr AI "How We Agent" is Lyzr AI's podcast and video series taking you inside real enterprise AI deployments with sovereign AI, agentic automation, and the production-ready agents actually running in the world's biggest companies. Each episode sits down with industry leaders building (and governing) AI agents at scale "How We Agent" is Lyzr AI's podcast and video series taking you inside real enterprise AI deployments with sovereign AI, agentic automation, and the production-ready agents actually running in the world's biggest companies. Lyzr AI subs@lyzr.com No No What Happens to Agile When AI Writes the Code? 11 11 What Happens to Agile When AI Writes the Code? full bd01325a-fd1f-4cb3-bf83-d7d49bf22f68 https://share.transistor.fm/s/831599dd In this episode of How We Agent, Ani sits down with Jason Knight, who leads Agentic Transformation at EWN, a Texas-based operator qualification platform for the oil and gas industry. Jason moved into the role from inside the delivery organization. He has a background in Scrum coaching, Agile development and Lean Startup, with earlier stints at CommunityCare, BOK Financial and the Agile Leadership Institute.

Jason shares how EWN went from running one or two experimental backlog items per sprint to rolling out agents across the company. He also explains why rising AI spend is a sign of progress and why human judgment matters more now than it did a year ago.

The conversation covers agent orchestration, the BMAD Method, agent scorecards, governance frameworks, the future of Scrum, and what AI means for people who have spent years honing their craft.

Whether you’re leading AI adoption, running agile teams or figuring out where you fit in an AI-first workplace, this episode is a practical look at agentic transformation as it’s happening.

]]> In this episode of How We Agent, Ani sits down with Jason Knight, who leads Agentic Transformation at EWN, a Texas-based operator qualification platform for the oil and gas industry. Jason moved into the role from inside the delivery organization. He has a background in Scrum coaching, Agile development and Lean Startup, with earlier stints at CommunityCare, BOK Financial and the Agile Leadership Institute.

Jason shares how EWN went from running one or two experimental backlog items per sprint to rolling out agents across the company. He also explains why rising AI spend is a sign of progress and why human judgment matters more now than it did a year ago.

The conversation covers agent orchestration, the BMAD Method, agent scorecards, governance frameworks, the future of Scrum, and what AI means for people who have spent years honing their craft.

Whether you’re leading AI adoption, running agile teams or figuring out where you fit in an AI-first workplace, this episode is a practical look at agentic transformation as it’s happening.

]]> Sat, 10 Oct 2026 21:11:06 -0700 Lyzr AI Watch on YouTube Lyzr AI 2039 In this episode of How We Agent, Ani sits down with Jason Knight, who leads Agentic Transformation at EWN, a Texas-based operator qualification platform for the oil and gas industry. Jason moved into the role from inside the delivery organization. He has a background in Scrum coaching, Agile development and Lean Startup, with earlier stints at CommunityCare, BOK Financial and the Agile Leadership Institute.

Jason shares how EWN went from running one or two experimental backlog items per sprint to rolling out agents across the company. He also explains why rising AI spend is a sign of progress and why human judgment matters more now than it did a year ago.

The conversation covers agent orchestration, the BMAD Method, agent scorecards, governance frameworks, the future of Scrum, and what AI means for people who have spent years honing their craft.

Whether you’re leading AI adoption, running agile teams or figuring out where you fit in an AI-first workplace, this episode is a practical look at agentic transformation as it’s happening.

]]> No The AI Velocity Gap Is Killing Your Productivity. Here’s How to Close It 10 10 The AI Velocity Gap Is Killing Your Productivity. Here’s How to Close It full 80de60ff-5ae4-48f5-b684-b22caa90d203 https://share.transistor.fm/s/29cf6ab1 In this episode of How We Agent, Ani sits down with Joel Martin, Chief Research Officer at HFS Research. Joel has spent nearly three decades in tech, with stints at IDC, Microsoft and TechInsights, and has led teams across North America, India, the UK and the Middle East.

Joel explains how HFS went from stacks of PDFs to a live, queryable knowledge engine that customers can plug straight into their own systems. He also shares why subscription-based research is dead and what founders and enterprise leaders should focus on as AI changes every three months.

The conversation covers enterprise AI adoption, the AI velocity gap, services as software, the headless future of work, AI risk and sovereignty, and the 4 Ps framework for getting AI into production.

Whether you’re building an AI startup, leading enterprise transformation or managing teams through the AI shift, this episode gives you a research-backed view of where enterprise AI is heading.

]]> In this episode of How We Agent, Ani sits down with Joel Martin, Chief Research Officer at HFS Research. Joel has spent nearly three decades in tech, with stints at IDC, Microsoft and TechInsights, and has led teams across North America, India, the UK and the Middle East.

Joel explains how HFS went from stacks of PDFs to a live, queryable knowledge engine that customers can plug straight into their own systems. He also shares why subscription-based research is dead and what founders and enterprise leaders should focus on as AI changes every three months.

The conversation covers enterprise AI adoption, the AI velocity gap, services as software, the headless future of work, AI risk and sovereignty, and the 4 Ps framework for getting AI into production.

Whether you’re building an AI startup, leading enterprise transformation or managing teams through the AI shift, this episode gives you a research-backed view of where enterprise AI is heading.

]]> Sat, 10 Oct 2026 20:49:20 -0700 Lyzr AI Watch on YouTube Lyzr AI 2594 In this episode of How We Agent, Ani sits down with Joel Martin, Chief Research Officer at HFS Research. Joel has spent nearly three decades in tech, with stints at IDC, Microsoft and TechInsights, and has led teams across North America, India, the UK and the Middle East.

Joel explains how HFS went from stacks of PDFs to a live, queryable knowledge engine that customers can plug straight into their own systems. He also shares why subscription-based research is dead and what founders and enterprise leaders should focus on as AI changes every three months.

The conversation covers enterprise AI adoption, the AI velocity gap, services as software, the headless future of work, AI risk and sovereignty, and the 4 Ps framework for getting AI into production.

Whether you’re building an AI startup, leading enterprise transformation or managing teams through the AI shift, this episode gives you a research-backed view of where enterprise AI is heading.

]]> No A cardiologist put 16 agents on her cases. Reviews got up to 60% faster. 2 2 A cardiologist put 16 agents on her cases. Reviews got up to 60% faster. full 61a68cd3-653a-4e9c-bfd2-8ebe3a32d68a https://share.transistor.fm/s/008b5521 Dr. Lucia Jewbali, with 15 years in the ICU, frames her tool the way she frames the stethoscope: an instrument that augments one specific clinical sense and in this case, reasoning at the bedside.

LionAIs, built with Lyzr, connects to the hospital EHR and combines symptoms with EKGs and bloodwork the way a clinician actually would.

The design choice that matters is the constraint. Narrow the corpus, cite the source, and the tool becomes something a specialist will put next to a patient.

]]> Dr. Lucia Jewbali, with 15 years in the ICU, frames her tool the way she frames the stethoscope: an instrument that augments one specific clinical sense and in this case, reasoning at the bedside.

LionAIs, built with Lyzr, connects to the hospital EHR and combines symptoms with EKGs and bloodwork the way a clinician actually would.

The design choice that matters is the constraint. Narrow the corpus, cite the source, and the tool becomes something a specialist will put next to a patient.

]]> Thu, 01 Oct 2026 20:49:19 -0700 Lyzr AI Watch on YouTube Lyzr AI 1755 Dr. Lucia Jewbali, with 15 years in the ICU, frames her tool the way she frames the stethoscope: an instrument that augments one specific clinical sense and in this case, reasoning at the bedside.

LionAIs, built with Lyzr, connects to the hospital EHR and combines symptoms with EKGs and bloodwork the way a clinician actually would.

The design choice that matters is the constraint. Narrow the corpus, cite the source, and the tool becomes something a specialist will put next to a patient.

]]> No Anyone can demo an agent. The last 40% is where it breaks. 9 9 Anyone can demo an agent. The last 40% is where it breaks. full 0cb8a059-a9c1-4988-9ecb-539d5c629141 https://share.transistor.fm/s/6fd75727 Swami Chandrasekaran has worked through four generations of AI and leads KPMG's move from experimentation into scaling. To understand agents properly, he built an agent harness from scratch rather than reading about frameworks. His mandate splits three ways: innovate, enable, standardize. Rather than build everything, KPMG assembles an ecosystem, which is why he is unusually direct about what gets a startup through the door: be a journey partner, bring differentiated technology, and have the nerve to let an enterprise actually use the product. The through line is the last 40%. Security, trust, scale and adoption are unglamorous, and they are what decides whether an agent ever leaves the demo environment.

]]> Swami Chandrasekaran has worked through four generations of AI and leads KPMG's move from experimentation into scaling. To understand agents properly, he built an agent harness from scratch rather than reading about frameworks. His mandate splits three ways: innovate, enable, standardize. Rather than build everything, KPMG assembles an ecosystem, which is why he is unusually direct about what gets a startup through the door: be a journey partner, bring differentiated technology, and have the nerve to let an enterprise actually use the product. The through line is the last 40%. Security, trust, scale and adoption are unglamorous, and they are what decides whether an agent ever leaves the demo environment.

]]> Mon, 28 Sep 2026 09:28:20 -0700 Lyzr AI Watch on YouTube Lyzr AI 1352 Swami Chandrasekaran has worked through four generations of AI and leads KPMG's move from experimentation into scaling. To understand agents properly, he built an agent harness from scratch rather than reading about frameworks. His mandate splits three ways: innovate, enable, standardize. Rather than build everything, KPMG assembles an ecosystem, which is why he is unusually direct about what gets a startup through the door: be a journey partner, bring differentiated technology, and have the nerve to let an enterprise actually use the product. The through line is the last 40%. Security, trust, scale and adoption are unglamorous, and they are what decides whether an agent ever leaves the demo environment.

]]> No How a 280,000-person company put 200+ AI agents into production 8 8 How a 280,000-person company put 200+ AI agents into production full 6005afc5-6c4a-496e-8281-307d58672f2a https://share.transistor.fm/s/5d6fc974 Patrick Corcoran leads marketing and external relations at Hitachi Digital Services, and his starting point is that AI is not new here. Machine learning and computer vision have been running inside Hitachi's factories and rail networks for around 25 years. What that bought them is a shorter run-up to the agent wave. HARC Agents is the enterprise framework: pre-built agents, unified observability and centralized control, with 200+ agents already in production and 618 sister companies in a position to test them. The part worth borrowing is where he stops. In the Lisbon rail command center, agents assist and a person still makes the call. Governance, security and observability are treated as the product, not the paperwork.

]]> Patrick Corcoran leads marketing and external relations at Hitachi Digital Services, and his starting point is that AI is not new here. Machine learning and computer vision have been running inside Hitachi's factories and rail networks for around 25 years. What that bought them is a shorter run-up to the agent wave. HARC Agents is the enterprise framework: pre-built agents, unified observability and centralized control, with 200+ agents already in production and 618 sister companies in a position to test them. The part worth borrowing is where he stops. In the Lisbon rail command center, agents assist and a person still makes the call. Governance, security and observability are treated as the product, not the paperwork.

]]> Mon, 28 Sep 2026 09:15:59 -0700 Lyzr AI Watch on YouTube Lyzr AI 1580 Patrick Corcoran leads marketing and external relations at Hitachi Digital Services, and his starting point is that AI is not new here. Machine learning and computer vision have been running inside Hitachi's factories and rail networks for around 25 years. What that bought them is a shorter run-up to the agent wave. HARC Agents is the enterprise framework: pre-built agents, unified observability and centralized control, with 200+ agents already in production and 618 sister companies in a position to test them. The part worth borrowing is where he stops. In the Lisbon rail command center, agents assist and a person still makes the call. Governance, security and observability are treated as the product, not the paperwork.

]]> No Your lab results land before the call. Should AI explain them first? 7 7 Your lab results land before the call. Should AI explain them first? full 581d3043-7342-43ef-84f6-1547191c0f97 https://share.transistor.fm/s/ded93a3c Jean Sachs runs an organisation that reaches two million people a year with breast cancer information, supporting people trying to understand a complex diagnosis. Closing that information gap is exactly what AI should be good at and exactly where a confidently wrong answer does the most damage.

This episode covers how she moves forward regardless: what they started with, what they won't touch yet, and why the first build was internal.

Worth watching if you've had to introduce AI into a room where the sceptics have a point.

]]> Jean Sachs runs an organisation that reaches two million people a year with breast cancer information, supporting people trying to understand a complex diagnosis. Closing that information gap is exactly what AI should be good at and exactly where a confidently wrong answer does the most damage.

This episode covers how she moves forward regardless: what they started with, what they won't touch yet, and why the first build was internal.

Worth watching if you've had to introduce AI into a room where the sceptics have a point.

]]> Mon, 28 Sep 2026 09:05:01 -0700 Lyzr AI Watch on YouTube Lyzr AI 931 Jean Sachs runs an organisation that reaches two million people a year with breast cancer information, supporting people trying to understand a complex diagnosis. Closing that information gap is exactly what AI should be good at and exactly where a confidently wrong answer does the most damage.

This episode covers how she moves forward regardless: what they started with, what they won't touch yet, and why the first build was internal.

Worth watching if you've had to introduce AI into a room where the sceptics have a point.

]]> No A $31M agency found 360 wasted hours a month. Then it built 12 internal tools. 6 6 A $31M agency found 360 wasted hours a month. Then it built 12 internal tools. full bfa97b16-8ee2-4940-84a5-aa7d8e23f73d https://share.transistor.fm/s/b6d793e2 Ryan Sprance co-founded Awestruck, which scaled from $106K in 2019 to $31M in 2025 without paid marketing. Along the way they found 360 hours a month going into manually formatting client reports and twelve tools worth building.

A budget pacing tool that outperformed the commercial product it replaced. A reputation platform for 150+ clients, grounded in each brand's own voice and local facts. A commission app that removed 20 hours of monthly Excel work.

]]> Ryan Sprance co-founded Awestruck, which scaled from $106K in 2019 to $31M in 2025 without paid marketing. Along the way they found 360 hours a month going into manually formatting client reports and twelve tools worth building.

A budget pacing tool that outperformed the commercial product it replaced. A reputation platform for 150+ clients, grounded in each brand's own voice and local facts. A commission app that removed 20 hours of monthly Excel work.

]]> Mon, 28 Sep 2026 08:44:18 -0700 Lyzr AI Watch on YouTube Lyzr AI 1749 Ryan Sprance co-founded Awestruck, which scaled from $106K in 2019 to $31M in 2025 without paid marketing. Along the way they found 360 hours a month going into manually formatting client reports and twelve tools worth building.

A budget pacing tool that outperformed the commercial product it replaced. A reputation platform for 150+ clients, grounded in each brand's own voice and local facts. A commission app that removed 20 hours of monthly Excel work.

]]> No Your company is stuck in the PoC Paradox. Here’s how to get out. 5 5 Your company is stuck in the PoC Paradox. Here’s how to get out. full 3a9be153-fcf7-4612-8493-5022e8463fe3 https://share.transistor.fm/s/ed946a17 Ronan Langford's argument is that many enterprise AI programmes are stuck in what he calls the PoC Paradox: a steady stream of pilots that make existing processes marginally faster, while nobody at the top can describe what the company looks like on the other side.

The argument here is to shift the emphasis: real-time benchmarking, simulations where autonomous avatars of regulators and unions stress-test decisions against supply chain and geopolitical shocks, and workflow redesign on sovereign-ready infrastructure.

Worth a listen if your AI strategy is currently a spreadsheet of pilots nobody can connect to a future state.

]]> Ronan Langford's argument is that many enterprise AI programmes are stuck in what he calls the PoC Paradox: a steady stream of pilots that make existing processes marginally faster, while nobody at the top can describe what the company looks like on the other side.

The argument here is to shift the emphasis: real-time benchmarking, simulations where autonomous avatars of regulators and unions stress-test decisions against supply chain and geopolitical shocks, and workflow redesign on sovereign-ready infrastructure.

Worth a listen if your AI strategy is currently a spreadsheet of pilots nobody can connect to a future state.

]]> Mon, 28 Sep 2026 03:40:57 -0700 Lyzr AI Watch on YouTube Lyzr AI 1414 Ronan Langford's argument is that many enterprise AI programmes are stuck in what he calls the PoC Paradox: a steady stream of pilots that make existing processes marginally faster, while nobody at the top can describe what the company looks like on the other side.

The argument here is to shift the emphasis: real-time benchmarking, simulations where autonomous avatars of regulators and unions stress-test decisions against supply chain and geopolitical shocks, and workflow redesign on sovereign-ready infrastructure.

Worth a listen if your AI strategy is currently a spreadsheet of pilots nobody can connect to a future state.

]]> No Solving agent memory at the database layer 4 4 Solving agent memory at the database layer full 3ba829a2-d23f-4632-8d1a-0b88bfc6a463 https://share.transistor.fm/s/b602b35b Most teams building agents run into the same problem: each agent accumulates its own private memory, and the organisation quietly acquires a dozen new information silos.

This episode is about addressing that at the database layer rather than the application layer. Yugabyte's new product, Meiko, gives agents shared memory and knowledge, so context compounds across agents.

The more interesting part is what they've built on it internally worth a listen if your agents keep re-learning what the last one already knew.

]]> Most teams building agents run into the same problem: each agent accumulates its own private memory, and the organisation quietly acquires a dozen new information silos.

This episode is about addressing that at the database layer rather than the application layer. Yugabyte's new product, Meiko, gives agents shared memory and knowledge, so context compounds across agents.

The more interesting part is what they've built on it internally worth a listen if your agents keep re-learning what the last one already knew.

]]> Mon, 28 Sep 2026 02:18:36 -0700 Lyzr AI Watch on YouTube Lyzr AI 2024 Most teams building agents run into the same problem: each agent accumulates its own private memory, and the organisation quietly acquires a dozen new information silos.

This episode is about addressing that at the database layer rather than the application layer. Yugabyte's new product, Meiko, gives agents shared memory and knowledge, so context compounds across agents.

The more interesting part is what they've built on it internally worth a listen if your agents keep re-learning what the last one already knew.

]]> No How a 500-person strategy firm crushed an 18-month delivery cycle into weeks 3 3 How a 500-person strategy firm crushed an 18-month delivery cycle into weeks full bd2ebd57-f0a8-4356-b211-bf10a057a5e3 https://share.transistor.fm/s/97802c68 Chan Suh leads digital at Prophet, whose client list runs Google, Netflix, Amazon and Marriott. The firm's core hasn't changed, but GenAI has collapsed a delivery cycle of six months research, six of strategy and six to launch into something closer to weeks.

Their answer is Maia, a multi-agent OS built with Lyzr and structured like an internal app store, with agents carrying their proprietary consumer survey and 30 years of activation data.

The shift in what clients ask for is the real headline: not a point solution, but a workbench they can run a process on.

]]> Chan Suh leads digital at Prophet, whose client list runs Google, Netflix, Amazon and Marriott. The firm's core hasn't changed, but GenAI has collapsed a delivery cycle of six months research, six of strategy and six to launch into something closer to weeks.

Their answer is Maia, a multi-agent OS built with Lyzr and structured like an internal app store, with agents carrying their proprietary consumer survey and 30 years of activation data.

The shift in what clients ask for is the real headline: not a point solution, but a workbench they can run a process on.

]]> Sun, 27 Sep 2026 23:32:13 -0700 Lyzr AI Watch on YouTube Lyzr AI 1778 Chan Suh leads digital at Prophet, whose client list runs Google, Netflix, Amazon and Marriott. The firm's core hasn't changed, but GenAI has collapsed a delivery cycle of six months research, six of strategy and six to launch into something closer to weeks.

Their answer is Maia, a multi-agent OS built with Lyzr and structured like an internal app store, with agents carrying their proprietary consumer survey and 30 years of activation data.

The shift in what clients ask for is the real headline: not a point solution, but a workbench they can run a process on.

]]> No How a 10,000-person IT firm made test prep up to 40% faster with AI agents 1 1 How a 10,000-person IT firm made test prep up to 40% faster with AI agents full 7518c933-ee2d-4dde-8c2e-c73e81eaad83 https://share.transistor.fm/s/14aeb8b5 Devanathan Desikan runs Movate's momentum and innovation division, and made a call most teams get wrong: rather than spend two years building a platform, orchestrate on one.

They built on Lyzr and shipped digital twins of roles - a coding twin, a QA twin - delivered as plug-ins inside Jira, VS Code, Slack, Teams and ServiceNow, so nobody has to context-switch to use them.

The part worth borrowing is downstream: human-agent hybrid delivery let them move to outcome-based pricing, which meant retraining legal and pricing teams to underwrite what an agent commits to in an SOW.

]]> Devanathan Desikan runs Movate's momentum and innovation division, and made a call most teams get wrong: rather than spend two years building a platform, orchestrate on one.

They built on Lyzr and shipped digital twins of roles - a coding twin, a QA twin - delivered as plug-ins inside Jira, VS Code, Slack, Teams and ServiceNow, so nobody has to context-switch to use them.

The part worth borrowing is downstream: human-agent hybrid delivery let them move to outcome-based pricing, which meant retraining legal and pricing teams to underwrite what an agent commits to in an SOW.

]]> Fri, 25 Sep 2026 03:09:47 -0700 Lyzr AI Watch on YouTube Lyzr AI 2181 Devanathan Desikan runs Movate's momentum and innovation division, and made a call most teams get wrong: rather than spend two years building a platform, orchestrate on one.

They built on Lyzr and shipped digital twins of roles - a coding twin, a QA twin - delivered as plug-ins inside Jira, VS Code, Slack, Teams and ServiceNow, so nobody has to context-switch to use them.

The part worth borrowing is downstream: human-agent hybrid delivery let them move to outcome-based pricing, which meant retraining legal and pricing teams to underwrite what an agent commits to in an SOW.

]]> No