Shift AI with Boaz Ashkenazy

In this episode of Shift AI, Steve Tarcza, leader of StoreGen at Amazon Stores, joins host Boaz Ashkenazy for a wide-ranging conversation on what it actually took to make Amazon's developer teams multiple times faster with AI.At the start of last year, Steve's team set a goal that sounded almost reckless: not a 10 or 20 percent improvement, but 3x. Steve admits he was skeptical it could be done at all. What his team found along the way, buried in an analysis of how developers actually spend their time, forced them to rethink the entire product development lifecycle rather than just handing engineers a faster tool.This one's for engineering leaders, VPs of product, and technical program managers wrestling with how to actually operationalize AI gains rather than just chase percentage-point productivity boosts.Chapters[00:01] Welcome and Steve's path to leading AI work at Amazon Stores[02:39] Steve's first job: fixing school networks in upstate New York[04:53] The 3x goal: betting on better models and rethinking developer work[07:05] Building "AI Teammate" for autonomous team workflows[08:22] Problem solvers, not code writers: staying customer-first[11:15] Junior vs. senior developers in an agent-heavy org[13:49] What models do well, and where they still fall short[16:17] Spec-driven development in action: the "Add to Delivery" button[18:31] Inside Kiro: Amazon's spec-driven development tool[21:01] Culture over tools: the harder half of going AI-native[24:18] Layoffs, job security, and why Steve stays optimistic[29:51] Beyond developers: PMs, DevOps, and the full product lifecycle[32:55] Closing two words: optimism and innovationConnect with Steve TarczaLinkedIn: https://www.linkedin.com/in/steven-tarcza-ii-8b22936b/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Colleen Kozak, Chief Transformation Officer of Dynatrace, joins host Boaz Ashkenazy for a wide-ranging conversation on what's actually slowing down agentic AI adoption inside the enterprise.Everyone assumes the blocker is cost. Colleen sees something different playing out across her customers, from token-maxing tech companies to cautious, regulated enterprises: the real hesitation isn't the bill, it's not knowing whether the agent got it right. She walks through what that gap looks like in practice, and what happens once companies decide they're ready to hand agents the keys to take action on their own.This one's for CTOs, platform engineers, security leaders, and anyone driving AI strategy inside a large organization who's trying to figure out how to move from pilot to production without losing the ability to see what their agents are actually doing.Chapters[00:01] Welcome and introductions[00:32] From mechanical engineering to Chief Transformation Officer[01:54] The first paycheck: babysitting[02:42] Inside Dynatrace: Grail, Smartscape, and Dynatrace Intelligence[06:03] From copilots to full agentic systems[07:03] Why trust, not maturity, is the real divide between companies[08:32] Building trust into agents at runtime, and securing a world with more agents than employees[12:42] Splitting the work: human review, automated review, and internal vs. customer-built agents[14:15] Tokenomics and choosing the right model for the right job[16:52] What dogfooding AI internally revealed, and getting SaaS vendors to open their telemetry[21:00] Sovereign cloud, geopolitics, and the return of on-prem[23:27] Two words for the future, the jobs question, and hiring at DynatraceConnect with Colleen KozakLinkedIn: https://www.linkedin.com/in/colleen-kozakDynatrace careers: dynatrace.com Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Mick Costigan, Vice President of Salesforce Futures at Salesforce, joins host Boaz Ashkenazy live from Dreamforce for a wide-ranging conversation on how AI is reshaping the way work gets done, and who does it.Mick's team are all Claude coders now, and they've noticed something strange. Each person goes deep with their AI, surfaces with an 8-page document, and finds everyone else has tunneled off somewhere else with one of their own. Coding figured out how to bring that work back together. Mick isn't sure the rest of work can, and he has a 2x2 that suggests which parts of your job are about to be pulled apart.CIOs, CTOs, strategy and transformation leaders, and anyone designing teams and roles for the agentic era will come away with a sharper way to think about which work stays human.Chapters[00:00] Live from Dreamforce: what futures work is and how Salesforce Futures operates[05:15] An off-license in Ireland and a bouncer job across from Wrigley Field[07:05] Harnesses before anyone called them harnesses[10:25] Spotting the headless platform back in 2016[13:00] Opus 4.5 and the team's Claude Code moment[15:50] Tunneling and the 8-page document problem[19:15] From work from anywhere to intentional in-person time[21:10] The verifiability and data 2x2 for unbundling work[24:50] Slop, efficiency, and why we won't all become Rick Rubin[26:55] Finding the human part of your own job[28:20] Bundling, unbundling, and the radiologist lesson[31:05] Futures Magazine and how to reach the teamConnect with Mick CostiganLinkedIn: https://www.linkedin.com/in/mcostigan/Futures Magazine: salesforce.com/news/futuresEmail the Futures team: [email protected] with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Mario Rodriguez, Chief Product Officer of GitHub, joins host Boaz Ashkenazy for a wide-ranging conversation on what GitHub is becoming now that humans and AI agents build software side by side.Mario shares a number from inside GitHub's own Copilot data that cuts against the idea of a single dominant AI model, and explains why he thinks the real competition isn't happening at the model layer at all. He also lays out how GitHub is rethinking its surfaces, from Agent HQ to a tool called Spark, around a much bigger bet on where developer collaboration is headed next.This episode is for CTOs, VPs of engineering, platform and DevEx leads, and any software engineer trying to figure out where their own skills fit as more of the codebase gets written by agents.Chapters[00:00] Welcome and introducing Mario Rodriguez[00:29] From a Cuban restaurant busboy to electrical engineering to Perl[03:11] Landing at Microsoft, then GitHub after the 2018 acquisition[03:58] Redefining GitHub beyond repos: the agent-native engineering system[07:31] Staying true to developers and going model-agnostic[09:06] The Copilot usage data on model choice[10:27] Harnesses, and why the fixation on any one model is fading[13:49] Agent HQ, the GitHub Copilot app, and canvases explained[16:29] Chronicle and the continuous learning loop[18:10] Spark: lowering the floor and raising the ceiling for builders[21:35] What AI means for new versus experienced software engineers[29:09] The closing two words: fluid creativityConnect with Mario RodriguezLinkedIn: https://www.linkedin.com/in/mariorodriguez3X: https://x.com/mariorod1Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Emrecan Dogan, Head of Product of Glean, joins host Boaz Ashkenazy for a wide-ranging conversation on what it actually takes to give enterprise AI real organizational context.Emrecan has convinced countless CIOs and CEOs to stop chasing a data cleanup project that he says will never finish. Instead he makes the case for leaving the mess exactly where it is and solving the problem somewhere else entirely, a position that runs against nearly everything companies think they need to do before they can "get onto AI." He also lays out a theory of why knowledge workers spend half their AI time just re-teaching context, and what it would take to get that number to zero.This one is for CIOs, chief AI officers, heads of product, and platform and data leaders who are being told to fix their data before they can move on AI, and who want a second opinion.Chapters[00:00] Welcome and introduction[00:33] Emrecan's path to Glean: entrepreneur, LinkedIn, Stripe, and a warning from a VC[02:36] First paid job: fixing bikes in Turkey[04:19] What Glean actually does: the work AI platform explained[06:53] The onboarding moment of truth and losing Glean when you leave[09:40] Why organizational data, not model choice, is the real moat[10:47] Seven years of infrastructure work before the GPT moment[13:00] The pipe dream of cleaning up your data stack first[15:36] "Bot sitting": the hidden cost of teaching context to AI every day[17:59] Why picking a single model provider is one of the worst bets you can make[23:37] Token yield, marginal cost intelligence, and the "half my budget is wasted" problem[30:36] Assistants versus agents: a framework for when each one applies[36:31] What's coming next: durable, multiplayer artifacts and proactive AI[40:34] Closing question: the future of work in two wordsConnect with Emrecan DoganLinkedIn: https://www.linkedin.com/in/emrecandogan/Glean blog: glean.comConnect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Paul Mikesell, CEO of Carbon Robotics, joins host Boaz Ashkenazy for a wide-ranging conversation on how AI, lasers, and autonomy are replacing chemical weed control on farms.Carbon Robotics built a foundation model out of 150 million plant images, and Paul explains what happens when you show it a weed it has never encountered before. There's no retraining involved, and the result is something closer to a machine that understands what a plant is rather than one that's just memorized a dataset. What that actually looks like in the field, and why it took years of accumulated data to get there, is worth hearing him walk through directly.This episode is for CTOs and engineering leaders working on physical AI and robotics, agtech investors and founders, and anyone building computer vision systems that need to generalize beyond their training data.Chapters[00:01] Welcome to the show[00:31] From self-driving cars at Uber to founding Carbon Robotics[02:54] The farmer's real problem: weeds, chemicals, and health risks[04:05] Paper routes, Nintendo, and a Commodore 64: Paul's path into computing[07:59] Laser Weeder by the numbers: 15 countries and $100M+ in revenue[10:04] Inside the machine: light brighter than the sun and real-time targeting[13:33] The tractor driver bottleneck and the move to autonomy[14:55] Center pivots and near-misses: what farms teach robots that roads don't[18:40] The real moat: people, data, and years in the field[20:31] The Large Plant Model: recognizing a weed it's never seen before[24:23] Physical AI and why data is becoming the new moat[26:57] Two words for the future: autonomy and healthConnect with Paul MikesellLinkedIn: https://www.linkedin.com/in/paul-mikesell-4b63a9/Company: carbonrobotics.comConnect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Praerit Garg, CEO of One Identity, joins host Boaz Ashkenazy for a wide-ranging conversation on what happens to enterprise security when AI agents start outnumbering the humans they work alongside.Praerit has spent his career on both sides of this problem, from building Active Directory at Microsoft to running identity at AWS, and he says the thing keeping him up at night isn't a new category of threat at all. It's an old one moving at a speed nobody has built the guardrails for yet, and he points to a very recent, very public example of exactly how fast it can get away from you.This one's for CISOs, CTOs, platform and security engineers, and any founder scaling a company that's already handing real work to autonomous agents.Recorded Live at Baker Tily during Seattle Tech Week 2026. Thank you to Stifel Bank and Wison Sonsini for sponsoring.Chapters[00:00] Welcome back — PG's journey from Smartsheet to CEO of One Identity[01:58] What One Identity does: identity governance, explained[03:41] How the firewall evaporated and identity became the new perimeter[04:24] Rethinking identity for a world full of AI agents[07:14] Why agent identities are harder to secure than human ones[08:00] Breaking down the OpenAI and Hugging Face agent escape[09:03] Least privilege: the hardest idea in security to actually pull off[11:19] What keeps PG up at night as agents start to outnumber people[15:19] Sovereign AI, air-gapped models, and the return of on-prem[18:18] Scaling Smartsheet fast, and why flexibility beats architecture bets[20:20] What CEOs should be asking security vendors and usually aren't[22:37] The next five years: agents outnumbering humans and AI writing the codeConnect with Praerit GargLinkedIn: https://www.linkedin.com/in/praerit-garg/Company: One Identity (oneidentity.com)Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Sabina Anja, Chief Technologist at VMware by Broadcom, joins host Boaz Ashkenazy for a wide-ranging conversation on why private, flexible infrastructure is becoming the foundation enterprises need for the agentic era.Sabina makes the case that most infrastructure and security thinking was built for a world where humans approve every step, and that world is already gone. An assistant waits for you. An agent, in her words, gets set loose and just goes. So what happens when nobody notices an agent doing something it was technically allowed to do, but shouldn't have? Sabina has a way of thinking about that question that most infrastructure teams haven't caught up to yet.This episode is for CIOs, CTOs, VPs of infrastructure, platform engineers, and security leaders who are trying to figure out what their environments need to look like before agents are running unsupervised inside them.Chapters[00:00] Welcome and introducing Sabina Anja[00:31] From Belgium to self-taught programmer: Sabina's first jobs[04:29] Why programming hygiene still matters with Cursor and Claude Code[06:24] Virtualization then and now: from vCPUs to vGPUs[08:52] What businesses are really asking for as AI costs spike[10:46] Inside NVMe tiering and the memory crunch[13:28] Private AI and the return of sovereign infrastructure[15:43] Data ownership, geopolitics, and the new value of stolen IP[17:48] Open source, small language models, and fit-for-purpose compute[20:59] Advice for CIOs: build flexible foundations, not two-year projects[24:40] Agents vs. assistants: why blast radius changes everything[27:26] Agentic security, guardrails, and the two words: platform matters, earned trustConnect with Sabina AnjaLinkedIn: https://www.linkedin.com/in/sabinaanja/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Manos, CEO of Umi, Patrick Thompson, CEO of Clarify, Brian Hall, CMO of Mistral AI, and Ben Gaffney, Deputy General Counsel at OpenAI, join host Boaz Ashkenazy for a live panel recorded at Seattle Tech Week on who actually owns intelligence in the enterprise AI era.One panelist argues that any enterprise still treating a frontier model as its core intelligence layer is renting something it should own, and predicts that in two years we'll look back at CTOs defending that approach the way we look back at driving a Ferrari to the grocery store. Another panelist, sitting inside one of the most closely watched policy fights in AI right now, explains why the debate over open source models and national security is getting a lot less theoretical, and a lot more real, by the month.This one is for CTOs and CIOs deciding whether to build or rent their AI stack, product leaders at vertical AI startups thinking about fine-tuning their own models, and anyone tracking the open source AI security and policy debate.Chapters[00:00] Welcome and thanks to sponsors JP Morgan and Ascend[01:30] Introducing the panel: Manos, Patrick, Brian, and Ben[03:54] From foundation model hype to vertical AI, what actually changed[07:37] How Clarify balances owning the system of record with using frontier models[09:44] Rising model bills, local models, and the push toward open weights[11:30] Mistral AI, sovereign AI, and why owning your intelligence matters[14:32] Data retention, training, and what the privacy debate is really about[19:10] Chinese open models, national security, and the safety debate[26:18] Why fine-tuning beats prompting for real vertical AI companies[30:43] What enterprises actually want from foundation models right now[35:35] What CIOs and CTOs will laugh about in two years[44:47] The hundred million dollar question: where the panel would invest[51:44] Advice for a 22-year-old about to spend ten years building something[53:31] What each panelist is most excited about in AI's futureConnect with the PanelistsManos (Umi) - https://www.linkedin.com/in/koukoumidis/Patrick Thompson (Clarify) - https://www.linkedin.com/in/patrickt010/Brian Hall (Mistral AI) - https://www.linkedin.com/in/brhall/Ben Gaffney (OpenAI) - https://www.linkedin.com/in/bengaffney/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]

In this episode of Shift AI, Zohar Alon, CEO and Co-Founder of Newcore, joins host Boaz Ashkenazy live from Black Hat 2026 for a conversation on why identity, not infrastructure, is the real fault line in agentic AI.Zohar has spent thirty years watching the same problem resurface in a new costume, from VPNs to IDPs to now agents that can act on your behalf for hours at a time. He describes a system where a single trusted identity point can unlock hundreds of connected apps, and where an AI agent chasing a vague instruction might decide, on its own, to read six months of email or start testing messages against real people to get results. What happens when you can't fully predict what the agent will try next, and the guardrails have to be built for that uncertainty rather than against it, is the question Zohar has built a company around.This one is for CISOs, identity and access management leads, platform engineers building with autonomous agents, and founders working in enterprise security who need to think past service accounts and static permissions.Chapters[00:00] Welcome to Shift AI, live from Black Hat 2026[00:25] Thirty years in cyber, from Check Point employee 55 to founder[01:30] Founding Dome9 and convincing the world the cloud needed securing[02:25] The identity problem that never got solved, from VPNs to modern IDPs[04:50] Building Newcore: one identity fabric for humans and agents[06:15] Why a single IDP becomes a single point of catastrophic risk[07:13] Pilot school, electronics class, and Zohar's path into Check Point[09:36] Mentoring the next generation of Israeli cyber founders[10:45] Why an AI agent isn't a service account[11:59] Inside an agent's "creative" pursuit of a goal[14:10] Human-in-the-loop as protection, not friction[16:35] The closing two words: unknown unknownConnect with Zohar AlonLinkedIn: https://www.linkedin.com/in/zoharalon/Company: Newcore -https://newcore.com/Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: [email protected]