Shift AI

Boaz Ashkenazy
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Shift AI explores how AI and ML is changing the way that we work in the digital age. The show's creator Boaz Ashkenazy interviews thought leaders who are redefining how businesses and employees will be impacted by emerging technology today and in the future | Visit shiftaipodcast.com

  1. 6 天前

    Governing Agent-to-Agent Trust at Scale with MuleSoft from Salesforce SVP and GM Andrew Comstock

    In this episode of Shift AI, Andrew Comstock, Senior Vice President and General Manager of MuleSoft from Salesforce, joins host Boaz Ashkenazy for a wide-ranging conversation on governing, securing, and controlling the cost of agentic AI at enterprise scale. The conversation covers how MuleSoft's API-led integration playbook, built during the on-prem-to-cloud shift, is now extending into what the company calls Agent Fabric — bringing governance and controlled connectivity to agent-to-agent communication. Andrew walks through a concrete example of how two internal agents trusting each other by default can leak a customer's order history, and digs into prompt injection, impersonation, and why the security industry's people-focused compliance frameworks now have to account for reasoning software, not just people. He and Boaz also get into token economics, LLM gateways, intent-based routing between local and cloud models, and the emerging trend of companies repatriating some AI workloads on-premise. This episode is essential listening for CTOs, CISOs, platform and integration engineers, and IT and product leaders responsible for governing AI spend and agent security as their organizations scale past pilot projects into production. Chapters [00:01] Andrew Comstock's path to MuleSoft [02:06] First job: tax returns and trumpet reeds [03:21] What MuleSoft does and its extension into Agent Fabric [05:29] From consumer chatbots to enterprise agent connectors [07:22] Governance and security at the enterprise level [10:36] A real example: how two agents can leak an order number [13:45] Connect AI 2025 vs. 2026 — a year of night-and-day change [16:28] Mythos, Fable, and preparing for the LLM that breaks your systems [18:11] Token economics and the true cost of enterprise AI [20:38] The "AI savior" pattern vs. applying IT discipline to AI [22:40] Hybrid deployments, local models, and intent-based routing [27:13] Why AI's uneven acceleration makes prioritization more valuable [28:57] The two-word answer: "coming soon" Connect with Andrew Comstock LinkedIn: https://www.linkedin.com/in/andrewcomstock/ Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

  2. 7月25日

    Teaching Discernment in the Age of AI and Higher Education with UW Vice Provost for AI Noah Smith

    In this episode of Shift AI, Noah Smith, Vice Provost for AI at the University of Washington and Senior Director of NLP Research at the Allen Institute for AI, joins host Boaz Ashkenazy for a wide ranging conversation on how universities are preparing for a workplace increasingly run by AI agents. Noah's path wound from a PhD at Johns Hopkins to a tenured professorship at Carnegie Mellon, until a call from UW pulled him west in 2015 to help build out its natural language processing faculty. A few years later he took on a second role leading a research team at the Allen Institute for AI, and this past November added a newly created role as UW's first Vice Provost for AI. The conversation covers how faculty across UW are experimenting with AI in the classroom, from an interactive logic textbook in the philosophy department to new AI literacy courses, and digs into OLMo, the fully open language model project Noah leads at Ai2, unpacking why releasing the weights, code, and training data together, not just an API, matters for regulated industries, universities, and anyone who wants to retrain a model rather than just prompt it. Noah lays out a scenario where 80 percent of entry level work gets done by autonomous agents and argues the skill universities need to double down on is not AI literacy so much as discernment, the ability to unwrap a problem and figure out what questions to ask. This one is for university administrators, provosts, and faculty grappling with AI policy, as well as founders and engineers building on open source models, and anyone curious how a major research university is trying to get ahead of the agentic era instead of just reacting to it. Chapters [00:05] Welcome to Shift AI, live from UW's Foster School of Business [03:44] Noah's path from Carnegie Mellon to UW's Vice Provost for AI [06:08] Bagging groceries: Noah's first paid job [08:11] Six months in: what surprised Noah most about the role [09:22] How AI is reshaping teaching and pedagogy at UW [11:33] Preparing students for a world where agents do 80 percent of the work [14:08] Inside the Allen Institute for AI and the origins of OLMo [15:52] What "fully open" really means for language models [17:49] Specialized models versus general-purpose models for regulated industries [19:47] AI governance, security, and UW's new governance committee [24:35] The future of work in two words: human agency Connect with Noah Smith LinkedIn: https://www.linkedin.com/in/noah-smith-0322511a4/ Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

  3. 7月16日

    The End of DevOps and the Rise of Autonomous Cloud with Hyphen AI CEO Jared Wray

    In this episode of Shift AI, Jared Wray, CEO and co-founder of Hyphen, joins host Boaz Ashkenazy for a wide-ranging conversation on how AI is poised to eliminate the complexity of cloud infrastructure and the DevOps role entirely. Jared shares his unconventional career journey from growing up in a small town in Idaho, where technology barely existed, to washing dishes at 15, teaching himself programming at the local ISP, and eventually founding five startups across cloud computing, energy tech, and developer infrastructure. From bootstrapping Tier 3 (acquired by CenturyLink) to co-founding Palmetto, now one of the largest energy lenders in the nation, Jared's path has been defined by a passion for solving infrastructure problems. The conversation dives deep into why DevOps has become painfully complex, with developers needing to glue together seven to thirteen different services just to deploy a single application across providers like AWS, Google Cloud, and Cloudflare. Jared explains how Hyphen is using AI to abstract away this complexity by asking developers only for business rules like uptime requirements and performance needs, then letting the AI determine the right architecture, deploy it, and operate it autonomously. Boaz and Jared explore why tools like Claude Code and other coding agents still cannot handle the full deployment lifecycle, what it would look like if AI agents replaced PagerDuty by calling you during an outage with a diagnosis and recommendation, and why the future of infrastructure is an autonomous cloud where humans are decision makers and agents handle everything else. The episode closes with a forward-looking discussion on agent-only companies, the death of cloud certifications, and why Jared believes DevOps was a good idea that we ran too long. This episode is essential listening for CTOs, platform engineers, and startup founders who want to understand how AI is moving beyond writing code to fundamentally transforming how software is deployed, operated, and scaled. Chapters [00:00] From Pocatello to Five Startups: Jared's Career Journey [02:49] Building Fonz, Co-founding Palmetto, and Finding Passion in Infrastructure [06:05] Why AI Led Jared Back to Infrastructure with Hyphen [07:05] First Job as a Dishwasher and Breaking Into Tech [08:46] What Is DevOps and Why Does It Exist [10:49] Why Cloud Infrastructure Has Become So Painfully Complex [12:36] How AI Can Apply Best Practices Without Reinventing the Wheel [14:35] The Hyphen Developer Experience: Business Rules Over Architecture [17:14] Why Claude Code and Coding Agents Cannot Solve Infrastructure Yet [20:26] The Full Context Problem: Operating Across Multiple Cloud Providers [23:07] Autonomous Cloud: When Agents Talk to Agents [24:17] Replacing PagerDuty: AI Agents That Call You During Outages [28:47] March Madness, Live Streaming, and Why Five Minutes Feels Like a Lifetime [30:59] Two Words for the Future of Work: Autonomous Cloud [33:20] Agent-Only Companies and Why Humans Will Be CEOs [35:12] DevOps Was a Good Idea We Ran Too Long [35:41] What Is Next for Hyphen Connect with Jared Wray LinkedIn: https://www.linkedin.com/in/jaredwray/ Email: jw@hyphen.ai Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

  4. 7月7日

    The Case for Deterministic AI with Logical Intelligence CSO Patrick Hillmann

    In this episode of Shift AI, Patrick Hillmann, Chief Strategy Officer at Logical Intelligence, joins host Boaz Ashkenazy for a conversation about why the next era of AI cannot be built on probability alone. Patrick shares his unconventional path into AI, from crisis communications and cybersecurity work at Edelman and General Electric, to steering Binance through its most turbulent years and a major DOJ settlement. At Logical Intelligence, Patrick now works alongside Yann LeCun, a Fields Medalist, and engineers from Meta, Google, and Cruise to build deterministic, energy-based reasoning models. Patrick explains why LLMs behave like a confident intern, fast and articulate, but wrong in ways you only catch if you already know the answer, and why critical systems like power grids, hospitals, and self-driving cars need a layer of certainty that probabilistic systems cannot provide. He and Boaz dig into Logical Intelligence's benchmark results, including a 98% score on the notoriously difficult Putnam math competition, and a public Sudoku test where their energy-based model, Kona, beat every major LLM combined while running on a fraction of the compute cost. This episode is essential listening for CTOs, technical leaders, and anyone trying to understand what comes after the current generation of large language models. Chapters [00:00] Patrick's Improbable Path: From Grad School to the Front Lines of a Geopolitical Crisis [02:43] From Binance to Chief Strategy Officer at Logical Intelligence [02:54] The First Paid Job: Unloading UPS Trucks in 100 Degree Heat [04:31] The UPS Lesson That Still Shapes How He Thinks About Work [04:47] Why LLMs Are Confident Guessing Machines, Not Truth Machines [07:14] The Team Behind Logical Intelligence: A Fields Medalist, Yann LeCun, and Math Olympiad Engineers [08:55] Is Logical Intelligence Betting Against LLMs? [10:32] The AI Sandwich: Where LLMs, Reasoning Layers, and World Models Fit [12:36] The Putnam Benchmark and Why Formal Proofs Don't Get Partial Credit [15:44] What Is an Energy-Based Model, Really? [19:54] Eve Badia's 15-Year Path to the Energy-Based Reasoning Model [22:04] Formal Verification and the Future of Secure Code Generation [23:33] When Unverified Code Fails: The Molson Coors Ransomware Story [25:39] Why AI Coding Tools Create Rat's Nests Engineers Can't Debug [28:53] The Sudoku Test: 98% Accuracy for $4 vs $14,000 for the Leading LLMs [31:13] ByteDance, China, and the Race for Formal Methods [33:42] Two Words for the Future of AI: Chaotic Determinism [37:12] Where to Follow Logical Intelligence and Founder Eve Badia Connect with Patrick Hillmann LinkedIn: https://www.linkedin.com/in/crisiscommunications Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

  5. 6月26日

    AI, Security, and the Courage to Reinvent with Smartsheet CTO Cynthia Tee

    In this episode of the Shift AI Podcast, Cynthia Tee, former CTO of Smartsheet, joins host Boaz Ashkenazy for a wide-ranging conversation on what it really takes to integrate AI at enterprise scale responsibly, securely, and in a way that earns lasting customer trust. Cynthia shares her unconventional journey from growing up in Manila and working her first job at a library at age 12, to earning a computer science degree from MIT, building her career at Microsoft, running Ada Developers Academy, and ultimately leading engineering at Smartsheet through one of its most consequential chapters, including the company's transition from public to private and the rollout of its first generation of AI-powered features. The conversation dives deep into how Smartsheet approached AI integration: using generative AI to simplify formula generation and data visualization, being deliberate about what information was and wasn't sent to LLMs, and communicating transparently with enterprise customers who needed to trust the system before they would adopt it. Cynthia explains why trust, governance, and data classification aren't afterthoughts, they're the foundation that makes AI deployment possible at scale. Boaz and Cynthia explore the emerging role of MCP in connecting LLMs like Claude to applications like Smartsheet, translating user intent into real-world action across complex workflows. They also get into what SaaS executives often underestimate: that shipping AI features is the easy part, and evolving the rest of the organization, pricing, enablement, customer support, and role definitions is where companies get stuck. The discussion turns to the next generation of workers and the genuine tension young people face between learning a craft and leaning on AI to accelerate it. Cynthia shares a perspective on hustle, curiosity, and what it looks like when someone who's never written a line of code builds an inventory system for vintage clothing because a tool like Claude made it possible.This episode is essential listening for CTOs, engineering leaders, and product executives who want to understand what responsible AI deployment actually looks like inside a company operating at scale.

  6. 6月16日

    Building the AI-First City with San Jose Chief Innovation Officer Stephen Caines

    In this episode of the Shift AI Podcast, Stephen Caines, Chief Innovation Officer and Budget Director at the City of San Jose, joins host Boaz Ashkenazy for a wide-ranging conversation on how AI is reshaping city government, public services, and the workforce at one of America's most technologically ambitious cities. Stephen shares his unconventional path from pre-med at Case Western to digital privacy law at the University of Miami, a Stanford fellowship researching surveillance AI ethics, and ultimately landing at San Jose's Mayor's Office where he now leads both innovation strategy and the city's budget. From there, the conversation dives into how San Jose is positioning itself as the AI-first city in the nation, leveraging proximity to Adobe, Cisco, Zoom, Nvidia, Apple, and Google to advance meaningful community-level change. The discussion explores the city's AI for All initiative, a public-private partnership with Anthropic, Google, and OpenAI to provide free AI education to residents and city employees alike. Stephen walks through the city's dual-track upskilling program, its approach to employee training that is purposely non-mandatory, and how San Jose is balancing top-down innovation mandates with bottom-up experimentation. Boaz and Stephen also dig into real-world deployments: object detection cameras on fleet vehicles that proactively identify potholes and road hazards before residents report them, AI translation tools expanding Spanish and Vietnamese participation in city council meetings, and the 311 customer service redesign aimed at reducing resident burden while improving satisfaction. Stephen is candid about the ROI question, how to distinguish pilots worth operationalizing from ones that generate noise without value and the long-term financial risks of AI infrastructure built on VC-subsidized pricing. The episode closes with a discussion of the GovAI Coalition, a San Jose-founded network now spanning over 900 public agencies, and Stephen's two-word vision for the future of work: chronic adaptability. Chapters [00:00] From Pre-Med to Chief Innovation Officer: Stephen's Career Journey [04:12] San Jose as the AI-First City: Population, Geography, and the Lean City Challenge [07:49] Proximity as Advantage: Partnering with Anthropic, Google, OpenAI, and Nvidia [08:23] AI for All: Free Community Education and In-Person Training Sessions [11:10] Upskilling City Employees: Voluntary Training, Two Tracks, and Retention Strategy [14:38] Balancing Top-Down and Bottom-Up Innovation [16:14] The 311 Network and Customer Service Vision: A 360-Degree View of the Resident [17:13] Object Detection on Fleet Vehicles: Proactive Pothole and Road Hazard Detection [19:34] Surprising Community Feedback and the Case for Keeping Humans at the Front Door [22:04] ROI in Government: How to Evaluate Pilots and Decide What Gets Operationalized [24:24] The Hidden Costs of AI: Staffing Realignment, Drone Programs, and VC Subsidies [26:14] Building Infrastructure You Own: The Road Safety Images Database [27:24] The GovAI Coalition: 900 Public Agencies, Shared Contracts, and Peer Learning [32:04] The Future of Work in Cities: Chronic Adaptability and the Individual Journey Connect with Stephen Caines LinkedIn: https://www.linkedin.com/in/stephen-caines/ City of San Jose Innovation Hub: https://www.sanjoseca.gov/your-government/departments-offices/information-technology/city-innovation/it-innovation-hub Connect with the GovAI Coalition Website: https://www.sanjoseca.gov/your-government/departments-offices/information-technology/ai-reviews-algorithm-register/govai-coalition Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

  7. 6月9日

    Unprompted Intelligence in High-Stakes AI with Hebbia CTO Aabhas Sharma

    In this episode of the Shift AI Podcast, Aabhas Sharma, CTO at Hebbia, joins host Boaz Ashkenazy for a deep conversation on what it actually takes to deploy AI in high-stakes institutional environments — and why the bar is far higher than most tools can meet. Aabhas shares his path from running engineering at Postmates through its Uber acquisition, to a five-year stint as CTO at fintech startup Found, to his current role at Hebbia which began as a year-long advisory engagement before he joined formally. From there, the conversation dives into the core problem Hebbia solves: knowledge workers at the world's top investment banks, asset managers, and private equity firms buried in thousands of documents, needing multi-step analysis that existing tools simply can't handle. The discussion covers how Hebbia thinks about the interplay between deterministic software and large language models using LLMs only where generative reasoning is truly needed and keeping everything else rules-based, auditable, and fast. Aabhas explains the company's "forward deployed banker" model, where former investment bankers and transaction lawyers embed with customers to encode each firm's unique institutional methodology into Hebbia's platform. Boaz and Aabhas also explore what trust actually means in practice in regulated industries: explainability at the clause level, consistency across runs, and deliberate human checkpoints built into every workflow. They dig into the adoption dynamics at junior versus senior levels, the governance challenges that come with agentic systems, and why earning autonomy must be incremental in high-stakes environments. The episode closes with a striking observation: firms layering AI on top of existing processes are just moving bottlenecks. The firms that will pull ahead are the ones willing to redesign the factory floor, asking what it would look like to build the organization from scratch with AI today. This episode is essential listening for enterprise technology leaders, founders building in regulated verticals, and anyone thinking seriously about the gap between individual AI productivity and firm-level outcomes.--- Chapters ---Connect with Aabhas Sharma LinkedIn: https://www.linkedin.com/in/aabhassharma/ Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

  8. 6月3日

    Systems Thinking is the Agentic Unlock with Google's LaSean Smith

    In this episode of the Shift AI Podcast, LaSean Smith, Product and Growth Lead at Google Cloud, joins host Boaz Ashkenazy for a wide-ranging conversation on how systems thinking and agentic AI are reshaping the way individuals, small businesses, and enterprises operate. LaSean shares a career journey that spans Microsoft HoloLens, Amazon, a successful startup exit, and now Google — plus a portfolio of small businesses that have served as his real-world AI lab. From a salad shop in Renton to a pre-construction development business in Seattle, he's applied workflow design and agent automation to solve practical problems long before it was fashionable. The conversation digs deep into how to actually build effective AI agents — not by prompting a chatbot, but by thinking in workflows first, identifying where reasoning actually needs to happen, and writing skills that make agents fast, reliable, and token-efficient. LaSean explains the "parcel grader" agent he built for his construction business, why he starts every agent build in a chat interface before moving to CLI, and how the McDonald's SOP model is the right mental framework for getting great output from AI. Boaz and LaSean also discuss the barbell economy that AI is creating — where small players and large enterprises both gain leverage while the middle gets squeezed — why Microsoft's Copilot strategy missed the point, how to think about agent security and identity, and why healthy organizational culture is the actual prerequisite for successful AI adoption. The episode closes with a reflection on what "always changing" really means as a mindset, and why building resilience and systems thinking skills now is the most important career investment anyone can make. This episode is essential listening for entrepreneurs, operators, and anyone using or thinking about deploying AI agents in their work. --- Chapters [00:00] Episode 100 and LaSean's First Jobs [03:30] From Microsoft HoloLens to Amazon to Google: LaSean's Career Path [08:00] What LaSean Does at Google Cloud Today [11:00] The Entrepreneurial Side: Small Businesses as an AI Lab [16:00] The Barbell Economy: Why the Middle Is Being Squeezed [20:00] Building the Parcel Grader Agent for Pre-Construction [25:00] How to Write Better Skills: Start in Chat, Not CLI [30:00] Workflow Thinking vs. Department Thinking [35:00] Why Google Is Generating 75% of Its Code with AI [38:00] The McDonald's SOP Model for Agent Design [42:00] Agent Security for Individuals and Small Businesses [47:00] Enterprise AI: Governance, Trust, and Organizational Design [52:00] The Two-Word Future of Work: Always Changing --- Connect with LaSean Smith LinkedIn: https://www.linkedin.com/in/laseansmith/ Connect with Boaz Ashkenazy LinkedIn: https://www.linkedin.com/in/boazashkenazy/ Email: info@shiftai.fm

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簡介

Shift AI explores how AI and ML is changing the way that we work in the digital age. The show's creator Boaz Ashkenazy interviews thought leaders who are redefining how businesses and employees will be impacted by emerging technology today and in the future | Visit shiftaipodcast.com

資訊

  • 創作者
    Boaz Ashkenazy
  • 活躍年代
    2023年 - 2026年
  • 集數
    106
  • 年齡分級
    兒少適宜
  • 版權
    © Boaz Ashkenazy
  • 節目網站
    Shift AI

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