Podcasts about ctos

In dieser Episode von AWS Cloud Horizonte spricht Heinrich Nikonow mit Matthias Egelhaaf, CIO von Siemens Global Business Services (GBS), über die praktische Umsetzung von GenAI in einem der größten Shared-Service-Center Europas. Statt endloser Proof of Concepts liefert sein Team produktive Systeme – mit beeindruckenden 60-65% Erfolgsrate bei 45 GenAI-Use-Cases. Das erwartet euch in dieser Episode: Macher-Mentalität statt POC-Falle: Wie Siemens GBS es schafft, GenAI-Projekte tatsächlich produktiv zu machen und dabei Produktivitätssteigerung zu erreichen Die Dark Side of GenAI: Warum die Lücke zwischen Erwartung und Realität so groß ist – und wie man damit umgeht Kulturwandel in der Praxis: Vom personalgetriebenen Shared Service zur Tech-Company mit neuem Mentalmodell AI-Symposium & Validation Framework: Konkrete Methoden zur Ideengenerierung und strukturierten Evaluierung von Use Cases Co-Development als Erfolgsfaktor: Warum niemand im GenAI-Dschungel alleine überlebt und wie die Zusammenarbeit mit AWS und anderen Hyperscalern funktioniert Operations Matter: Warum der Betrieb von GenAI-Lösungen genauso wichtig ist wie die Entwicklung Best Practices: Von Microservices über Communities bis zum Cross-Functional-Team-Setup Konkrete Beispiele: Der "Bionic Agent" und andere Use Cases mit echten Zahlen zum Impact Matthias teilt ehrlich die Herausforderungen: Legacy-Systeme, Datenqualität, Vertrauensaufbau im Business und die Notwendigkeit, erst die Hausaufgaben zu machen, bevor GenAI sein volles Potenzial entfalten kann. Matthias' Lieblingsspruch: "Keiner überlebt im GenAI-Dschungel alleine." Eine Episode voller praktischer Learnings für alle, die GenAI wirklich produktiv einsetzen wollen – ohne Buzzword-Bingo (Ziel: unter 10 Buzzwords pro Minute!), dafür mit Realtalk über das, was funktioniert und was nicht. Perfekt für: CTOs, CIOs, Digitalisierungsverantwortliche, SaaS-Unternehmen und alle, die von der POC-Phase in die Produktivität kommen wollen. Wie ist das für euch?

Wultra provides post-quantum authentication for banks, fintechs, and governments—protecting digital identities from emerging quantum computing threats. In this episode, Peter Dvorak shares how he broke into the notoriously closed banking ecosystem by leveraging his early experience in mobile banking development. From navigating multi-stakeholder enterprise sales to positioning quantum-safe cryptography when the threat timeline remains uncertain (consensus: 2035, but could accelerate), Peter reveals the specific strategies required to sell mission-critical security infrastructure to regulated financial institutions. Topics Discussed How post-quantum cryptography runs on classical computers while protecting against quantum threats Why European banking regulation drives global authentication standards The multi-stakeholder sales process: quantum threat teams, CISOs, CTOs, and digital product owners Conference strategy and analyst relationships (Gartner, KuppingerCole) for category positioning Banking budget cycles and why June/July approaches fail Breaking the "who else is using this?" barrier with banking-specific proof points Positioning as the only post-quantum cryptography provider for digital identity in banking GTM Lessons For B2B Founders Layer future-proofing onto immediate ROI: Post-quantum cryptography doesn't require quantum computers to function—it runs on classical infrastructure while providing superior security. Peter sells banks on moving from SMS OTP to mobile app authentication (tangible, immediate benefit) while positioning quantum resistance as migration insurance: "You won't have to rip-and-replace in three years." For emerging tech, anchor value in today's operational wins, not future scenarios. Give struggling departments concrete wins: Large banks have quantum threat teams tasked with replacing every piece of software by 2030-2035. Peter gives them measurable progress: "We move you from 5% to 10% completion on authentication and digital identity." These teams need defensible projects to justify their existence. Identify which internal groups are fighting for relevance and deliver projects they can report upward. Banking references are binary gatekeepers: Every bank asks "who else is using this?" Non-banking customers (telcos, gaming, lottery) don't count—banking regulation and systems are fundamentally different. The first banking customer is the hardest barrier. Once cleared, subsequent conversations become tractable. Budget aggressively to land that first bank, even at unfavorable terms. Respect the annual budget cycle: Banks allocate resources 12 months ahead. Approaching in Q2/Q3 means budgets are locked—even free POCs fail because internal resources are committed. Peter's pipeline strategy: build relationships and maintain visibility throughout the year, then activate when budget windows open. Don't confuse market education with active pipeline. Map and sequence multi-stakeholder buys: Authentication purchases require alignment across quantum threat teams (if they exist), cybersecurity/compliance, CTO/CIO (infrastructure acceptance), and digital product owners (UX concerns affecting their KPIs). Start at director level—board executives are too removed from technical details. Research each bank's org structure before engaging, then tailor sequencing. EU regulatory leadership creates expansion vectors: European regulations like PSD2 and strong authentication requirements get replicated in Southeast Asia, MENA, and other regions. Peter benefits from solving EU compliance first, then riding regulatory diffusion. The US remains fragmented with smaller regional banks still using username/password. Founders should analyze which geographies lead regulatory adoption in their category. Maintain composure through 18+ month cycles: Peter's regret: losing his temper during negotiations cost him time. Banking doesn't buy impulsively—sales require patience through lengthy security reviews, compliance checks, and committee approvals. Incremental progress and rational positioning matter more than aggressive closing. Emotional control is operational discipline. // Sponsors:  Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.  Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Gaurav Bhasin is the founder and managing director of Allied Advisers, an M&A advisory firm whose principals have completed over 100 sell-side transactions for software and tech founders. After two decades in investment banking and tech M&A, Gaurav is a sell-side advisor to B2B software founders who have built successful businesses and want to explore selling their companies. Allied Advisers typically works with founders selling their businesses for $20M–$200M, helping them prepare materials, run a competitive process, and negotiate terms. We discuss how today's M&A market looks very different from the 2021 bubble. Valuations have normalized, deal timelines have increased, and buyers are more disciplined. But the demand for profitable, steadily growing SaaS companies is stronger than ever. Gaurav breaks down strategic and private equity buyers, what metrics matter most, how AI influences valuations, and why most founders underestimate the emotional and operational effort required to sell. For practical founders thinking about an exit in the next few years, this episode provides clear expectations and tactical guidance. Key Takeaways Profitable Growth Wins — Buyers prefer SaaS companies growing 20–50% with real profits over faster revenue growth fueled by burn. Metrics Drive Valuation — Net retention above 110%, gross retention above 90%, and >75% gross margins increase valuation and buyer interest. Run a Real Process — A single buyer gives you no leverage. Multiple qualified buyers improve pricing, terms, and closing certainty. AI Is Lipstick — But Real — You don't need to be AI-native. Practical AI that improves product, margin, or GTM still increases buyer interest.   Quote from Gaurav Bhasin, founder and managing director of Allied Advisers "The good news for SaaS founders is that the private equity community has raised about $1.5 trillion of capital, and more is being raised. And they also have access to debt. So there's $7 trillion of dry powder to do deals. Private equity is not paid to sit on the cash. And they love recurring revenue software.  "Private equity investors will typically move much faster than strategic buyers. Strategics will take a while. You need a business unit sponsor to buy into the vision, and then they will push the corporate to do the deal. But with the private equity, they will look at your financial metrics and if you fit in, they can move pretty fast.  "The one caveat with private equity compared to strategic is they generally pay a little bit less than the strategics because strategics have established distribution and GTM for higher growth, so private equity will index more on the financials." Links Gaurav Bhasin on LinkedIn Allied Advisers on LinkedIn Allied Advisers website 2025 Vertical SaaS Report - Allied Advisers Podcast Sponsor – Fraction This podcast is sponsored by Fraction. Fraction gives you access to senior US-based engineers and CTOs — without full-time costs or hiring risks. Get 10 to 30 hours per week from vetted and experienced US-based talent. Find your next fractional senior engineer or CTO at fraction.work. You can start with a one-week, risk-free trial to test it out. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

In this episode we're talking about being a CTO. People listening might have CTO career aspirations. A lot might report into a CTO, and others might be selling to CTO's. So we talk to David about all things CTO. David Crawford has spent many years as a CTO. He's also been a CTO advisor and non-executive director. He often hosts London Tech Leader panels, and also hosts the "CTO Lens" podcast. Show Links Ben Pearce LinkedIn - https://www.linkedin.com/in/benpthoughts/ Tech World Human Skills Home - https://www.techworldhumanskills.com David Linked In - https://www.linkedin.com/in/david-crawford-13679a/ CTO Lens Podcast - https://open.spotify.com/show/5aT2XrO7CTOCLPqKZmcnT9 Takeaways The role of a CTO is complex and varies by organization. CTOs are responsible for technology vision and strategy. Understanding finance is crucial for technology leaders. Soft skills in leadership are essential for success. Performance management is a critical aspect of the CTO role. Engaging with the business is vital for a CTO. Career development requires curiosity and mentorship. Fractional CTO roles are becoming more popular. CTOs must balance technical knowledge with leadership skills. Communication with non-technical stakeholders is key. Keywords CTO, CIO, technology leadership, fractional CTO, skills, career development, performance management, stakeholder management, communication, technology strategy

You raised Series B. Now what? If you're a tech founder in a Series B company, you're scaling fast, refining product, and chasing metrics. But while your team builds the tech, who's building the trust? In this solo episode, I'm pulling back the curtain on the blind spot I see across nearly every high-growth company: invisible leadership teams. You've got funding, product-market fit, and momentum—but if your leaders can't communicate externally with clarity, credibility, and confidence, you've got a serious growth liability. I'm not talking about polishing LinkedIn bios or posting more. I'm talking about turning your operators into trusted voices that support your brand, build stakeholder confidence, and drive real business outcomes. Let's talk about what Series B companies are getting wrong, and how to fix it before your competitors outshine you. What you'll learn: Why most Series B companies are ignoring a critical growth driver The external influence blind spot that's holding your leadership team back Real talk on why product alone won't get you to Series C What perception has to do with fundraising, talent, and enterprise deals Why silent CTOs and invisible VPs are costing you credibility How to equip your team to lead out loud, not just operate in the background Your Next Steps: Access the white paper: External Influence: The Currency Every Leader Must Carry. https://externalinfluence.us Follow Shayna on LinkedIn: http:/linkedin.com/in/shaynarattler Visit our website: https://shaynadavisconsulting.com

A special report on the new executive role focused on optimizing the Cost of Inference and Data Pipeline Efficiency. Focusing on practical models for calculating true AI ROI.Tune in at https://podcasts.apple.com/us/podcast/the-rise-of-the-ai-unit-economics-officer-aueo/id1684415169?i=1000736039016Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI.Today, we're diving into a problem that is quietly hitting every enterprise board meeting: The AI Success Tax. You built a brilliant generative AI product, adoption soared... and then the cloud bill landed. The traditional promise of software—near-zero marginal cost—has been shattered. AI operates like a utility with a running meter, causing a massive Margin Shock in customer-facing products and a Budget Shock in internal tools. We're calling this the AI Unit Economics Crisis. In this special edition, we unveil a new executive role built to solve it: The AI Unit Economics Officer, or AUEO. This is the hybrid leader—part FinOps expert, part Platform Head, part AI Economist—who is mandated to move your organization past failed traditional ROI metrics. We'll unpack their core missions: mastering the Cost of Inference (CoI) through technical optimization techniques like quantization, and confronting the critical reality that human data labeling costs are rapidly exceeding compute costs. Finally, we introduce the Return on Efficiency (ROE) framework, which is how the AUEO turns AI from an unpredictable liability into your most potent strategic growth lever. Stay tuned, because the true cost of intelligence is what we're unraveling today.But first, a crucial message for the enterprise builders:

AI Daily News Rundown November 11 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-openai-is-exploring-ai-tools/id1684415169?i=1000736172688In today's edition:

AI Weekly News Rundown November 02 to November 09 3025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn this week's edition:

AI Daily News Rundown November 07 3025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AITune in at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-apple-taps-googles-gemini-for/id1684415169?i=1000735767188In today's edition:

AI Daily News Rundown November 05 3025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AITune in at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-googles-space-based-ai-data-centers/id1684415169?i=1000735421097In today's edition:

AI Daily News Rundown November 03 3025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn today's edition:

This episode recaps key insights from the recent CIO / CTO Luncheon, co-hosted with AvidEdge. Guests Monte Nuckols and Juliet Fox explore how IT leaders can drive business value through ownership, ROI clarity, and data-ready accountability, plus what it takes to lead responsibly in the age of AI.

Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI.Tune in at https://podcasts.apple.com/us/podcast/ai-liability-litigation-and-proactive-governance/id1684415169?i=1000735013941Today, we pivot from deployment to defense. The autonomous capabilities of Generative AI—from hallucinating content to designing novel drugs—have created a legal risk landscape that challenges every traditional doctrine of corporate liability, from foreseeability to product liability. This is no longer an ethics debate; it's a litigation ticking clock.In this essential special episode, we dissect the burgeoning regulatory dichotomy: the comprehensive, risk-based approach of the EU AI Act versus the fragmented, litigation-led system of the United States. We will analyze the central conflict of copyright law and the high-stakes lawsuits over training data, and we will equip you to defend against the threat of defamation by hallucination.But first, a crucial message for the enterprise builders:

Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn this week's edition:

Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIThe cost of sequencing a human genome has plummeted, but the challenge remains interpretation. We will explore how large AI models are moving from assisting diagnostics to actively designing novel drugs and personalized treatments, and what this means for enterprise R&D budgets and ethical guidelines.Setting the stage:Why is AI essential for genomics now?What is the current bottleneck in drug discovery?How are LLMs being fine-tuned for chemical and biological structures?Specific AI applications that are cutting discovery time.How is AI used in de novo protein design?What is a "digital twin" of a patient, and how does it speed up clinical trials?How do we secure massive genomic datasets (PII)?What happens when models discover biases in existing genetic research?Is personalized medicine an investment or an insurance policy?Which AI capabilities (e.g., small molecule prediction vs. large molecule discovery) yield the highest ROI?What is the single most important hire an R&D department can make in the next 12 months to prepare for the AI-native bio-future?

In this conversation with Malte Ubl, CTO of Vercel (http://x.com/cramforce), we explore how the company is pioneering the infrastructure for AI-powered development through their comprehensive suite of tools including workflows, AI SDK, and the newly announced agent ecosystem. Malte shares insights into Vercel's philosophy of "dogfooding" - never shipping abstractions they haven't battle-tested themselves - which led to extracting their AI SDK from v0 and building production agents that handle everything from anomaly detection to lead qualification. The discussion dives deep into Vercel's new Workflow Development Kit, which brings durable execution patterns to serverless functions, allowing developers to write code that can pause, resume, and wait indefinitely without cost. Malte explains how this enables complex agent orchestration with human-in-the-loop approvals through simple webhook patterns, making it dramatically easier to build reliable AI applications. We explore Vercel's strategic approach to AI agents, including their DevOps agent that automatically investigates production anomalies by querying observability data and analyzing logs - solving the recall-precision problem that plagues traditional alerting systems. Malte candidly discusses where agents excel today (meeting notes, UI changes, lead qualification) versus where they fall short, emphasizing the importance of finding the "sweet spot" by asking employees what they hate most about their jobs. The conversation also covers Vercel's significant investment in Python support, bringing zero-config deployment to Flask and FastAPI applications, and their vision for security in an AI-coded world where developers "cannot be trusted." Malte shares his perspective on how CTOs must transform their companies for the AI era while staying true to their core competencies, and why maintaining strong IC (individual contributor) career paths is crucial as AI changes the nature of software development. What was launched at Ship AI 2025: AI SDK 6.0 & Agent Architecture Agent Abstraction Philosophy: AI SDK 6 introduces an agent abstraction where you can "define once, deploy everywhere". How does this differ from existing agent frameworks like LangChain or AutoGPT? What specific pain points did you observe in production that led to this design? Human-in-the-Loop at Scale: The tool approval system with needsApproval: true gates actions until human confirmation. How do you envision this working at scale for companies with thousands of agent executions? What's the queue management and escalation strategy? Type Safety Across Models: AI SDK 6 promises "end-to-end type safety across models and UI". Given that different LLMs have varying capabilities and output formats, how do you maintain type guarantees when swapping between providers like OpenAI, Anthropic, or Mistral? Workflow Development Kit (WDK) Durability as Code: The use workflow primitive makes any TypeScript function durable with automatic retries, progress persistence, and observability. What's happening under the hood? Are you using event sourcing, checkpoint/restart, or a different pattern? Infrastructure Provisioning: Vercel automatically detects when a function is durable and dynamically provisions infrastructure in real-time. What signals are you detecting in the code, and how do you determine the optimal infrastructure configuration (queue sizes, retry policies, timeout values)? Vercel Agent (beta) Code Review Validation: The Agent reviews code and proposes "validated patches". What does "validated" mean in this context? Are you running automated tests, static analysis, or something more sophisticated? AI Investigations: Vercel Agent automatically opens AI investigations when it detects performance or error spikes using real production data. What data sources does it have access to? How does it distinguish between normal variance and actual anomalies? Python Support (For the first time, Vercel now supports Python backends natively.) Marketplace & Agent Ecosystem Agent Network Effects: The Marketplace now offers agents like CodeRabbit, Corridor, Sourcery, and integrations with Autonoma, Braintrust, Browser Use. How do you ensure these third-party agents can't access sensitive customer data? What's the security model? "An Agent on Every Desk" Program Vercel launched a new program to help companies identify high-value use cases and build their first production AI agents. It provides consultations, reference templates, and hands-on support to go from idea to deployed agent

AI Daily Rundown: October 31, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-amazon-ceo-says-layoffs-were/id1684415169?i=1000734511393In Today's edition:

AI is more powerful than ever, but companies are way overhyping this one feature. Today, we're talking to Bryan McCann, CTO and co-founder at You.com. We discuss why CTOs need to start asking deeper questions about meaning, how AI is forcing us to rethink consciousness and intelligence, and why treating AI with respect might actually help you become a better person. All of this right here, right now, on the Modern CTO Podcast!  Thank you to Digital Ocean for sponsoring this episode. For simple cloud and powerful AI that's built to scale, check out Digital Ocean here. To learn more about You.com, check out their website here.

AI Daily Rundown: October 30, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

AI Daily Rundown: October 29, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

Businesses are spending millions on AI tools hoping to accelerate time-to-market but aren't seeing organizational-level results. Laura Tacho (CTO @ DX) explains why an "individual productivity" mindset fails and how AI merely accelerates the condition of the system it enters. She provides a framework for leaders to shift to a systems-level approach, find high-leverage ROI by looking outside the 20% of time spent coding, and understand what sets high-ROI orgs apart. Plus Laura shares data literacy tools to cut through the "whiplash" of conflicting AI reports and provides key considerations for 2026 budgeting, detailing where and how companies are planning to strategically invest.ABOUT LAURA TACHOLaura Tacho is CTO at DX, a developer experience company. She previously led teams at companies like CloudBees, Aula Education, and Nova Credit. She's an expert in building world-class engineering organisations that consistently deliver outstanding results. Laura has coached CTOs and other engineering leaders from startups to the Fortune 500, and also facilitates a popular course on metrics and engineering team performance.SHOW NOTES:Downsides to approaching organizational outcomes from an individual task level (2:59)Why individual product gains don't always equate to systems-level improvements (4:56)How the quality of existing systems impacts the improvements AI can foster (7:26)Strategies for shifting mental models from the individual to systems level (9:09)Implement training & enablement techniques as an organizational lever (11:22)Common workflows that can unlock new problem-solving methods (14:46)Understanding what impact you want to see / getting the most ROI from AI (18:40)How to interpret the data when it comes to AI & its true ROI (21:22)AI data literacy for engineering leaders (23:06)Interpreting the meter study & what it means for engineers using AI (25:49)Quality vs. quantity when it comes to AI implementation on the org level (28:43)Characteristics that high-ROI companies possess when it comes to AI (30:35)Strategies to invest in that may lead to higher ROI (32:29)Laura's observations on time & money budgeting / investments for 2026 (35:28)Embracing cost savings & opportunity generation as an eng org (38:08)Tackling fear / uncertainty when it comes to AI adoption, budgeting, & ROI (40:01)LINKS AND RESOURCESPrevious Episode with Laura TachoIntroducing the AI Measurement Framework from DXAtlassian State of DevEx ReportMETR StudyDORA Report (2025)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ion Feldman, CTO at Rightway, has learned to love one thing about scaling a company from a kitchen table to nearly 1,000 employees: his job completely changes every six months. In this episode, Ion shares what it means to lead engineering when the role refuses to stay still—from writing code in the early days to building product, security, and data teams, and now shaping AI infrastructure. He explains how to stay hands-on without micromanaging, why he deliberately works himself out of roles by hiring people better than him, and how to preserve startup urgency inside a heavily regulated industry. If you've ever wondered how CTOs balance technical depth with business strategy while keeping their team fast and focused, this conversation delivers.Key TakeawaysTreat change as part of the job.Ion's leadership mindset centers on adapting to wherever the company needs him most—product, security, data, or AI. He views change as an opportunity to grow, not a disruption to avoid.Hire yourself out of the role.He dives deep into an area, builds it from scratch, then brings in experts who can take it to the next level. Once the right leadership is in place, he steps back completely and lets them own it.Hands-on time creates credibility.Ion makes sure every leader spends time building. Each quarter, his team takes a week off from meetings and Slack to focus on creating something new. It keeps them close to the work and sharp as technical leaders.AI adoption needs clarity and focus.Rightway avoids vague “use AI” goals by targeting clear use cases like unit test generation and onboarding to codebases. Sharing examples and results drives faster adoption than leaving teams to figure it out alone.Fail fast and move forward.Ion builds space for experimentation but expects quick recognition of failure. The goal is not to avoid mistakes but to learn, pivot, and evolve faster.Timestamped Highlights[02:10] The zero to one mindset – Why Ion thrives on constant reinvention and the satisfaction of building new functions from the ground up.[06:41] Three pillars of AI strategy – How Rightway is transforming work through AI enablement, applied projects, and bold experiments.[08:26] Delegating by design – How going deep before handing off creates clarity and trust across teams.[15:42] Skills that matter later – Ion reflects on learning public speaking and business fluency after years of technical focus.[17:48] Creating space for risk – How to give your team agency to take on big challenges and fail fast without fear.[21:22] Preparing successors – Why the best leaders hire people who will replace them and rethink everything they built.What Stuck With Us"I don't know, maybe I just get bored easily. I think a lot of people could view it as a burden and they want to stay in their lane of expertise, but I see it as an opportunity to learn and change things up."Pro Tips for Tech LeadersTake a week each quarter to build something with zero meetings or Slack. It reconnects you and your team with what you actually love about engineering.Wait to hire senior leadership until the need is undeniable. The role becomes meaningful, and you'll attract higher caliber talent.Give your engineers specific AI examples and let them experiment from there. Adoption follows clarity, not mandates.

Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI.Today, we move beyond the office environment and into the real world, where billions in infrastructure, energy, and construction assets are managed. These foundational sectors face a relentless convergence of pressure: aging infrastructure, severe safety mandates, and non-negotiable ESG compliance. Reactive maintenance is no longer a viable strategy; it is a liability.This special episode is dedicated to the new standard: Intelligent Automation. We are examining the fusion of autonomous data capture via advanced drones with the cognitive power of AI to create a new data-driven rigor for heavy industry.We're reviewing the article, "Intelligent Automation: AI and Drones in Heavy Industry," breaking down how companies are using this combination to move from risky, manual inspections to predictive maintenance that detects cracks and corrosion days, even weeks, before catastrophic failure. This isn't just efficiency; it's about zero-trust infrastructure monitoring at scale.But first, a crucial message for the enterprise builders:

A speculative but grounded discussion on how companies should be restructuring their R&D and product teams today to capitalize on a future with highly capable agents.Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI.Today, we go beyond the immediate quarter and focus on long-term strategic survival.When you operate at the executive level, you know the competitive "moat" built on data or scale is dissolving. This special episode is dedicated to the most critical question facing every CTO and investor: What happens after AGI?We're breaking down the article, "Beyond Moats: Analyzing the Next Wave of Post-AGI Business Models." We reveal how competitive advantage shifts entirely, forcing companies to pivot from gathering data to structuring proprietary workflows and coordinating autonomous agent fleets.This is not a theoretical discussion; it is a roadmap for future proofing your enterprise.Before we dive in, we have a critical message for the enterprise builders listening:

AI Daily Rundown: October 28, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-amazon-axes-14-000-corporate/id1684415169?i=1000733899886In Today's edition:✂️Amazon Axes 14,000 Corporate Jobs because of AI

AI Daily Rundown: October 27, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

AI Weekly Rundown From October 19th to October 26th 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI

Darryl Pahl is the co-founder of DFnet, a Seattle-based company providing clinical trial data management software and services. Along with his wife and co-founder, Lisa Andrzejczyk, Darryl started the company more than 20 years ago after careers at Fred Hutchinson Cancer Research Center. They built DFnet around long-term client relationships in global health and clinical research. The company runs DFdiscover, an enterprise-grade electronic data capture and management platform used in clinical studies worldwide. With offices in the U.S., Canada, and South Africa, DFnet has grown to more than 50 employees and is approaching $10M in revenue. Clients range from the U.S. Department of Veterans Affairs to nonprofits like PATH and major universities. Still independent and bootstrapped, DFnet has made key moves to prepare for the future—such as bringing in a growth-focused CEO, diversifying beyond single-client risk, and shifting legacy software to SaaS and services. Darryl shares the lessons from running conservatively under debt, buying rather than building, and building a global company rooted in relationships and practical execution. Key Takeaways Stability First Growth – Carrying a 10-year SBA loan forced conservative growth and taught the discipline of stability over risky expansion. Buying Not Building – Acquiring DataFax brought 35+ new clients overnight and proved that buying legacy software can be smarter than reinventing. Services Plus Software – Unlike pure SaaS, DFnet thrives by combining consulting, hosting, and software in a regulated field. Spouse Founders Structure – Their 51/49 ownership split avoided deadlocks and kept marriage and business aligned. This Interview Is Perfect For SaaS founders balancing growth and control Founders considering succession or sale Bootstrapped entrepreneurs in niche B2B markets Anyone curious about global health data and impact-driven tech Quote from Darryl Pahl, co-founder of DFnet "The best position to be in is to say that in three to five years, we would be crazy to sell this company. It's doing so well. That would be the perfect thing. And what we're not looking for is a giant payout. We have a very modest lifestyle. “But is an asset, it is a business, and there's a business aspect. It would have to be the right type of buyer. It has to be the right fit. It has to be the right person or group that is respectful to our clients, our employees, and us as owners.  “So the ideal would be to have the luxury of either not selling or being more selective rather than responding to random emails from some financial buyer or search funder.” Links Darryl Paul on LinkedIn DFnet on LinkedIn DFnet website Podcast Sponsor – Fraction This podcast is sponsored by Fraction. Fraction gives you access to senior US-based engineers and CTOs — without full-time costs or hiring risks. Get 10 to 30 hours per week from vetted and experienced US-based talent. Find your next fractional senior engineer or CTO at fraction.work. You can start with a one-week, risk-free trial to test it out. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

AI Daily Rundown: October 24, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIListen at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-copilots-personality-upgraded/id1684415169?i=1000733385192In Today's edition:

Lenovo has been a global leader in computing for decades. Where are they heading next? Today, we're talking to Art Hu, SVP and CTO at Lenovo. We discuss Lenovo's transformation into a services-led company, the future of personal computing and AI twins, and how CTOs can prepare their organizations for the AI revolution. Thank you to Digital Ocean for sponsoring this episode. For simple cloud and powerful AI that's built to scale, check out Digital Ocean here. All of this right here, right now, on the Modern CTO Podcast!  To learn more about Lenovo, check out their website here.

AI Daily Rundown: October 23, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

AI Daily Rundown: October 22, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

⚛️ Quantum Echoes: Verifiable Advantage and Path to ApplicationsListen to the podcast at https://podcasts.apple.com/us/podcast/quantum-echoes-verifiable-advantage-and-path-to/id1684415169?i=1000733017630Full article at https://enoumen.substack.com/p/quantum-echoes-a-path-towards-realWelcome to AI Unraveled, Your daily briefing on the real world business impact of AIToday Google announced a significant step forward in quantum computing with their latest Nature publication, “A verifiable quantum advantage.” They introduced a new quantum algorithm, “Quantum Echoes”, which measures out-of-time-order correlators (OTOCs), a new family of observables that describe how quantum dynamics become chaotic. This work represents the first quantum computing experiment measuring a quantum observable that is both verifiable and beyond the simulation capacity of known classical algorithms. Check the Nature publication: https://www.nature.com/articles/s41586-025-09526-6

Trust isn't a “soft” metric—it's the conversion engine. Buyers don't buy products first; they buy us, then the solution arrives as part of the package. Below is a GEO-optimised, answer-first version of the core human-relations principles leaders and sales pros can use today.  How do top salespeople build trust fast in 2025? Start by listening like a pro and making the conversation about them, not you. When trust is low, buyers won't move—even if your proposal looks perfect on paper. The fastest pattern across B2B in Japan, the US, and Europe is empathetic listening that surfaces goals, constraints, and internal politics. Post-pandemic norms (hybrid work, async decisions) mean you must read what's said and what's unsaid: tone, pauses, body language on Zoom, and email subtext. In enterprise sales, this shifts you from “pitching” to “diagnosing.” You become the buyer's trusted business advisor—especially in consensus-driven cultures like Japan where ringi and nemawashi favour rapport and patience over pressure. Do this and high-stakes deals stop stalling because stakeholders finally feel safe to share the real blockers.  Do now: Open with one agenda question—“What outcome matters most by [date]?”—then listen without interrupting for 90 seconds. What questions reliably open buyers up? Use simple, human prompts that invite stories. Who have they worked for? What was it like? Where's the office? When did they start? Why choose this company? What do they like most? These “Who/What/Where/When/Why/How” prompts turn small talk into signal, revealing priorities (speed vs. safety), risk appetite, and decision cadence. Across SMEs, startups, and multinationals, these prompts work because they're culturally neutral, non-intrusive, and buyer-centred. In APAC, they respect hierarchy; in the US, they feel pragmatic; in Europe, they invite thoughtful context. The goal isn't to interrogate—it's to let people talk about themselves while you capture needs, metrics, and names of influencers you'll later engage.  Do now: Prepare six openers on a card; ask two, go deep on one, and mirror key phrases back. How do I remember personal details without being awkward? Use the “Nameplate → House → Family → Briefcase → Airplane → Tennis Racquet → Newspaper” memory chain. Visualise a giant nameplate smashing into a bright house; inside, a baby with a briefcase pulls out an old plane; its propellers are tennis racquets threaded with rolled newspapers. Each hook cues a safe, human topic: name, home, family, work, travel, hobbies, and industry news. This light mnemonic keeps first meetings natural across cultures. In Japan, it supports relationship-first norms (meishi exchange, hometown ties). In the US/EU, it avoids prying while still finding common ground (sports, routes, recent sector headlines). Use tact and sequence flexibly; skip topics if they feel private. The point is to remember them so follow-ups feel personal, not transactional.  Do now: Before calls, jot the seven cues; after calls, log one fact per cue in your CRM. What if I don't know the buyer's interests yet? Keep asking—then mirror their language and frame benefits in their terms. Early on, many buyers withhold interests until they decide you're trustworthy. That's normal. Persist with respectful questions, then translate features into “so-whats” they already value: uptime for CTOs, cycle-time for COOs, compliance for CFOs, psychological safety for HR. As of 2025, complex deals involve multi-threading (RevOps, Legal, IT, Security). Tailor each touch: startup CTOs want velocity and unit economics; enterprise VPs want risk mitigation and stakeholder alignment; Japanese heads of division may prioritise harmony and precedent. The win is relevance—your proposal reads like their strategy memo, not your brochure.  Do now: After each meeting, write one line: “They care most about ___ because ___.” Lead with that next time. How do I make someone feel important—without manipulation? Spot real wins and praise them sincerely and specifically. Most professionals get little recognition. When you catch people doing something right—clear brief, crisp data, fast feedback—name it. Never over-flatter; buyers detect tactics instantly. The goal is dignity, not drama. Practical example: “Your timeline reduced rework across Legal and IT—that saved us both weeks.” In Japan, sincere appreciation that acknowledges team effort (not just the individual) lands better; in the US, direct credit energises champions. Across sectors (SaaS, manufacturing, services), this fosters reciprocity and deepens trust far faster than discounts ever can.  Do now: In your next email, add one honest, specific thank-you sentence linked to a business outcome. What should leaders systemise so this sticks? Bake these principles into playbooks, onboarding, and CRM hygiene. Codify the seven memory cues, the open-question matrix, and a “buyer interest” field in CRM. Coach for silence (count to three before replying). Review call snippets for interrupt rate and question balance. Reward teams for discovery quality, not just revenue. Executives at firms from startups to conglomerates can run fortnightly “deal trust reviews”: is the sponsor heard, interests mapped, and recognition given? In Japan, align with nemawashi—map stakeholders and pre-wire decisions. In the US/EU, pressure-test value hypotheses with RevOps and Finance. Consistency beats charisma.  Do now: Add three fields to your CRM today—Interests, Stakeholders, Recognition Given—and make them required. Conclusion When you listen deeply, speak in the buyer's interests, and recognise people sincerely, you stop selling and start being chosen. Make this your firm's operating system and watch cycle times shorten and referrals grow.  FAQs Isn't this just “be nice” advice? No—these behaviours reduce friction, surface risks early, and accelerate consensus, which shortens sales cycles.  Do these tips work in Japan? Yes—especially the memory chain and sincere group-focused recognition, which fit relationship-first norms.  How do I measure progress? Track interrupt rate, number of stakeholder interests captured, and instances of specific recognition logged in CRM. Next Steps Add the seven-cue mnemonic and open-question set to your onboarding. Require “Interests” and “Recognition Given” fields in every opportunity. Coach teams to wait three beats before replying on calls. About the Author Dr. Greg Story, Ph.D. in Japanese Decision-Making, is President of Dale Carnegie Tokyo Training and Adjunct Professor at Griffith University. He is a two-time winner of the Dale Carnegie “One Carnegie Award” (2018, 2021) and recipient of the Griffith University Business School Outstanding Alumnus Award (2012). As a Dale Carnegie Master Trainer, Greg is certified to deliver globally across all leadership, communication, sales, and presentation programs, including Leadership Training for Results. He has written several books, including three best-sellers—Japan Business Mastery, Japan Sales Mastery, and Japan Presentations Mastery—along with Japan Leadership Mastery and How to Stop Wasting Money on Training. Japanese editions include ザ営業, プレゼンの達人, トレーニングでお金を無駄にするのはやめましょう, and 現代版「人を動かす」リーダー. Greg also publishes daily business insights on LinkedIn, Facebook, and Twitter, and hosts six weekly podcasts. On YouTube, he produces The Cutting Edge Japan Business Show, Japan Business Mastery, and Japan's Top Business Interviews, followed widely by executives seeking success strategies in Japan. 

AI Daily Rundown: October 21, 2025: Your daily briefing on the real world business impact of AI

AI Daily Rundown: October 17, 2025: Your daily briefing on the real world business impact of AI

The Geopolitics of Silicon and the Maturation of Intelligence:

In this episode of Convergence.fm, Ashok Sivanand sits down with Farhan Thawar, Head of Engineering at Shopify, to go behind the scenes of how Shopify not only keeps pace with rapid change but leads it.  The discussion explores how Shopify became one of the first platforms to allow merchants to sell products directly inside ChatGPT, why that move challenges Amazon's dominance, and what it takes to build a company that learns faster than it fails.  Farhan explains the systems that make being first repeatable rather than accidental, including Shopify's internal LLM proxy, MCP servers, experimentation culture, and democratized tooling.  If you are a CEO, COO, or CTO looking to scale through culture, systems, and intentional technology adoption, this episode shows what it looks like to operate with conviction and long-term relevance. Key Topics and Moments: Shopify and OpenAI's commerce integration. The same day OpenAI enabled in-chat shopping, Shopify merchants were already live. Farhan explains what it takes for a company of Shopify's size to move with that kind of speed Competing with Amazon through culture, not size. Shopify has 3,000 engineers compared to Amazon's 35,000+, yet continues to outpace bigger players by focusing on coherence, focus, and empowered execution rather than bureaucracy and scale. The meaning behind Tobi Lütke's April AI memo. Farhan discusses how Shopify operationalized its “AI is non-optional” stance, what baseline expectations look like, and how performance is evaluated in an AI-native organization. AI reflexivity and the “three buckets.” Farhan explains how teams are taught to recognize “AI not allowed,” “AI optional,” and “AI mandatory” problems so that employees develop instinct for when to reach for AI — and when to pick up the screwdriver. The risk of ‘vibe coding' and why hand tools still matter. Farhan shares lessons from real incidents inside and outside Shopify, like the Cloudflare outage caused by unreviewed AI-generated code, and how engineering leaders teach judgment, not just prompting. The LLM Proxy and MCP Servers. Inside look at how Shopify democratized AI across departments by building an internal platform that connects all major models and corporate data sources, enabling every employee to build workflows and ask intelligent questions — not just engineers. AI budgeting vs. SaaS budgeting. Farhan explains why AI usage isn't treated like traditional SaaS spend and how Shopify encourages heavy experimentation by rewarding impact rather than punishing token consumption. Experimentation as a system. How teams are encouraged to show work at 20%, not 80%, and why the speed of learning, not perfection, is the true productivity metric. Subtraction as leadership. Farhan shares how founders and executives must delete outdated processes, rules, and layers of bureaucracy to make room for new ideas — why process should only exist if it makes something possible or 10x better. Hiring and growing AI-native talent. Why Shopify doubled down on internships, hiring 1,000 interns this year and next, and how younger engineers push full-timers to stay current by being born AI-native “centaurs.” Responsibility versus accountability. Why leaders can delegate tasks but not responsibility, and how to stay in the work without disempowering the team. Certainty as intolerance. Farhan's reflection on why overconfidence kills creativity, and how leaders can replace fixed beliefs with wayfinding, curiosity, and adaptive decision-making. Rapid-fire reflections for CEOs. Ashok and Farhan close with lessons on showing unfinished work, modeling curiosity, and removing friction as a cultural operating system. Who Should Listen: Mid-market CEOs, COOs, and CTOs building adaptable organizations that can scale.  Leaders focused on culture and transformation, not just technology adoption.  Operators who want to apply product thinking and modern software practices to traditional industries. Notable Quotes: “We have a baseline expectation of using AI. If you have two people, one using AI and one not, they will both be evaluated the same.” – Farhan Thawar on AI usage expectations  “We don't like waste, but we don't have limits. If you believe in your workflow, use the best model for your problem solving.” – Farhan Thawar on AI token cost and consumption   “You can now buy directly in chat from Shopify merchants. That is a major shift in how people discover and buy online.” – Ashok Sivanand on Shopify launching all their merchants on ChatGPT's Shop feature on the very day it was launched  Related Reading and References: Shopify Blog: Shopify and OpenAI bring commerce to ChatGPT (official announcement) - https://www.shopify.com/news/shopify-open-ai-commerce?podconvergence   Reuters: OpenAI partners with Shopify, Stripe, and others to expand ChatGPT integrations - https://www.reuters.com/world/americas/openai-partners-with-etsy-shopify-chatgpt-checkout-2025-09-29/?podconvergence   TechCrunch: Inside Tobi Lütke's AI Memo and Shopify's Cultural Shift - https://techcrunch.com/2025/04/07/shopify-ceo-tells-teams-to-consider-using-ai-before-growing-headcount/?podconvergence  Farhan's opinions about token consumption - https://x.com/fnthawar/status/1930367595670274058  Farhan's article about “looking stupid”- https://medium.com/helpful-com/why-looking-stupid-is-my-superpower-2ee3fe00a748?podconvergence  The Convergence.fm first episode with Farhan in 2024 - https://convergence.fm/episode/from-code-to-culture-how-shopify-thrives-under-farhan-thawars-thought-leadership  The Convergence.fm Episode about Tobi Lütke's leaked AI memo mandate, and our 6 takeaways - https://convergence.fm/episode/shopifys-leaked-ai-mandate-explained-6-takeaways-for-your-product-team  Tobi's memo Tweet - https://x.com/tobi/status/1909231499448401946 Unreasonable Hospitality (book) - https://www.amazon.com/Unreasonable-Hospitality-Remarkable-Giving-People/dp/0593418573  Farhan's Twitter (public handle) - https://x.com/fnthawar  Reflection and Action Steps: Start with your mission. Before choosing tools, clarify what problem you are solving and what your business stands for.  Enable your team. Ask whether you are removing barriers or creating them.  Are employees empowered to experiment?  Model the change. Use AI tools yourself. Share your learnings, wins, and failures openly. F Foster learning. Consider introducing internal forums or “thinking clubs” that encourage curiosity and reflection across your team.  

Coralogix CEO Ariel Assaraf reveals how their observability lake lets companies own their data, reduce costs, and use AI agents to transform monitoring into actionable business intelligence.Topics Include:Coralogix solves observability scaling issues: tool disparity, sprawling costs, limited control.Streama parses data pre-ingestion; DataPrime queries directly on customer's own S3 buckets.AI will generate massive unstructured data, making observability challenges exponentially worse.CTOs should ask: Can observability data drive business decisions beyond just monitoring?Observability lake lets you own data in open format versus vendor lock-in.OLLI designed as research engine, not another natural language database interface.Ask business questions like "What's customer experience today?" instead of technical queries.Trading platform unified tools, reduced resolution time 6x, now uses for business intelligence.Future: Multiple AI personas, automated investigations, hypothesis-driven alerts without human prompting.AWS partnership enables S3 innovation, Bedrock models, and strong co-sell growth motion.Data sovereignty solved: customers control their S3, remove access anytime, own encryption.Business data experience will match consumer AI tools within two years fundamentally.Participants:Ariel Assaraf – Chief Executive Officer, CoralogixBoaz Ziniman – Principal Developer Advocate - EMEA, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

We've entered what I call The Friction Era—a period where every organization, from the fastest-growing startup to the most entrenched enterprise, is advancing so rapidly that the internal systems meant to support growth are straining under their own ambition. Mergers, acquisitions, product expansions, tech integrations, AI disruption, competitive parity—all of it is hitting at once. And yet, none of it signals failure. Quite the opposite. It signals acceleration.But acceleration brings turbulence. And when the temperature inside an organization rises—not because things are breaking, but because the stakes are higher—you learn quickly who your real operators are. The CHRO, the CFO, and the CTO become the three anchors in the storm. They are the triad balancing the organization's emotional intelligence, financial discipline, and technological infrastructure. And if they're not in sync, the company drifts into chaos, no matter how strong the product or how brilliant the strategy.In this episode, we go behind the scenes into how these three executives navigate what most companies never talk about publicly—the fragile, high-stakes process of scaling without losing the core of what made the business great.We'll unpack:How CHROs are redefining their role from HR operator to cultural engineer—embedding trust, energy, and clarity into the revenue architecture itself, not just engagement programs.How CFOs are reframing financial discipline not as constraint, but as a creative tool to shape psychological safety, focus, and long-term decision-making velocity.How CTOs are engineering unification—breaking down redundant systems, harmonizing data, and turning technology stacks into living frameworks that guide behavior, not just performance.We'll also dive into what happens when growth gets ahead of structure: when a company's narrative outpaces its people systems, when speed starts to erode judgment, and when competing incentives fracture collaboration between sales, product, and finance. Because at that point, it's not just about “alignment”—it's about survival through sophistication.The most forward-thinking executives know that emotional discipline is operational discipline. They know that culture without commercial intent is theater—and that commercial intent without culture is chaos. So this conversation is about what it takes to build the internal architecture of a billion-dollar organization before you actually reach a billion.This is a raw, unfiltered look at the modern enterprise from the inside out. A masterclass in executive endurance, systemic awareness, and the courage to build stability inside complexity.Core Question: When your organization is in motion—growing, merging, integrating, evolving—how do you maintain the psychological precision, financial rigor, and operational unity to keep the whole thing from tearing apart at the seams?

On the latest episode of After Earnings, Ann sits down with Udemy CEO Hugo Sarrazin to discuss the company's pivot from a traditional online course marketplace to an AI-powered platform designed to reskill the global workforce. Highlights include: - Udemy's shift from one-off course sales to a subscription model - The company's enterprise push to reskill workforces at scale - The future of its instructor-driven marketplace - How AI can deliver mass personalization in learning 00:00 – Hugo Sarrazin Joins 01:12 – Why the online learning industry is under pressure 02:42 – Udemy's consumer vs. enterprise business explained 05:56 – How AI enables personalization in learning 08:00 – Marketplace model vs. proprietary content 11:58 – Transition to subscriptions and monetization challenges 15:02 – Is Udemy becoming a digital media company? 16:48 – Enterprise clients and “just-in-time” learning 20:27 – Selling to CTOs, HR, and business leaders 23:33 – Reskilling 92 million workers in the AI era 25:39 – ROI pressure vs. growth opportunity 27:11 – Margins, cash flow, and product investment 29:03 – Hugo Sarrazin's career journey: McKinsey to CEO 33:40 – Will AI replace consulting? 37:55 – The future of Udemy After Earnings is brought to you by Stakeholder Labs and Morning Brew. For more go to https://www.afterearnings.com Follow Us X: https://twitter.com/AfterEarnings TikTok: https://www.tiktok.com/@AfterEarnings Instagram: https://www.instagram.com/afterearnings_/ Reach Out Email: afterearnings@morningbrew.com $UDMY Learn more about your ad choices. Visit megaphone.fm/adchoices

What happens when a CTO and a CIO of a global tech company sit down together to talk about AI? That's the starting point of today's episode, where I'm joined by Jeremy Ung, CTO at Blackline, and Sumit Johar, the company's CIO. Rather than chasing the hype, we focus on what AI really means for executive decision making, governance, and business outcomes. Both leaders open up about how their partnership is blurring the traditional lines between product and IT, and why the board is demanding answers on topics that once sat deep in the technology stack. Jeremy and Sumit explain why AI is not just another SaaS subscription and why expectations have changed so dramatically. For decades, technology was seen as predictable, a rules-based engine that followed instructions without error. AI feels different because it speaks, reasons, and sometimes makes mistakes. That human-like experience is what excites employees, but it is also what unsettles them. This is where education and governance come in, helping teams learn how to question, verify, and trace AI outputs before they make critical decisions. We also explore how AI agents are beginning to work across tools like SharePoint and email, raising new compliance and security questions that CIOs and CTOs must answer together. The conversation turns to AI sprawl, a problem that mirrors the SaaS explosion of a decade ago. With new AI tools emerging every week, enterprises risk overlapping investments and fragmented initiatives. Sumit shares how Blackline uses two governance councils to keep projects aligned. One is dedicated to risk, pulling in voices from legal, security, and privacy. The other is focused on transformation, evaluating whether requests for new AI capabilities make sense, or whether they duplicate what already exists. The signal that sprawl is taking root, he says, is when requests for tools suddenly jump from a few each month to a dozen. We also tackle the build versus buy dilemma. Budgets haven't magically increased just because AI is hot. Jeremy argues that building only makes sense when it reinforces a company's core advantage. Everything else should be bought, integrated, and kept flexible so that organizations can pivot as the AI landscape changes. Both leaders stress that trust, auditability, and value delivery must sit at the center of every investment decision.  

Praveen Ghanta, founder of Fraction and former CEO of HiddenLevers, shares how he turned his experience scaling a bootstrapped SaaS company into a fast-growing fractional talent marketplace. After HiddenLevers reached $8M in ARR and sold for over $100M, he realized that senior fractional engineers were the secret to delivering efficiently without expensive full-time hires. Fraction now serves over 100 SaaS clients with a vetted pool of 500 senior U.S.-based engineers and CTOs. Typical engagements run 10–30 hours a week, helping founders tackle scaling challenges in vertical SaaS, AI engineering, DevOps, and legacy system conversions. The company has reached $10M ARR in just three years while keeping half its own team fractional. Praveen explains how clients use Fraction to save costs, speed development, and even prepare for M&A due diligence with fractional CTOs. He also highlights how AI has boosted senior developer productivity by 4x, why U.S.-only context matters, and how fractional-to-full-time hiring often becomes a win-win path. This interview is perfect for SaaS founders at $1M–10M ARR, hitting scaling issues, vertical SaaS leaders needing senior engineers without VC funding, and founders considering AI-powered product features and engineering talent. Key Takeaways Fractional Individual Contributors: Not just execs—senior engineers deliver hands-on code, marketing, and DevOps part-time. AI Productivity Boost: Senior developers using AI tools are delivering 2–4x more than peers without them. Cost Advantage: Starting at $5K/month, founders access senior dev talent without $200K+ full-time salaries. Best ICP Fit: Vertical SaaS companies at $1–10M ARR facing scaling issues or legacy migrations. Developer Productivity: Fraction leveraged its experience with over 100 clients to build DevHawk.ai, a tool that manages fractional talent and delivers results even more efficiently. This Interview Is Perfect For SaaS founders stuck at scaling challenges without a budget for big teams Bootstrappers and practical founders looking for senior engineering firepower Founders facing legacy code, scaling issues, or AI feature rollouts Non-technical founders struggling to manage offshore or junior dev teams Quote from Praveen Ghanta, founder of Fraction “There are a lot of very experienced engineers who get into a senior developer role, but if they're not going to become the manager of the team, there's not a really good and obvious career path for them. “They start to get bored because they know their job inside and out and it's relatively easy for them to keep delivering.  “So working on a startup on the side is actually a way for both for them to sort of enrich their career and see new things and have that creative satisfaction, but at the same time, not take the risk. There are plenty of folks that want to be full-time at the startup, but there's risk in being at a startup.”  Links Praveen Ghanta on LinkedIn Fraction on LinkedIn Fraction website (fraction.work) DevHawk website Podcast Sponsor – Fraction This podcast is sponsored by Fraction. Fraction gives you access to senior US-based engineers and CTOs — without full-time costs or hiring risks. Get 10 to 30 hours per week from vetted and experienced US-based talent. Find your next fractional senior engineer or CTO at fraction.work. You can start with a one-week, risk-free trial to test it out. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

Healthcare is in the middle of a great migration, moving out of traditional "on-prem" data centers and into the cloud. What does that mean for health systems, clinicians, and ultimately patients? Dr. Tim Calahan, Chief Technology Officer at Michigan Medicine, shares a bold vision about how cloud migration is reshaping healthcare infrastructure and unlocking innovation. Dr. Calahan also shares why he's passionate about “getting healthcare out of the data center business.” Watch the video version here. What you'll learn in this episode: Why healthcare organizations are moving out of traditional data centers The benefits of public cloud vs. private cloud in healthcare How Michigan Medicine is executing an unprecedented Epic EHR migration Built-in public cloud tools like AI, machine learning, and advanced security How shifting IT infrastructure to the cloud can move the workforce closer to patient care This episode is a must-listen for healthcare executives, CIOs, CTOs, IT leaders, and clinicians who want to understand the future of digital health, health IT, and healthcare infrastructure. Connect with Dr. Calahan on Linkedin at https://www.linkedin.com/in/dr-tim-calahan Find Dr. Calahan's work at https://www.uofmhealth.org Subscribe and stay at the forefront of the digital healthcare revolution. Watch the full video on YouTube @TheDigitalHealthcareExperience The Digital Healthcare Experience is a hub to connect healthcare leaders and tech enthusiasts. Powered by Taylor Healthcare, this podcast is your gateway to the latest trends and breakthroughs in digital health. Learn more at taylor.com/digital-healthcare About Us: Taylor Healthcare empowers healthcare organizations to thrive in the digital world. Our technology streamlines critical workflows such as procedural & surgical informed consent with patented mobile signature capture, ransomware downtime mitigation, patient engagement and more. For more information, please visit imedhealth.com   The Digital Healthcare Experience Podcast: Powered by Taylor Healthcare Produced by Naomi Schwimmer  Hosted by Chris Civitarese Edited by Eli Banks Music by Nicholas Bach  

Lindsey S. Mignano is the founder of SSM Legal, an entrepreneurial Silicon Valley corporate lawyer representing emerging technology companies and industry-adjacent firms and small businesses. Her practice spans technology company business formation and expansion into US markets, M&A (flips, entity or asset sales), commercial and technology transactions, and venture financing. Lindsey has been recognized as a “Rising Star” by Super Lawyers every year from 2016-2024, an honor awarded to only 2.5% of attorneys under the age of 40. In 2025, she was awarded the Super Lawyers distinction for the first time at the age of 40, an honor awarded to only 5% of attorneys. Separate from her law practice, Lindsey speaks often about diversity issues in the fields of law, tech, and venture. In 2023, Lindsey founded Venture Betches, a venture fund of funds, and Syndicate Betches, a real estate syndicate fund of funds, both with a social justice mission to bring investment opportunities to historically underrepresented accredited limited partners who identify as female and/or BIPOC/minorities.