Just Curious: Applied AI for Value Creation

Most of the AI conversation in private equity has been about sourcing, diligence, and value creation. But a quieter transformation is underway inside portfolio teams — closing the gap between when something goes wrong at a portfolio company and when the GP actually finds out.Stu is joined by Yann Magnan, CEO and Co-Founder of 73 Strings (AI-powered valuation and monitoring platform, backed by Goldman Sachs, Blackstone, Fidelity International, Golub, and Hamilton Lane), and Joe Zein, Co-Founder of Soal Labs (custom AI infrastructure for PE and private credit). One builds the platform. One builds the custom architecture that sits around it. Together they lay out why portfolio monitoring is uniquely hard to automate, and what operators should actually do next.You'll Learn:Why the real bottleneck in portfolio monitoring is infrastructure, not cadence — and why LP demand for weekly/daily reporting is about to force the issueWhat a governed data model actually requires (auditability, versioning, rules, entity resolution) and how it differs from a pile of Excel filesWhy private capital needs 100% accuracy, not 99.5%, and what that means for how LLMs get deployedWhen lighter, cheaper models beat frontier LLMs — and the case for combining ML, NLP and LLMs inside a single ingestion pipelineWhy "vibecoded" portfolio monitoring tools fail the moment they touch real LP reporting — and how to think about buy vs. buildThe entity-resolution problem (the same company named three different ways across 73 Strings, Salesforce, and your file system) and how to solve itWhat changes in 18 months: daily mark-to-market, AI-surfaced alerts in your inbox, and the prerequisite data foundation that makes it possibleChapters: 00:00 – Intro & the 60-day information gap 02:33 – Why monthly monitoring is brutal: data, process, bandwidth 06:10 – The real bottleneck at the GP: how reports actually get assembled 09:20 – Best and worst case timelines for a quarterly close 10:44 – Is the problem cadence, or infrastructure? 13:40 – Signals: what shows up before EBITDA moves 18:57 – New data sources, covenants, and the credit boom 21:31 – Why "vibecoded" monitoring tools fail 25:20 – The 100% accuracy problem in private capital 26:55 – What a robust data model actually looks like 29:45 – Moving from file systems to governed structured data 35:49 – Entity resolution across 73 Strings, Salesforce, and the file system 37:00 – Light vs. frontier LLMs: which do you actually need? 40:17 – Confidentiality, enterprise plans, and the open-source option 43:59 – What most people miss about AI and portfolio monitoring 46:29 – Portfolio monitoring in 18 months 49:35 – One thing to start doing right now🎧 Listen on Spotify: https://open.spotify.com/show/3OlTNvh2FGlE4VJyCrMJVE 📺 Watch on YouTube: https://www.youtube.com/@JustCuriousAI 🔗 More Expert More interviews: https://checkpluris.com/expert-interviewsJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jonathan Hansing is the co-founder of Wallabi, a data, technology, and AI strategy firm helping growth-oriented mid-market companies go AI-native. His team works with CEOs, COOs, and CIOs who feel the pressure to do something with AI — but need a clear path from experimentation to execution. This conversation is full of sharp frameworks and hard-won patterns from the field.You'll Learn:Why "sprinkling AI" is simultaneously a signal of opportunity and a warning sign — and how to tell the differenceHow to assess whether a leadership team actually has the appetite for real AI transformation (not just the desire for it)What the J-curve of technology adoption means for AI specifically — and why Jonathan believes companies have about two years to get on the right side of itThe difference between a company that uses AI and one that is genuinely AI-native — and the single most important shift in mindset that separates themA detailed case study: how a media and events company's request for an email automation workflow revealed — layer by layer — a need for full data architecture overhaul, delivered in 8 weeksChapters:00:00 – Intro00:37 – What Jonathan hopes listeners take away: 10,000 prompts is the new 10,000 hours02:16 – Who is Jonathan Hansing / what is Wallabi04:00 – The Wallabi platform: forward-deployed coaches backed by AI06:30 – A machine learning case study: 18-month problem solved in a week07:03 – The journey: West Point → Army → Narrative Science → Salesforce → Wallabi10:08 – "Sprinkling AI": green flag and red flag12:35 – How Wallabi assesses appetite: the 2-week sprint approach17:03 – Data philosophy: use case first, architecture second18:20 – What's happening beneath the surface for pressured CEOs20:48 – The J-curve: from 20 years to 2 years25:03 – Dual Transformation: managing two change curves at once25:49 – AI-native vs. companies that use AI28:00 – Case study: media & events company — the layered problem33:09 – What they built on top: Snowflake Intelligence, Tableau, reverse ETL34:15 – Claude Code and context management: shared learning across repos36:04 – The ROI of AI is the ROI of WiFi38:09 – The bifurcation: who becomes unstoppable vs. who plateaus41:03 – One thing to remember: 10,000 prompts is the new 10,000 hours🔗 Connect with Jonathan Hansing: https://www.linkedin.com/in/jonathanhansing🔗 Explore Wallabi: https://www.wallabi.ai🔗 Explore more interviews: https://checkpluris.com/expert-interviewsJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Justin Massa and Jason Rubinstein are the co-founders of Remix Partners, an AI strategy consultancy that has now run 32+ kickstarts with small and medium-sized businesses across sectors and geographies. Their perspective is grounded in what actually works — not what looks good in a slide deck — and this conversation is full of practical frameworks for PE investors and operators trying to move AI from an experiment into the business.You'll Learn:Why executive engagement is the single non-negotiable success factor in any AI rollout, and what it actually looks like in practiceThe difference between augment and automate — and why 95% of consulting firms stop at automation when the real leverage is in augmentationHow to use a three-tier deployment framework (Experiment / Pilot / Implement) to prioritize where AI goes next, and why you need to revisit it every quarterWhat "agent-legible" means — restructuring business information so agents can navigate it efficiently — and a simple mental model for where to startA detailed manufacturing case study: how a 70-year-old custom parts company cut its RFQ turnaround time nearly in half using a Claude Code workbench built in 3.5 weeksChapters: 00:00 – Intro00:33 – Welcome & what Justin and Jason hope listeners take away01:41 – Who are Justin & Jason / Remix Partners origin03:19 – Jason's background and why they're doing this together04:36 – Reflecting on the past year: what changed in the market07:21 – What's driving the shift in appetite for AI11:50 – Going wide vs. going deep on AI opportunities12:55 – Data on AI adoption: where companies actually are14:42 – Why small businesses are now advantaged over enterprise15:39 – Operationalizing AI: the Remix kickstart approach18:21 – Executive engagement as the #1 success factor19:13 – Show and tell culture: banning secret cyborgs21:33 – How the approach scales from SMBs to Fortune 2523:56 – The leader's mandate: making time for AI25:03 – What went wrong with other consultants26:48 – The augment vs. automate framework28:07 – Getting from automation to augmentation30:33 – The jagged frontier and workforce implications31:55 – How to navigate capabilities without a static view33:35 – Deployment zones: Experiment / Pilot / Implement35:29 – How zones shift quarterly / software stack decisions37:50 – Manufacturing case study: the setup40:26 – What they built (workbench in Claude Code, RFQ automation)42:54 – Who was involved across the organization44:27 – Impact: clock speed and capacity nearly halved46:00 – Engineers' time reallocation; divorcing revenue from headcount47:33 – Agent legibility: what it means and why it matters49:38 – Making your business agent-legible: the practical how52:54 – This year we edit documents, we don't create them53:32 – Where to start for a 50-person company56:16 – Plug into your core work application and play58:07 – What happens to companies that don't experiment now59:11 – Playing to Win in an AI era: differentiation AND low cost01:02:33 – ClosingWatch on YouTube: https:/Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Kris Krisco, Co-founder of Synopsis, is building AI-native data infrastructure designed specifically for the middle market. After scaling and selling a company under private equity, he saw firsthand why most AI initiatives fail — not because of ambition, but because of broken data foundations. In this episode, he explains how to move from fragmented systems and unreliable dashboards to real-time, operational AI that actually drives EBITDA.You’ll LearnWhy 97% of middle-market AI projects fail — and the hidden infrastructure gap most companies ignoreThe critical role of master data management (MDM) and entity resolution in making AI outputs trustworthyHow AI agents can replace months of traditional data engineering work with one-week iteration cyclesReal examples of workflow automation that reduce operational waste and improve field execution in real timeHow private equity-backed companies are using AI in live board meetings to answer strategic questions instantlyChapters00:00 Intro01:00 Why Most AI Initiatives Fail04:40 The Synopsys Approach to Data Infrastructure10:40 The MDM Problem No One Talks About17:15 How Much of Your Data Are You Actually Using?20:45 Workflow Automation & Real-World Use Cases25:15 Disaster Recovery Case Study33:00 AI Inside Private Equity Board Meetings36:30 The Future: Rule of 40 Becomes Rule of 70+LinksExplore more expert interviews: https://checkpluris.com/expert-interviewsWatch on YouTube: https://youtu.be/a6H8SxJTsOcConnect with Kris Krisco: https://www.linkedin.com/in/kris-krisco/Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Mollie Amkraut Mueller, Founder of Watch Me AI and former strategist at IDEO and EY, helps non-technical leaders turn AI into a chief of staff, analyst, and revenue engine. In this episode, she breaks down a practical, business-first approach to AI adoption—showing how one recorded meeting can become 10 high-value assets. If you lead a team or operate in the middle market, this is a tactical blueprint for saving time, increasing output, and unlocking ROI without hiring a dev shop.You’ll LearnHow to turn a single meeting transcript into LinkedIn posts, proposals, client deliverables, and course content in minutesWhy most AI projects fail—and how to scope high-ROI use cases that actually stickA simple diagnostic framework to uncover 1–10 immediate AI opportunities inside any workflowHow off-the-shelf tools like Claude and Relay can replace expensive, over-engineered automation projectsA real-world PR agency case study that cut multi-hour manual research down to 10 minutes per client requestChapters00:00 Intro01:58 Mollie’s background and founding WatchMe AI05:09 The 90-minute AI diagnostic that reveals hidden ROI12:17 One transcript → 10 revenue-generating assets18:55 Why jumping into automations can backfire20:32 PR agency case study: automating conference research25:16 Busting myths about AI adoption29:09 Who should start using AI nowLinksWatch on YouTube: https://www.youtube.com/watch?v=XEP3Vs5ml4gConnect with Mollie Amkraut Mueller: https://www.linkedin.com/in/mollieamkraut/Explore more on Just Curious https://www.justcurious.io/articles/ai-for-non-technical-leaders-turn-one-meeting-into-10-revenue-generating-assetsJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Ryan Kurt, CEO & Founder of The AI Lab, advises middle-market CEOs on how to turn AI from hype into measurable operational advantage. A 13-year veteran of generative AI, he’s helped leaders move beyond “AI strategy decks” to real workflow transformation — including a healthcare network that used computer vision to improve care quality and performance-based pay with 99% accuracy. His perspective is clear: the technology isn’t the hard part — leadership ownership is.You’ll Learn• Why most AI initiatives fail because CEOs delegate ownership instead of leading transformation themselves• How to rebuild workflows from first principles instead of layering AI onto broken processes• What “total ownership” actually means — and why third-party vendors can’t carry your AI strategy• How agentic workflows unlock capacity by automating repetitive work before it hits your desk• A behind-the-scenes case study of using computer vision and human-in-the-loop systems to improve care quality, culture, and compensationChapters00:00 Intro01:00 Ryan’s path from early AI startup to founding The AI Lab04:15 Why “AI strategy” is the wrong starting point08:10 The leadership readiness test most companies fail12:00 What total ownership actually looks like18:00 Why agentic workflows change the economics of work23:00 Case study: Using AI to improve caregiver performance27:30 Human-in-the-loop systems and hybrid AI architecture30:00 Cultural and operational impact31:45 How to sequence AI adoption the right way34:25 Who The AI Lab works withLinksWatch on YouTube: https://youtu.be/bdSq4S2_PZUConnect with Ryan Kurt: https://www.linkedin.com/in/ryankurt/Explore more interviews: https://www.justcurious.io/articles/how-ai-caught-what-bonuses-training-and-pay-raises-couldnt-fix"Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Adam Schwartz, Co-founder and CEO of Parable, explains why most enterprise AI initiatives fail before they ever touch the P&L. Drawing on firsthand work with Fortune 500 and private equity–backed companies, he breaks down how hidden operational inefficiencies block real transformation—and what leaders must measure to unlock durable AI-driven value.You’ll LearnWhy executives consistently misjudge how teams actually spend their time—and how that blind spot derails AI strategyHow “keep-the-lights-on” work and operational debt quietly consume 50–70% of enterprise capacityWhy data warehouses and dashboards lack the context required for effective AI agents and decision-makingHow mapping work at the activity level enables AI use cases to be prioritized by ROI, not intuitionWhat Sunrun uncovered when it quantified technical and operational debt—and how that led to $80M+ in savingsChapters00:00 Intro01:33 Why leaders lack visibility into real work05:12 The hidden cost of “keep the lights on” work09:10 Why data warehouses fail at operational understanding13:20 What a contextual work graph actually looks like18:29 Measuring AI impact beyond adoption23:46 Operational debt and resource allocation30:01 Sunrun case study: uncovering $80M in inefficiencies35:43 AI vs. process change—what to automate and why41:57 The mindset shift leaders need for AI at scaleLinksWatch on YouTube: https://youtu.be/zDDspYqT_7oConnect with Adam Schwartz: https://www.linkedin.com/in/adamgregoryschwartz/Explore more interviews: https://www.justcurious.io/articles/how-sunrun-found-80m-in-hidden-costs-by-finally-understanding-its-dataJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Arman Hezarkhani is the Co-founder & Managing Partner of Tenex, an AI transformation firm helping middle-market and growth companies turn AI from hype into real P&L impact. Drawing from experience scaling Google’s cloud AI tools and building venture-backed startups, Arman breaks down how leaders can actually operationalize AI — not just talk about it. This episode is a practical guide for investors and operators who want measurable results, fast.You’ll LearnWhy AI adoption is easy for individuals but structurally hard for organizations — and how to close that gapHow to identify high-ROI AI use cases by starting with business goals, not technologyWhat “AI slop” looks like in practice and how to avoid wasting capital on vaporwareWhy Tenex charges on output (story points) instead of hours — and how incentives unlock 10x productivityHow to get your first AI win inside a company to build momentum and executive buy-inChapters00:00 Intro00:49 Arman’s background and founding Tenex02:30 Why AI is different from past tech waves05:26 What AI changes — and what it doesn’t — in business07:08 How companies should prepare for an AI-native future09:01 How Tenex identifies and executes AI opportunities12:15 Diagnostic process and opportunity mapping15:13 Why CEO-level buy-in is critical16:31 The Tenex output-based business model21:28 Generative AI, agents, and AI-powered software builds23:25 Avoiding “AI slop” and navigating the AI bubble27:00 Build vs. buy decisions in an AI world28:39 Real client example: AI-driven revenue and efficiency gains33:24 Ruthless focus on business goals34:02 Advice for new Heads of AILinksWatch on YouTube: https://youtu.be/xRV_OnkK9eAExplore more interviews: https://www.justcurious.io/Connect with Arman Hezarkhani: https://www.linkedin.com/in/ahez/Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Evan Glaser, Founder & CEO of Alongside AI, joins Just Curious to break down how middle-market companies can actually deploy AI, without blowing up risk, compliance, or trust. Drawing on a decade of Fortune 100 experience, Evan explains why governance isn’t a blocker to AI value creation, but the accelerator most operators are missing.You’ll LearnWhy AI governance is the fastest way to unlock real productivity—not slow it downHow to design practical AI guardrails that let teams innovate safely and move fasterWhere middle-market companies typically underestimate their AI risk exposureHow to turn siloed institutional knowledge into a scalable, AI-powered assetA real-world case study showing how AI reduced onboarding time and unlocked new revenueChapters00:00 Intro01:24 Why middle-market leaders struggle to start with AI02:59 Governance as an accelerator, not a brake04:41 Defining AI guardrails that actually work06:47 Common governance gaps and blind spots09:03 What “good” AI governance looks like in practice14:02 Unlocking trapped institutional knowledge with AI19:59 Case study: AI-powered onboarding and faster ramp times30:23 Turning AI questions into a new advisory revenue stream33:54 The risks of shadow AI36:13 Lessons from regulated industries that apply everywhereLinksWatch on YouTube: https://youtu.be/OXYdxzPgPKgConnect with Evan Glaser: https://www.linkedin.com/in/glaserevan/Explore more interviews: https://www.justcurious.io/experts/evan-glaserJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Alex Gruebele and Chandler Gonzalez, co-founders of Tau9 Labs, build custom AI systems that solve the messy, high-value problems generic manufacturing software can’t touch. With roots in robotics, hyperscale software, and logistics, they focus on the workflows where context matters most—quoting, downtime, document analysis, and technician knowledge. Their work shows how applied AI can transform mid-market industrial operations in months, not years, by fitting the way factories actually run.You’ll LearnWhy generic SaaS breaks in manufacturing—and how custom AI can match real-world workflows without forcing process changes.How decades of unstructured documents hide the root causes of downtime, warranty costs, and defects—and how AI can surface them.A practical approach to turning vague “AI requests” into solvable, ROI-positive operational problems using on-site discovery and the five whys.How AI-accelerated engineering compresses build cycles from quarters to weeks, enabling tools like instant quoting platforms.When to build vs. buy: the signals that indicate a custom solution will outperform configurable off-the-shelf tools.Chapters00:00 Intro01:00 Backgrounds & the origin of Tau9 Labs03:20 Why manufacturing lags in software adoption05:10 Common operational problems & unstructured data07:15 Downtime, tribal knowledge, and automation08:50 Quoting workflows and workflow automation09:50 How Tau9 diagnoses the “real” problem12:20 On-site discovery and the five whys15:20 Case study: injection molding quoting platform18:10 Designing for speed and user behavior20:15 Building the platform in four months22:50 Results: conversion lift & revenue impact25:10 Build vs. buy in industrial AI28:45 Why on-site U.S. engineers outperform remote teams31:20 How AI changes software design principles33:50 Who Tau9 Labs is best suited to help35:50 ClosingLinksExplore more interviews: https://www.justcurious.io/articles/how-tau9-labs-helped-a-manufacturer-cut-quoting-time-from-hours-to-seconds----and-double-win-ratesWatch on YouTube: https://youtu.be/njuUtQucqHUConnect with Alex Gruebele: https://www.linkedin.com/in/alexgruebele/Connect with Chandler Gonzalez: https://www.linkedin.com/in/chandlergonzales/Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Felix Rösner, Co-founder of Marble AI, builds AI-driven workflow “clones” that reveal what really happens inside complex enterprise operations. His team helps private equity operators and middle-market leaders uncover hidden inefficiencies, quantify real ROI, and automate with precision instead of guesswork. In this episode, Felix shares why deep context—not tools—is the final moat in AI-enabled organizations.You’ll LearnHow capturing keystrokes and screen activity uncovers the real workflow variations that break most automation efforts.Why PE roll-ups routinely misjudge operational reality—and how AI clones surface true time, cost, and redundancy patterns.How sharing internal best practices (revealed through data) can unlock major efficiency gains even before automation begins.How to translate thousands of workflow observations into programmatic specifications for reliable, end-to-end digital workers.The specific types of repetitive, customer-facing tasks where automation consistently returns 100–250 hours per month to teams.Chapters00:00 Intro01:03 Felix’s background and Marble AI’s mission03:12 Why context—not tools—is the last AI moat05:06 What it means to instrument real workflows07:30 The insight that sparked Marble’s approach10:31 Why PE roll-ups struggle to see operational reality12:24 AI clones vs. traditional process diagrams13:34 Balancing workflow capture with privacy and compliance15:21 Signals a company doesn’t understand its operations17:03 Case study: diagnosing a PE-backed roll-up20:40 Deploying the capture stack across teams23:43 What Marble does with the collected data26:27 Findings: redundancy, best practices, and ROI34:05 The 40% redundancy insight37:26 Practical advice for operations leadersLinks• Watch on YouTube: https://youtu.be/sc-A0MPiZxE• Connect with Felix Rösner: https://www.linkedin.com/in/felix-roesner/• Explore more interviews: https://www.justcurious.io/articles/how-marbles-ai-clones-uncovered-40-redundant-work-and-saved-250-hours-monthJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jack Weissenberger, Co-founder & CTO of Ciridae, shares how his team rebuilds core systems and deploys AI agents that remove bottlenecks across finance, operations, and project management. Ciridae works with private-equity-backed companies to identify the real constraints inside a business and replace slow, manual workflows with AI-native software built in days, not months. Jack’s perspective matters because he’s led AI teams at Apple and Salesforce-acquired 10X and now drives full-stack AI transformations in the middle market.You’ll Learn • How to identify high-leverage AI opportunities that sit behind the obvious pain point—like uncovering that insurance negotiations, not AR, were the true constraint in a restoration business. • Why unscoped, natural-language workflows (invoice routing, proposal comparisons, nuanced judgment tasks) are often the best candidates for AI agents. • How AI-native platforms shrink traditional timelines—enabling full-stack applications, including ERP components, to be rebuilt in days or weeks instead of quarters. • The operational impact of linking AI automation directly to key financial levers: cycle time, DSO, throughput, and leadership bandwidth. • Why data readiness—not model quality—is the silent blocker in most failed AI rollouts, and what companies must do before any automation can work.Chapters 00:00 Intro 01:00 What Ciridae Does 02:48 Why the Middle Market Is Ripe for AI 03:44 Inside the Ciridae Platform 05:04 How Clients Engage & How Audits Work 07:03 Identifying Unscoped Problems for AI 08:44 Why AI Projects Fail 11:08 Rebuilding AI-Native Sources of Truth 12:39 How Fast Can You Rebuild an ERP? 14:13 Where Custom Software Is Heading 15:26 Why Finance & AP/AR Are Perfect for Automation 16:43 Why Home Services Companies Are a Strong Fit 18:29 What “Large Enough” Means for AI Transformation 19:02 Case Study: Uncovering the Real Bottleneck 20:21 Automating Insurance Rebuttals 21:31 Deploying a Production System in 48 Hours 22:42 How AI Cut a 3-Hour Workflow to 10 Minutes 24:18 How This Solution Could Double Enterprise Value 25:32 Staying Open-Minded in AI Audits 26:33 Data Readiness & Integrations 27:59 Who Should Reach Out to Ciridae 29:01 Practical First Steps for LeadersLinks • Watch on YouTube: https://youtu.be/2PXce31N3IY?si=5PCQaM6DcS9236aM • Connect with Jack Weissenberger: https://www.linkedin.com/in/jack-weissenberger-9b8549144/ • Explore more interviews: https://www.justcurious.io/articles/how-ai-cut-a-3-hour-workflow-to-10-minutes-for-a-home-restoration-companyJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jordan Gurrieri, Co-founder & CEO of BlueLabel, explains how mid-market and enterprise operators can finally escape pilot purgatory and deploy AI systems that scale reliably. Drawing on two decades of automation experience and hundreds of shipped products, he breaks down why AI initiatives fail, how to design for workflow fit from day one, and what it takes to turn tribal knowledge and inconsistent pilots into production-grade, agentic workflows.You’ll Learn:Why AI pilots break when more than a handful of people rely on them—and how to rebuild them for consistency, accuracy, and cost efficiency.How to identify high-friction workflows by mapping real user behavior, pain points, and dependency chains.How to convert tribal knowledge into durable, queryable agentic systems that support frontline teams in real time.Why agentic, workflow-embedded AI drives true competitive advantage while personal productivity tools do not.How a regional telecom automated dispatch operations and doubled field technician throughput with an AI-powered workflow system.Chapters:00:00 Intro00:32 Jordan’s background & BlueLabel’s focus02:09 How early automation shaped his AI worldview03:31 Why pilots break when scaling AI05:05 Common traps between pilot and production07:15 What scaling AI actually requires10:26 Personal productivity vs. organizational advantage12:45 Telecom case study: the dispatch bottleneck15:02 Agentic tools for field technicians17:59 Change management inside legacy workflows19:36 Rebuilding the pilot on a scalable API foundation21:50 Lessons for future AI deployments23:35 Identifying high-fit workflows26:08 What makes a strong AI use case28:05 A myth about AI implementation30:15 Who should work with BlueLabel31:52 Advice for leaders under AI pressureLinks:Explore more interviews and Jordan Gurrieri's expert profile:  https://www.justcurious.io/experts/jordan-gurrieriConnect with Jordan Gurrieri: https://www.linkedin.com/in/jordangurrieri/Watch on YouTube: https://youtu.be/T7lhyDkZca0Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Greg Shove, CEO of Section, breaks down why enterprise AI adoption remains stuck in low single digits—and what leaders must do to unlock meaningful productivity gains. With experience building six companies and training global workforces in applied AI, Greg explains how culture, workflows, and leadership behavior—not tools—determine whether AI becomes a competitive advantage.You'll Learn:Why only ~9% of knowledge workers are truly AI-proficient and how to move teams from anxious to confidentThe biggest mistakes enterprises make when rolling out tools like Copilot and ChatGPTHow workflow redesign unlocks real value and why “lighthouse” use cases accelerate adoptionHow executives can use AI as a strategic thought partner for better decisionsHow AI will reshape team structure, performance distribution, and talent development over the next five yearsChapters:00:00 Intro01:09 Why Greg pivoted Section to AI03:29 Comparing AI to past tech waves07:22 How AI changes cognitive work09:14 The AI-proficient workforce11:16 Why enterprise adoption is stalling18:49 How to get from 8% to 50% adoption25:19 Why AI isn’t “just software”27:53 AI as a strategic advisor33:40 Using AI to prep for board meetings37:20 How AI will reshape teams43:32 Who Section helpsLinks:Explore more interviews and Greg Shove's expert profile: https://www.justcurious.io/experts/greg-shoveConnect with Greg Shove: https://www.linkedin.com/in/gregshove/Watch on YouTube: https://youtu.be/4bXULTB9ySA Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jay Singh, Co-founder & CEO of Casper Studios, breaks down how real organizations—hedge funds, PE-backed companies, and growth-stage startups—are actually deploying AI that gets used. Drawing on deep experience building modular, production-grade systems, he explains why small, workflow-anchored wins consistently outperform AI moonshots and how companies can integrate AI without chaos, panic, or overreach.You’ll Learn:Why modular, workflow-specific automation beats monolithic “AI platform” builds.How to assess whether an organization is truly ready for AI adoption—from data quality to executive behavior.How to identify the highest-leverage workflows by mapping real user behavior, not theoretical use cases.How applied AI cuts research and analysis time by 50–80% when integrated directly into existing systems.How voice-based agents can surface hidden workflow pain and accelerate discovery across large teams.Chapters:00:00 Intro00:33 Jay’s background and what Casper Studios does01:55 Why he left LinkedIn to build an AI implementation studio03:23 Common AI mistakes across startups and enterprises05:02 What “the middle ground” of AI adoption looks like06:49 How company behavior around AI has shifted08:40 Why clients come to Casper and what problems they bring10:09 How clients identify workflows worth automating11:26 Signals a company is (or isn’t) ready for real AI adoption13:49 Hedge fund case study introduction15:55 Why modular systems outperform monolithic builds18:15 Module 2 and 3: transcription, synthesis, and decision support20:13 How they ensure recommendations stay grounded in logic22:24 Time savings and impact23:29 How long it takes to get to production24:42 Integrating with real enterprise stacks27:02 Why ambitious projects often stall—and when moonshots make sense30:18 How singles and doubles build momentum32:15 The first question leaders should ask their teams33:41 A high-leverage first AI project35:41 Who should reach out to Casper StudiosLinks:Explore more interviews and Jay Singh's expert profile:  https://www.justcurious.io/experts/jay-singhConnect with Jay Singh: https://www.linkedin.com/in/jaysingh10125/Watch on YouTube: https://youtu.be/o7duyoDZUS4 Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Chris Taylor, Co-founder & CEO of Fractional AI, explains how private equity–backed companies are using applied AI to drive measurable operational impact—not experiments. Drawing from deep experience building AI-native services and deploying production systems across dozens of portcos, Chris breaks down how incumbents can move fast, automate real workflows, and turn AI into cost savings, productivity, and defensibility.You’ll Learn:How to identify the workflows where AI can actually deliver value—not wishful “AI ideas.”Why incumbents, not AI-first startups, are often best positioned to win with generative AI.How to evaluate feasibility, scope, and ROI so projects move quickly from idea to production.Why PE-owned companies are ideal AI adopters and how to navigate partnership with SMEs and engineering.How one portco achieved an 84% cost reduction by automating product-taxonomy mapping with an AI-first workflow.Chapters:00:00 Intro00:32 What Fractional AI does04:29 How companies identify real AI opportunities06:37 Why PE-backed companies adopt AI differently09:15 Partnering with SMEs and engineers11:50 Common misconceptions and early mistakes20:35 Case study: automating product-taxonomy mapping26:30 Deployment and internal reaction29:03 Cost savings and impact31:02 What AI means in PE diligence34:41 First 30-day steps for CEOs36:54 Who Fractional AI works best withLinks:Explore more interviews and Chris Taylor's expert profile: https://www.justcurious.io/experts/chris-taylorConnect with Chris Taylor: https://www.linkedin.com/in/taylorcd/Watch on YouTube: https://youtu.be/sVb3QmqucEg Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Csongor Barabasi, CEO of Bonsai Labs, helps private equity–backed B2B software companies ship AI products that generate real EBITDA impact. Working with top global PE funds, his team has repeatedly taken companies from idea to paying customers in as little as a few weeks—often unlocking new ARR and defending market share against AI-native competitors. He explains why most AI efforts stall, how to validate use cases fast, and what it takes to turn domain knowledge into production-grade AI workflows.You’ll Learn:How to validate high-ROI AI use cases in 4–6 weeks without waiting on long, expensive data-transformation projects.Why evaluation datasets, first-answer correctness, and weekly iteration cycles are essential for launch-ready AI.How to redesign legacy processes through an AI-native lens to reduce busywork and unlock revenue opportunities.The engineering practices Bonsai Labs uses to reach production in 4–12 weeks, even in complex domains.How incumbents can neutralize AI-native challengers by pairing distribution advantages with elite execution speed.Chapters:00:00 Intro00:42 Who Csongor Is & What Bonsai Labs Does03:04 Career Path & Why He Built Bonsai Labs06:15 Common Mistakes in AI Adoption08:04 How Leaders Should Approach POCs09:13 CTO Concerns & Engineering Challenges11:18 People, Process & Product in AI Transformation13:53 The Four-Step Build Process17:26 Legal AI Case Study20:24 Revenue Impact & Lessons for Incumbents23:49 PE-Backed Legacy Software Case Study26:21 How Bonsai Labs Differs From Dev Shops30:53 Misconceptions About Launching AI Products32:28 Building High-Performing AI Teams34:28 What Leaders Should Stop Doing With POCs36:02 Who Should Reach Out to Bonsai LabsLinks:Explore more interviews and Csongor Barabasi’s expert profile: https://www.justcurious.io/experts/csongor-barabasiConnect with Csongor: https://www.linkedin.com/in/barabasicsongor/Watch the full conversation on YouTube: https://youtu.be/LEfWNjaT_LgJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Osman Ghandour, Co-founder & CEO of Soal Labs, helps private equity and private credit firms turn chaotic, spreadsheet-driven processes into unified, AI-powered workflows. Working with middle-market teams drowning in SIMs, fragmented systems, and delayed reporting, he shows how well-designed data foundations and targeted automation can unlock 50% more deal capacity without adding headcount. In this conversation, he breaks down what actually drives time-to-value and why AI only works when it’s built directly into the way investment teams operate.You’ll Learn:Why most firms struggle to move from AI ideas to execution—and how to bridge the gap with standardized workflows.How private equity and private credit differ in their AI needs, and what each must prioritize to move faster.Where diligence and reporting break down, and which parts of underwriting can be automated for immediate wins.A four-stage framework (align → blueprint → deliver → expand) for bringing AI into core investment functions.How a private credit firm cut memo-creation time by 70% and increased deal capacity by 50% through systematization and automation.Chapters:00:00 Intro00:42 What Soal Labs Does03:04 Why Osman Entered the PE/PC Data Space05:06 Indicators a Firm Is Truly Forward-Looking07:13 Biggest Bottlenecks in Diligence & Reporting09:08 How AI Conversations Have Shifted10:41 How Middle-Market Funds Should Prioritize AI12:12 The Four-Stage Transformation Framework15:25 Time-to-Value & What Can Be Done in Weeks16:11 Private Credit Case Study: The Initial Problem17:32 Diagnosing the Root Causes19:39 System Design & Integration Choices20:48 Trade-Offs: Standardization vs. Flexibility22:19 Driving Adoption Through Co-Design23:22 Results: 70% Faster Memos & 50% More Deal Capacity24:27 Lessons Learned25:37 Misconceptions About AI Platforms26:37 Why Projects Get Stuck27:46 Moving Teams From “Cool Idea” to Business Impact28:42 CloseLinks:Explore more interviews and Osman Ghandour's expert profile: https://www.justcurious.io/experts/osman-ghandourConnect with Osman Ghandour: https://www.linkedin.com/in/osman-a-ghandour/Watch on YouTube: https://youtu.be/_-Wt-CGkPxcJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Brandon Gell, Head of Studio at Every, shares how companies move from AI experimentation to true adoption by creating the “magic moments” that make AI indispensable. Drawing from his experience building and selling companies, shipping AI-native products, and advising leadership teams, Brandon breaks down the practical steps operators and investors can use to turn AI into leverage, productivity, and cultural transformation.You’ll Learn:How to uncover high-value workflows by interviewing teams about what they actually do—not their AI ideas.Why magical moments, not abstract training, are the key to durable AI adoption.How to package institutional knowledge into prompts, tools, and GPTs that multiply expertise across an organization.When simple LLM workflows are enough—and when you need agents, automation, or lightweight internal apps.How executive curiosity and cultural pressure accelerate adoption more than any technical investment.Chapters:00:00 Intro02:49 The origins of Every Consulting06:44 How Every’s maker culture shapes consulting11:07 What Every’s studio builds and why it matters13:21 Every’s framework for AI adoption17:22 Creating magical moments20:47 How engagements work28:43 Turning interviews into solutions32:27 Training by building real tools36:25 What makes a workflow a strong AI candidate39:32 Who Every works best with42:55 What’s coming next in AI48:28 Quick wins for teamsLinks:Explore more interviews and Brandon Gell's expert profile: https://www.justcurious.io/experts/brandon-gellConnect with Brandon Gell: https://www.linkedin.com/in/brandongell/Watch on YouTube: https://youtu.be/C1lajIlHVpgJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Ross Hale, CEO of Artium, and Mike McCormick, Artium’s CTO, share how leading organizations are moving from AI experimentation to real production-grade systems. They explain what it takes to build reliable, high-impact AI software in environments where accuracy, governance, and scale truly matter. Their perspective is grounded in deep hands-on work with enterprise and mid-market teams navigating AI adoption today.You'll Learn:How enterprises move from AI proofs-of-concept to production reliability using continuous alignment testingWhy AI-native software requires scientific experimentation before traditional product developmentHow small, senior teams leverage AI-assisted development to deliver outcomes in weeks, and not yearsThe operational differences between building custom AI systems and buying off-the-shelf toolsReal examples of AI workflows transforming healthcare, financial services, and media operationsChapters:00:00 Intro01:04 What Artium Builds and Why AI Changes Everything03:37 Where Enterprises Actually Stand With AI Adoption08:29 How AI Development Differs From Traditional Software10:53 Reducing Uncertainty With a Proof-of-Concept Phase12:47 Turning Experiments Into Production Systems16:59 Ensuring Reliability in Non-Deterministic AI Systems24:43 Build vs. Buy in the Age of AI32:39 Real-World Case Study: Arrive Health36:48 Timelines, Stakeholders, and Scaling AI Products41:19 Who Artium Works With43:37 ClosingLinks:Explore more interviews and Ross Hale's expert profile: https://www.justcurious.io/experts/ross-haleConnect with Ross Hale: https://www.linkedin.com/in/rosshale/Connect with Mike McCormick: https://www.linkedin.com/in/get-to-know-mike/Watch on YouTube: https://youtu.be/qtryqaCaPWkJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Amrit Saxena, CEO of SaxeCap, shares how he and his team have led more than 100 AI transformations and advised over 40 private equity funds on using AI to expand margins, accelerate growth, and reshape value creation. His perspective matters because SaxeCap has pioneered AI-levered buyouts and proven repeatable frameworks for turning workflow inefficiencies and data assets into enterprise value. In this episode, he breaks down what actually drives returns—and what doesn’t—when applying AI inside middle-market businesses.You’ll Learn:How to evaluate AI risk and upside during diligence using business-model signals, workflow analysis, and proprietary data assetsWhy early EBITDA wins within the first 60 days are essential for building AI adoption and organizational momentumHow to quantify value from AI across labor optimization, human-capital augmentation, and AI-driven product expansionThe functional areas where AI repeatedly delivers ROI, especially customer service, operations, and engineeringHow to determine whether an AI transformation can become a defensible moat through proprietary data and distribution advantagesChapters:00:00 Intro01:00 Evolution of value creation in private equity05:15 How SaxeCap supports diligence07:00 Signals of AI risk and opportunity08:20 Speed to EBITDA impact09:50 Transforming legacy or lean organizations12:20 Cost vs. revenue value creation mix14:00 Where AI delivers repeatable ROI15:00 Common mistakes PE firms make with AI17:40 AI transformation examples22:55 Value creation ranges24:55 Generative AI transformation example27:30 Can AI be a moat?30:00 Who should reach out to SaxeCap31:20 Three AI questions for investment committees32:40 ClosingLinks:Explore more interviews and Amrit Saxena's expert profile: https://www.justcurious.io/experts/amrit-saxena"Connect with Amrit Saxena: https://www.linkedin.com/in/amrit-saxena-33432035/Watch on YouTube: https://youtu.be/2UigwwWcl6gJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Justin Massa, Partner & Co-Founder of Remix Partners, helps SMB and mid-market teams translate rapidly evolving AI capabilities into practical workflows that unlock real business value. His perspective matters because he has spent a decade guiding leaders through emerging technology waves and building repeatable frameworks that help organizations identify, experiment with, and operationalize AI in ways that drive competitive differentiation. In this episode, he explains why most executives lack a true on-ramp into generative AI, and how techniques, jigs, and tools provide a structured path from experimentation to scalable impact.You’ll Learn:How to build an “AI on-ramp” that gives leaders strategic context—not just task-level tricksWhy techniques, jigs, and tools form a maturity path for workflow transformationHow to identify the specific AI capabilities tied to a company’s competitive differentiationHow early experimentation accelerates prototyping speed and cross-functional innovationHow to approach ROI rigorously when deciding whether to adopt, buy, or build AI toolsChapters:00:00 Intro01:00 Justin’s background in innovation and AI02:15 The client’s challenge and early skepticism03:40 The on-ramp problem for business leaders06:20 Techniques vs. jigs vs. tools10:50 How leaders decide what to build or buy14:30 Evaluating ROI and tool decisions18:45 Why leaders don’t need deep technical knowledge22:00 Coaching executives to use AI directly24:20 Startup acceleration and rapid prototyping26:45 Advice for leaders beginning their AI journeyLinks:Explore more interviews and Justin Massa's expert profile: https://www.justcurious.io/experts/justin-massaConnect with Justin Massa: https://www.linkedin.com/in/justinmassa/Watch on YouTube: https://youtu.be/smZC_jLk0ZsJust Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jeremy Utley, adjunct professor at Stanford and host of Beyond the Prompt, shares how executives and operators can use AI to unlock creativity, accelerate decision-making, and drive transformational change. His work sits at the intersection of innovation, experimentation, and applied AI, making his perspective especially relevant for private equity leaders and middle-market teams navigating rapid operational shifts. In this episode, he breaks down practical ways AI becomes a strategic partner, not just a tactical tool.You’ll LearnHow AI-powered role-play can prepare leaders for high-stakes conversations and improve organizational outcomes.Why treating AI like a collaborator — not an oracle — dramatically improves idea quality and problem-solving.A structured method for using AI as a strategic thought partner for capital allocation, board prep, and complex decision workflows.How non-technical teams can codify workflows into lightweight GPTs that unlock days — and sometimes weeks — of saved effort.Why experimentation must be a KPI, and how leaders can create a culture where inaction — not failure — becomes the punishable offense.Chapters00:00 Intro00:42 Jeremy’s shift from professor to AI learner03:39 Coaching executives on applied AI05:54 Using AI to prepare for difficult conversations10:02 Expanding executives’ imagination for AI13:22 Strategic use cases for leaders18:19 Modeling AI adoption from the top20:11 How AI amplifies creativity22:39 Collaborating with AI vs. treating it as an oracle24:21 Who benefits most from these tools26:38 National Park Service transformation story30:49 “Use AI to use AI” — the first step33:48 ClosingLinksExplore more interviews and Jeremy Utley's expert profile: https://www.justcurious.io/experts/jeremy-utleyWatch on YouTube: https://youtu.be/ZuUXggPcQygConnect with Jeremy Utley: https://www.linkedin.com/in/jeremyutley/Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.Explore more interviews and connect with experts at https://www.checkpluris.com Subscribe to our newsletter at https://just-curious-ai.beehiiv.com