Proof of Work: AI Value Creation

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 Learn

• Why executives consistently misjudge how teams actually spend their time—and how that blind spot derails AI strategy
• How “keep-the-lights-on” work and operational debt quietly consume 50–70% of enterprise capacity
• Why data warehouses and dashboards lack the context required for effective AI agents and decision-making
• How mapping work at the activity level enables AI use cases to be prioritized by ROI, not intuition
• What Sunrun uncovered when it quantified technical and operational debt—and how that led to $80M+ in savings

Chapters

00:00 Intro
01:33 Why leaders lack visibility into real work
05:12 The hidden cost of “keep the lights on” work
09:10 Why data warehouses fail at operational understanding
13:20 What a contextual work graph actually looks like
18:29 Measuring AI impact beyond adoption
23:46 Operational debt and resource allocation
30:01 Sunrun case study: uncovering $80M in inefficiencies
35:43 AI vs. process change—what to automate and why
41:57 The mindset shift leaders need for AI at scale

Links

• Watch on YouTube: https://youtu.be/zDDspYqT_7o
• Connect with Adam Schwartz: https://www.linkedin.com/in/adamgregoryschwartz/
• Explore more interviews: https://www.checkpluris.com/insights/how-sunrun-found-80m-in-hidden-costs-by-finally-understanding-its-data

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Learn

Why AI adoption is easy for individuals but structurally hard for organizations — and how to close that gap

How to identify high-ROI AI use cases by starting with business goals, not technology

What “AI slop” looks like in practice and how to avoid wasting capital on vaporware

Why Tenex charges on output (story points) instead of hours — and how incentives unlock 10x productivity

How to get your first AI win inside a company to build momentum and executive buy-in

Chapters

00:00 Intro
00:49 Arman’s background and founding Tenex
02:30 Why AI is different from past tech waves
05:26 What AI changes — and what it doesn’t — in business
07:08 How companies should prepare for an AI-native future
09:01 How Tenex identifies and executes AI opportunities
12:15 Diagnostic process and opportunity mapping
15:13 Why CEO-level buy-in is critical
16:31 The Tenex output-based business model
21:28 Generative AI, agents, and AI-powered software builds
23:25 Avoiding “AI slop” and navigating the AI bubble
27:00 Build vs. buy decisions in an AI world
28:39 Real client example: AI-driven revenue and efficiency gains
33:24 Ruthless focus on business goals
34:02 Advice for new Heads of AI

Links

• Watch on YouTube: https://youtu.be/xRV_OnkK9eA
• Explore more interviews: https://www.checkpluris.com
• Connect with Arman Hezarkhani: https://www.linkedin.com/in/ahez/

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Learn

Why AI governance is the fastest way to unlock real productivity—not slow it down

How to design practical AI guardrails that let teams innovate safely and move faster

Where middle-market companies typically underestimate their AI risk exposure

How to turn siloed institutional knowledge into a scalable, AI-powered asset

A real-world case study showing how AI reduced onboarding time and unlocked new revenue

Chapters

00:00 Intro
01:24 Why middle-market leaders struggle to start with AI
02:59 Governance as an accelerator, not a brake
04:41 Defining AI guardrails that actually work
06:47 Common governance gaps and blind spots
09:03 What “good” AI governance looks like in practice
14:02 Unlocking trapped institutional knowledge with AI
19:59 Case study: AI-powered onboarding and faster ramp times
30:23 Turning AI questions into a new advisory revenue stream
33:54 The risks of shadow AI
36:13 Lessons from regulated industries that apply everywhere

Links

• Watch on YouTube: https://youtu.be/OXYdxzPgPKg
• Connect with Evan Glaser: https://www.linkedin.com/in/glaserevan/
• Explore more interviews: https://www.checkpluris.com/insights/how-smart-ai-guardrails-unlock-faster-growth-without-killing-innovation

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Learn

• Why 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.

Chapters

00:00 Intro
01:00 Backgrounds & the origin of Tau9 Labs
03:20 Why manufacturing lags in software adoption
05:10 Common operational problems & unstructured data
07:15 Downtime, tribal knowledge, and automation
08:50 Quoting workflows and workflow automation
09:50 How Tau9 diagnoses the “real” problem
12:20 On-site discovery and the five whys
15:20 Case study: injection molding quoting platform
18:10 Designing for speed and user behavior
20:15 Building the platform in four months
22:50 Results: conversion lift & revenue impact
25:10 Build vs. buy in industrial AI
28:45 Why on-site U.S. engineers outperform remote teams
31:20 How AI changes software design principles
33:50 Who Tau9 Labs is best suited to help
35:50 Closing

Links

• Explore more interviews: https://www.checkpluris.com/insights/how-tau9-labs-helped-a-manufacturer-cut-quoting-time-from-hours-to-seconds----and-double-win-rates
• Watch on YouTube: https://youtu.be/njuUtQucqHU
• Connect with Alex Gruebele: https://www.linkedin.com/in/alexgruebele/
• Connect with Chandler Gonzalez: https://www.linkedin.com/in/chandlergonzales/

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Learn

How 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.

Chapters

00:00 Intro
01:03 Felix’s background and Marble AI’s mission
03:12 Why context—not tools—is the last AI moat
05:06 What it means to instrument real workflows
07:30 The insight that sparked Marble’s approach
10:31 Why PE roll-ups struggle to see operational reality
12:24 AI clones vs. traditional process diagrams
13:34 Balancing workflow capture with privacy and compliance
15:21 Signals a company doesn’t understand its operations
17:03 Case study: diagnosing a PE-backed roll-up
20:40 Deploying the capture stack across teams
23:43 What Marble does with the collected data
26:27 Findings: redundancy, best practices, and ROI
34:05 The 40% redundancy insight
37:26 Practical advice for operations leaders

Links

• Watch on YouTube: https://youtu.be/sc-A0MPiZxE

• Connect with Felix Rösner: https://www.linkedin.com/in/felix-roesner/

• Explore more interviews: https://www.checkpluris.com/insights/how-marbles-ai-clones-uncovered-40-redundant-work-and-saved-250-hours-month

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Leaders

Links
• 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.checkpluris.com/insights/how-ai-cut-a-3-hour-workflow-to-10-minutes-for-a-home-restoration-company

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Intro
00:32 Jordan’s background & BlueLabel’s focus
02:09 How early automation shaped his AI worldview
03:31 Why pilots break when scaling AI
05:05 Common traps between pilot and production
07:15 What scaling AI actually requires
10:26 Personal productivity vs. organizational advantage
12:45 Telecom case study: the dispatch bottleneck
15:02 Agentic tools for field technicians
17:59 Change management inside legacy workflows
19:36 Rebuilding the pilot on a scalable API foundation
21:50 Lessons for future AI deployments
23:35 Identifying high-fit workflows
26:08 What makes a strong AI use case
28:05 A myth about AI implementation
30:15 Who should work with BlueLabel
31:52 Advice for leaders under AI pressure

Links:

• Explore more interviews and Jordan Gurrieri's expert profile:  https://www.checkpluris.com/insights/how-to-turn-ai-experiments-into-enterprise-systems--lessons-from-300-deployments
• Connect with Jordan Gurrieri: https://www.linkedin.com/in/jordangurrieri/
• Watch on YouTube: https://youtu.be/T7lhyDkZca0

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 confident
• The biggest mistakes enterprises make when rolling out tools like Copilot and ChatGPT
• How workflow redesign unlocks real value and why “lighthouse” use cases accelerate adoption
• How executives can use AI as a strategic thought partner for better decisions
• How AI will reshape team structure, performance distribution, and talent development over the next five years

Chapters:

00:00 Intro
01:09 Why Greg pivoted Section to AI
03:29 Comparing AI to past tech waves
07:22 How AI changes cognitive work
09:14 The AI-proficient workforce
11:16 Why enterprise adoption is stalling
18:49 How to get from 8% to 50% adoption
25:19 Why AI isn’t “just software”
27:53 AI as a strategic advisor
33:40 Using AI to prep for board meetings
37:20 How AI will reshape teams
43:32 Who Section helps

Links:

• Explore more interviews and Greg Shove's expert profile: https://www.checkpluris.com/insights/how-ai-is-redefining-leadership-roles
• Connect with Greg Shove: https://www.linkedin.com/in/gregshove/
• Watch on YouTube: https://youtu.be/4bXULTB9ySA 

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Intro
00:33 Jay’s background and what Casper Studios does
01:55 Why he left LinkedIn to build an AI implementation studio
03:23 Common AI mistakes across startups and enterprises
05:02 What “the middle ground” of AI adoption looks like
06:49 How company behavior around AI has shifted
08:40 Why clients come to Casper and what problems they bring
10:09 How clients identify workflows worth automating
11:26 Signals a company is (or isn’t) ready for real AI adoption
13:49 Hedge fund case study introduction
15:55 Why modular systems outperform monolithic builds
18:15 Module 2 and 3: transcription, synthesis, and decision support
20:13 How they ensure recommendations stay grounded in logic
22:24 Time savings and impact
23:29 How long it takes to get to production
24:42 Integrating with real enterprise stacks
27:02 Why ambitious projects often stall—and when moonshots make sense
30:18 How singles and doubles build momentum
32:15 The first question leaders should ask their teams
33:41 A high-leverage first AI project
35:41 Who should reach out to Casper Studios

Links:

• Explore more interviews and Jay Singh's expert profile:  https://www.checkpluris.com/insights/ai-that-actually-gets-used-how-casper-studios-cut-hedge-fund-research-time-by-80
• Connect with Jay Singh: https://www.linkedin.com/in/jaysingh10125/
• Watch on YouTube: https://youtu.be/o7duyoDZUS4 

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-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 Intro
00:32 What Fractional AI does
04:29 How companies identify real AI opportunities
06:37 Why PE-backed companies adopt AI differently
09:15 Partnering with SMEs and engineers
11:50 Common misconceptions and early mistakes
20:35 Case study: automating product-taxonomy mapping
26:30 Deployment and internal reaction
29:03 Cost savings and impact
31:02 What AI means in PE diligence
34:41 First 30-day steps for CEOs
36:54 Who Fractional AI works best with

Links:

• Explore more interviews and Chris Taylor's expert profile: https://www.checkpluris.com/insights/84-cost-savings-30-second-turnarounds-the-pe-playbook-for-production-grade-ai
• Connect with Chris Taylor: https://www.linkedin.com/in/taylorcd/
• Watch on YouTube: https://youtu.be/sVb3QmqucEg 

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-ai.beehiiv.com/