AI models are becoming commoditized, but deploying AI systems that deliver real ROI remains hard. In this episode, Mehmet sits down with Bryan Wood, Principal Architect at Snorkel AI, to unpack why data-centric AI, evaluation, and domain expertise are now the true differentiators.
Bryan shares lessons from working with frontier AI labs and highly regulated enterprises, explains why most AI projects stall before production, and breaks down what it actually takes to deploy AI safely and at scale.
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👤 About the Guest
Bryan Wood is a Principal Architect at Snorkel AI, where he works closely with frontier AI labs and enterprises to design high-quality, AI-ready datasets and evaluation frameworks.
He brings over 20 years of experience in financial services, with a unique background spanning banking, engineering, and fine art. Bryan specializes in data-centric AI, programmatic labeling, AI evaluation, and deploying AI systems in high-compliance environments.
https://www.linkedin.com/in/bryanmwood/
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🧠 Key Takeaways
• Why AI success is less about models and more about data and evaluation
• How enterprises misunderstand ROI and why most projects stall before production
• The difference between benchmark performance and real-world trust
• Why evaluation must be bespoke, not off-the-shelf
• How frontier labs approach data as true R&D
• Why partnering beats building AI entirely in-house today
• What’s realistic (and unrealistic) about autonomous agents in the near term
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🎯 What You’ll Learn
• How to move from AI experimentation to production deployment
• How to design data that reflects real enterprise workflows
• How to identify where AI systems actually fail, and why
• Why regulated industries are proving grounds, not laggards
• How startups can overcome data and talent constraints
• Where AI is heading beyond today’s LLM plateau
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⏱️ Episode Highlights & Timestamps
00:00 – Introduction & Bryan’s background
02:30 – Why data is now the real AI bottleneck
05:00 – Models are commoditized. So what actually matters?
07:45 – Why AI evaluation is harder than building AI
11:30 – Enterprise misconceptions about AI readiness
15:10 – Hallucinations, RAG failures, and finding the real problem
18:40 – Why most AI projects fail to show ROI
22:30 – Partnering vs building AI in-house
26:00 – AI in regulated industries: myth vs reality
30:10 – Startups, cold start problems, and data moats
33:40 – Scaling data operations with small teams
36:00 – What’s next: agents, data complexity, and AI timelines
39:00 – Final thoughts and where AI is really heading
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📌 Resources Mentioned
• Snorkel AI – Data-centric AI and programmatic labeling: https://snorkel.ai/
• Enterprise AI evaluation frameworks
• Frontier AI lab research practices
• MIT studies on AI ROI and enterprise adoption
Live events generate massive attention, yet most venues have no idea who is actually attending. In this episode, Mehmet Gonullu sits down with Matt Zarracina, CEO and Co-Founder of True Tickets, to unpack the hidden infrastructure problem behind ticketing, identity, and audience ownership.
Matt shares how legacy ticketing systems optimized for transactions, not relationships, and why “shadow audiences” have become one of the biggest blind spots in live event tech. The conversation spans SaaS innovation in legacy industries, blockchain learnings, AI-driven personalization, and what it truly takes to build mission-critical infrastructure at scale.
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About the Guest
Matt Zarracina is the CEO and Co-Founder of True Tickets, a ticket custody and identity platform helping venues understand who is actually attending their events.
His background spans the U.S. Naval Academy, helicopter aviation, systems engineering, an MBA, M&A consulting at Deloitte, and corporate innovation leadership before founding True Tickets full-time in 2018.
https://www.linkedin.com/in/zarracina/
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Key Takeaways
• Why most venues only know 30–40% of their real audience
• How “ticket custody” differs fundamentally from ticket sales
• Why legacy ticketing systems were never designed for identity or post-sale visibility
• The real reason ticket resale abuse and bots persist
• How data unlocks personalization, donor growth, and long-term audience relationships
• Why mission-critical SaaS cannot “move fast and break things”
• Where AI fits next: fraud detection, pricing intelligence, and behavioral patterns
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What You’ll Learn
• What the “shadow audience” really is and why it matters
• How True Tickets integrates into legacy ticketing systems without replacing them
• Why frictionless UX is not always the goal and what “optimal friction” means
• How venues can reclaim ownership from secondary markets
• Lessons from building SaaS inside conservative, legacy industries
• Why consultants and operators can become strong founders
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Episode Highlights & Timestamps
(Approximate, optimized for Spotify & YouTube chapters)
• 00:00 – Introduction and Matt’s unconventional journey
• 03:45 – The origin of True Tickets and discovering ticketing’s blind spot
• 07:30 – Defining the “Shadow Audience” problem
• 10:45 – Bots, resale markets, and why legislation alone fails
• 14:00 – Real-world example: turning attendees into donors
• 17:45 – What True Tickets actually does under the hood
• 21:30 – SaaS in legacy industries and mission-critical systems
• 26:00 – Balancing security, friction, and user experience
• 30:45 – The future of ticketing: data, AI, and personalization
• 35:00 – Global expansion and market opportunity
• 38:30 – Founder lessons from consulting to scale-up CEO
• 43:30 – Final reflections and where to learn more
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Resources Mentioned
• True Tickets Website: https://www.true-tickets.com/
• ROI Calculator and Product Demo (available on True Tickets’ site)
• Super Founders by Ali Tamaseb
In this episode of The CTO Show with Mehmet, I’m joined by Ahikam Kaufman, Co-Founder and CEO of Safebooks.ai, a seasoned finance executive turned entrepreneur with deep experience across startups, public companies, and large-scale acquisitions.
We explore why finance has lagged behind other functions in digital transformation, how AI is fundamentally reshaping financial governance, and why the modern CFO is becoming a transformation leader, not just a financial steward.
This conversation goes beyond buzzwords and dives into real-world problems: broken audit trails, fragmented systems, compliance risk, and how AI agents can finally deliver real-time financial truth.
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👤 About the Guest
Ahikam Kaufman is the Co-Founder and CEO of Safebooks.ai.
He began his career in accounting, served as a CFO in Silicon Valley startups, experienced multiple acquisitions including by Hewlett-Packard and Intuit, and spent over a decade as an entrepreneur.
Today, Ahikam is focused on modernizing the Office of the CFO by applying AI to financial data governance, auditability, and compliance at scale.
https://www.linkedin.com/in/ahikam-kaufman-688310/
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🎯 Key Topics Covered
• Why finance was never designed for today’s data complexity
• The two biggest blind spots in modern financial organizations
• What “audit trail” really means and why it’s so hard to achieve
• How AI agents bridge structured system data and unstructured documents
• From quote to cash: tracing transactions across fragmented systems
• Why compliance failures are often data problems, not intent problems
• The evolving role of the CFO in the AI era
• Where humans still matter and where machines outperform
• Why AI makes regulation easier to meet, not harder
• Practical advice for founders building in finance and compliance
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🧠 Key Takeaways
• Finance teams deal with massive data but are not trained as data teams
• Fragmented systems create hidden compliance and cash-flow risks
• AI can monitor 100% of financial transactions, not just samples
• Real-time governance is now technically possible for the first time
• CFOs are becoming transformation leaders, not just scorekeepers
• The future of finance is continuous, automated, and exception-driven
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🎓 What You’ll Learn
• How AI changes financial accuracy from “material” to near-perfect
• Why most financial errors happen even when teams do “everything right”
• How AI reduces headcount pressure without removing human oversight
• What founders must understand before building in fintech or compliance
• How finance can finally get its own “single pane of glass”
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⏱️ Episode Highlights (Timestamps)
• 00:00 – Ahikam’s journey from CFO to AI founder
• 05:00 – The two unsolved problems in corporate finance
• 09:30 – Why audit trails break across modern systems
• 14:00 – What really goes wrong when financial data is wrong
• 18:30 – How AI understands contracts and financial documents
• 24:00 – Humans vs machines in financial decision-making
• 30:00 – The CFO’s evolving role in AI transformation
• 36:00 – Regulation, compliance, and AI realities
• 43:00 – Advice for founders building in finance
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🔗 Resources Mentioned
• Topics: AI agents, financial audit trails, CFO transformation, data governance
In this episode of The CTO Show with Mehmet, I sit down with Khaled Nazif, COO of DSquares, one of the most influential yet quietly powerful enterprise loyalty platforms in the MENA region.
Khaled shares his journey from Stanford and Silicon Valley back to the region, where he helped scale DSquares into a 150M+ end-user platform serving banks, telcos, governments, and large enterprises across 16 countries.
We go deep into what loyalty really means today, why most companies still misunderstand it, how culture breaks at scale if you are not intentional, and what founders in emerging markets can learn from Silicon Valley without copying it blindly.
This is a conversation about scale, systems, leadership, and long-term thinking.
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👤 About the Guest
Khaled Nazif is the Chief Operating Officer at DSquares, a leading white-labeled loyalty and engagement platform powering some of the largest enterprises and government programs across MENA and Africa.
Before returning to the region, Khaled spent nearly a decade in Silicon Valley, earning his MBA from Stanford, founding a B2B SaaS startup, and later working at Zendesk. He brings a rare blend of operator discipline, startup grit, and enterprise execution to scaling regional platforms.
https://www.linkedin.com/in/khalednazif/
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🧠 Key Takeaways
• Why loyalty is misunderstood and often wrongly treated as a cost center
• How DSquares scaled without VC hype and stayed bootstrapped for 13 years
• What it really means to move from a “pirate” startup culture to a “navy” scale-up
• Why government loyalty programs are not an oxymoron
• The importance of productization when scaling enterprise platforms
• How culture breaks after ~150 people and what leaders must do proactively
• What MENA founders can learn from Silicon Valley and what they should ignore
• Why failure must be normalized for ecosystems to truly mature
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🎯 What You Will Learn
• How to scale enterprise platforms across multiple countries and cultures
• How loyalty, data, and behavior change intersect at scale
• Why leadership transitions matter more than founder heroics
• How to think long-term when building in emerging markets
• Why execution discipline beats hype cycles every time
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⏱ Episode Highlights & Timestamps
00:00 – Welcome and introduction
02:00 – Khaled’s journey from Stanford to Silicon Valley
05:30 – What DSquares really does and why most people don’t know it
09:00 – Scaling loyalty across banks, telcos, and governments
13:30 – Loyalty vs transactions: what most companies get wrong
18:00 – Using data and gamification to influence behavior
23:00 – Loyalty as a revenue driver, not a cost center
27:30 – Bootstrapping DSquares and resisting VC pressure
33:00 – Replacing a founder and scaling leadership responsibly
38:30 – The 150-employee culture breaking point
45:00 – Pirate vs Navy mindset and operational maturity
51:00 – Silicon Valley lessons that actually work in MENA
57:00 – Failure, risk-taking, and ecosystem maturity
01:03:00 – Advice for founders building in emerging markets
01:08:00 – Closing thoughts and where to connect with Khaled
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🔗 Resources & Mentions
• DSquares – Enterprise Loyalty & Engagement Platform : https://dsquares.com/
• Book referenced: Blitzscaling by Reid Hoffman
In this episode of The CTO Show with Mehmet, I’m joined by Alex Schlager, Founder and CEO of AIceberg, a company operating at the intersection of AI, cybersecurity, and explainability.
We dive deep into why AI agents fundamentally change enterprise risk, how shadow AI is spreading across organizations, and why monitoring black-box models with other black boxes is a dangerous mistake.
Alex explains how explainable machine learning can provide the observability, safety, and security enterprises desperately need as they adopt agentic AI at scale.
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👤 About the Guest
Alex Schlager is the Founder and CEO of AIceberg, a company focused on detection and response for AI-powered workflows, from LLM-based chatbots to complex multi-agent systems.
AIceberg’s mission is to secure enterprise AI adoption using fully explainable machine learning models, avoiding black-box-on-black-box monitoring approaches. Alex has deep expertise in AI explainability, agentic systems, and enterprise AI risk management.
https://www.linkedin.com/in/alexschlager/
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🧠 Key Topics We Cover
• Why AI agents create a new and expanding attack surface
• The rise of shadow AI across business functions
• Safety vs security in AI systems and why CISOs must now care about both
• How agentic AI amplifies risk through autonomy and tool access
• Explainable AI vs LLM-based guardrails
• Observability challenges in agent-based workflows
• Why traditional cybersecurity tools fall short in the AI era
• Governance, risk, and compliance for AI driven systems
• The future role of AI agents inside security teams
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📌 Episode Highlights & Timestamps
00:00 – Introduction and welcome
01:05 – Alex Schlager’s background and the founding of AIceberg
02:20 – Why AI-powered workflows need new security models
03:45 – The danger of monitoring black boxes with black boxes
05:10 – Shadow AI and the loss of enterprise visibility
07:30 – Safety vs security in AI systems
09:15 – Real-world AI risks: hallucinations, data leaks, toxic outputs
12:40 – Why agentic AI massively expands the attack surface
15:05 – Privilege, identity, and agents acting on behalf of users
18:00 – How AIceberg provides observability and control
21:30 – Securing APIs, tools, and agent execution paths
24:10 – Data leakage, DLP, and public LLM usage
27:20 – Governance challenges for CISOs and enterprises
30:15 – AI adoption vs security trade-offs inside organizations
33:40 – Why observability is the first step to AI security
36:10 – The future of AI agents in cybersecurity teams
40:30 – Final thoughts and where to learn more
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🎯 What You’ll Learn
• How AI agents differ from traditional software from a security perspective
• Why explainability is becoming critical for AI governance
• How enterprises can regain visibility over AI usage
• What CISOs should prioritize as agentic AI adoption accelerates
• Where AI security is heading in 2026 and beyond
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🔗 Resources Mentioned
• AIceberg: https://aiceberg.ai
• AIceberg Podcast – How Hard Can It Be? https://howhardcanitbe.ai/
Raising capital looks easy from the outside. In reality, it is one of the most misunderstood parts of building a startup.
In this episode, Mehmet sits down with Daniel Nikic, a global investment researcher who has analyzed over 15,000 companies across the US, Europe, and the Middle East. Together, they unpack the hard truths founders need to understand about fundraising, investor psychology, market geography, and why most rounds fail long before the first term sheet.
This is a grounded, no-hype conversation about what actually drives investment decisions in 2025 and why “easy money” is often the biggest illusion founders believe.
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About the Guest
Daniel Nikic is the founder of Coherent Research and a global investment research professional with deep experience across North America, Europe, and emerging markets. Originally from Canada and now based in Croatia, Daniel has worked with investors, family offices, and founders worldwide, helping evaluate companies across stages, industries, and geographies.
His work focuses on due diligence, market opportunity analysis, and understanding the human and cultural factors behind investment decisions.
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Key Topics Discussed
• Why most fundraising fails before it even starts
• The biggest misconceptions founders have about “easy capital”
• How geography actually impacts investment decisions
• Why the Middle East is not fast money despite capital availability
• Founder psychology, stress, and emotional control as investment signals
• What investors look for beyond pitch decks and valuations
• The difference between angels, VCs, family offices, and accelerators
• Why urgency and FOMO often kill deals instead of closing them
• How AI is changing investment behavior and decision-making
• Realistic timelines for closing funding rounds in emerging markets
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Key Takeaways
• Capital is not free money. Investors expect returns, discipline, and execution.
• Geography still matters, but trust and relevance matter more.
• Founders who rush fundraising often lose credibility.
• Investors back people they trust, not just ideas or decks.
• Being organized and prepared beats hype every time.
• Fundraising is a relationship-building process, not a transaction.
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What You Will Learn
• How to target the right investors at the right stage
• Why mixing angels, VCs, and family offices too early backfires
• How investors think about risk, timing, and founder maturity
• What “smart money” really means beyond capital
• How long fundraising realistically takes and why patience matters
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Episode Highlights & Timestamps
(You can fine-tune timestamps once audio is finalized)
• 00:00 – Introduction and Daniel’s global background
• 04:00 – Patterns from analyzing 15,000+ companies
• 07:30 – Geography vs psychology in startup success
• 10:45 – The Middle East investment misconception
• 15:20 – Why capital follows trust, not hype
• 18:30 – Choosing the right investor type early on
• 22:40 – Check sizes, valuations, and regional differences
• 27:00 – AI, FOMO, and modern investment behavior
• 32:00 – Why urgency kills fundraising deals
• 36:30 – Realistic timelines to close a round
• 41:00 – Final advice for founders raising capital
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Resources & Links
• Daniel Nikic on LinkedIn: https://www.linkedin.com/in/daniel-nikic/
• Website: https://www.danielnikic.com/
In this episode, Gabriel Jarrosson, founder and managing partner at Lobster Capital, breaks down what truly drives breakout startups inside the world’s most competitive ecosystem.
Before becoming a YC-focused investor, Gabriel built seven startups, failed four, and bootstrapped one to one million ARR alone — no co-founder, no employees, no AI.
Today he invests exclusively in YC companies and shares how he evaluates founders, why early traction beats everything, how YC creates unstoppable momentum, and how AI is reshaping the next generation of builders.
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About Gabriel Jarrosson
Gabriel Jarrosson is a serial founder turned YC-specialized investor and managing partner at Lobster Capital. He has built seven companies, exited three, and invested in more than 100 YC startups. Gabriel also hosts The Lobster Talks and has grown a fast-rising media presence supporting early-stage founders.
https://www.linkedin.com/in/gabrieljarrosson/
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Key Takeaways
• Why solo founders can still win big when they embrace urgency, automation, and creative resourcefulness
• The mindset required to scale without waiting for funding or a co-founder
• YC founder patterns: technical teams, relentless execution, and high velocity
• Why YC attracts the world’s strongest builders and why it’s nearly impossible to replicate
• Gabriel’s 2 percent rule for selecting the best companies in every YC batch
• Why early revenue and market pull matter more than ideas and hype
• How AI is changing the definition of what a “lean team” can achieve
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What You Will Learn
• How top investors evaluate teams, traction, and momentum
• How YC creates an environment that rewires founders to move faster
• Why some geographies struggle to reproduce Silicon Valley outcomes
• How to think about automation, support systems, and scaling with AI
• How founders outside the US can become YC-ready
• What Gabriel regrets missing as an angel investor — and what he learned from it
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Episode Highlights & Timestamps
00:00 — Introduction
01:30 — Seven startups, three exits, four failures
03:00 — Bootstrapping to 1M ARR as a solo founder
07:00 — The role of AI in scaling today
10:00 — Why YC is a category of its own
14:30 — What YC founders have in common
18:00 — Why “local incubators” fail to replicate YC
21:00 — How Gabriel selects winners
27:00 — Getting into competitive YC deals
33:00 — The media edge in venture
37:00 — Becoming YC-ready as a non-US founder
46:00 — Gabriel’s biggest miss
50:00 — Closing thoughts
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Resources Mentioned
• Lobster Capital: https://www.lobstercap.com/
• The Lobster Talks podcast: https://www.youtube.com/@lobster-talks
In this episode, Kingsley Maunder breaks down one of the most overlooked aspects of startup building: proper validation. With over two decades in the startup ecosystem, building products used by Disney, EA Sports, Snap, and more, Kingsley shares the hard-won lessons behind his framework, The SALT Test.
We explore how founders can turn raw ideas into validated products, avoid the assumption trap, distinguish noise from real traction, and leverage AI to accelerate product discovery. This conversation is a masterclass in thinking clearly, testing quickly, and building what people actually want.
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About the Guest — Kingsley Maunder
Kingsley is a veteran product builder, former startup operator, and the author of The SALT Test: How to Take an Innovative Product from Idea to Scale. Over the past 20 years, he has built and scaled products for some of the world’s biggest brands, taken two startups to exit, and helped another raise over $180M. Today, he teaches founders how to validate ideas, avoid costly assumptions, and build products that truly solve user problems.
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Key Takeaways
• Why assumptions are the biggest hidden risk in early-stage innovation
• The story behind the SALT Test and how Thomas Edison inspired it
• How to validate ideas in the right order
• The difference between noise traction and real traction
• Why customer discovery often leads founders astray
• How AI can compress weeks of product validation into hours
• Why you must test the problem before you test the solution
• When to pivot lightly vs when to pivot hard
• The importance of building something significantly better, not just slightly better
• How to distinguish between the user and the buyer in B2B products
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What You Will Learn
• A practical, repeatable process for validating any product idea
• How to talk to customers without falling into the polite feedback trap
• How to stress-test your assumptions before writing a single line of code
• How to set success and failure metrics before experimentation
• How to avoid “innovator bias” and ego-driven decision making
• How to use AI tools to accelerate discovery, research, and early validation
• How to map your idea through the Growth Map to find blind spots
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Episode Highlights
00:00 — Introduction
02:00 — Why the SALT Test?
04:00 — The Assumption Trap
06:00 — How to Stress-Test an Idea
08:00 — Noise Traction vs Real Traction
10:00 — The Right and Wrong Way to Do Customer Discovery
13:00 — Competing with Excel, WhatsApp, and the real world
15:00 — Behavior Change and “Significantly Better”
18:00 — Solution Selling for Founders
22:00 — How AI Compresses Validation Cycles
25:00 — B2B vs B2C Validation
27:00 — Pivoting: Light vs Hard
33:00 — Ego, fear, and founder psychology
36:00 — Lessons from Amazon and Successful Innovators
40:00 — Where Builders Should Focus Next
42:00 — Final Advice
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Resources Mentioned
• The SALT Test by Kingsley Maunder: https://www.kingsleymaunder.com/the-salt-test
• Kingsley’s LinkedIn profile: https://www.linkedin.com/in/kingsleymaunder/
In this conversation, Colin opens the curtain on how Sheets & Giggles became a breakout DTC success by doing things differently: selling before building, leaning into humor, making bold brand decisions, and prioritizing community and impact over hype.
This episode is packed with practical lessons for founders navigating uncertainty, fundraising, pricing strategy, brand identity, and the deeper personal journey behind entrepreneurship.
About the Guest
Colin McIntosh is the founder of Sheets & Giggles, one of the most beloved modern consumer brands known for its sustainable eucalyptus bedding and its unmistakably humorous voice. Colin bootstrapped the company from a simple idea into a high-growth startup that hit one million dollars in monthly revenue within two years. His journey blends sharp execution, authentic branding, creative fundraising, and a grounded philosophy about building companies with purpose.
Colin has appeared on Good Morning America and multiple national outlets, has built a loyal customer community, and is now also a mentor at Techstars, where his 2019 pitch is used globally as an example for new founders.
Connect with Colin: https://www.linkedin.com/in/colindmcintosh/
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In This Episode You’ll Learn
1. How Sheets & Giggles Started Without Inventory
Colin reveals why he chose to validate demand first through pre-orders, and how a successful Indiegogo campaign became early seed capital and proof of market need.
2. The Inflection Points That Unlocked Serious Scale
From a bold COVID donation that unexpectedly reached the governor’s office to a national Good Morning America feature and a high-impact podcast sponsorship, Colin breaks down the moments that changed the company’s trajectory.
3. Humor as a Business Strategy
Why Colin embraced the “jester” brand archetype and how authenticity, relatability, and personality helped Sheets & Giggles stand out in a boring category.
4. Pricing Psychology Explained Simply
Most founders underprice — Colin explains why, and how he tested price elasticity, optimized margins, and used real data to guide pricing decisions.
5. How to Talk to Investors the Right Way
Colin breaks down investor psychology, why FOMO matters, why you must know your numbers by heart, and how honesty builds long-term trust.
6. Bootstrapping vs. VC in Today’s Market
An honest look at why this era might be the best time to build slowly, stay disciplined, and focus on profitability instead of chasing rounds.
7. Purpose, Happiness, and the Reality of Being a Founder
Colin dives deep into fulfillment, ego, expectations, and why internal peace matters far more than revenue milestones.
8. Techstars and a Full Circle Moment
From joining Techstars Boulder as an early team member to returning years later as a founder, and later as a mentor and pitch coach — Colin shares what the program taught him and why founders should consider it.
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Chapters
00:00 Intro
01:00 Colin’s journey and background
03:00 Starting Sheets & Giggles through pre-orders
06:00 Early traction and unexpected breakthroughs
10:00 The donation that changed everything
12:00 Building a humorous and authentic brand identity
16:00 Pricing psychology and finding your true value
20:00 Fundraising and managing investor expectations
27:00 The truth about growth and scale
33:00 Bootstrapping vs raising capital
40:00 Purpose, fulfillment, and founder mindset
46:00 Techstars experience and mentorship
52:00 Final reflections
Why This Episode Matters
If you’re building a startup today, this conversation will give you both tactical clarity and emotional grounding. Colin brings a rare mix of sharp execution and thoughtful humility. From pre-selling products to scaling with humor, from raising millions to staying true to purpose, his journey offers a realistic playbook for building something meaningful.
Mark Donnigan has spent decades helping deep tech and video technology startups translate complex products into commercial traction. In this conversation, we cover why early stage companies must stay lean, how to diagnose GTM confusion, and what AI first marketing looks like in practice.
We also dig into the new buyer journey in B2B, why content is a serious competitive advantage, and why founder led marketing is becoming non negotiable for technical startups.
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👤 About Mark Donnigan
Mark Donnigan is a virtual CMO who specializes in helping early stage technology companies design and execute GTM systems for scale. He blends a technical background with marketing strategy, and has worked closely with deep tech, infrastructure, and video technology companies across the US and beyond. Mark also hosts his own podcast where he covers the intersection of engineering, GTM, and startup growth.
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💡 Key Takeaways
• Small teams outperform large teams because they adapt faster and avoid siloed decision making
• Most early marketing hires fail because they come from companies with fully established ICPs and playbooks
• The new B2B buyer journey is committee based and nonlinear
• Founders must articulate pain, value, and narrative before marketing can be effective
• AI tools create leverage but still require human curation
• Content is not optional; it is a revenue accelerant
• The best marketing starts with mapping actual buying behavior, not assumptions
• Technical founders can outperform junior marketers with AI workflows
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🎓 What You Will Learn
• How to avoid the early stage marketing trap
• Why small GTM teams win in dynamic markets
• How to map buying journeys in modern B2B
• How to use AI to generate content, frameworks, and GTM assets
• The difference between buyers, influencers, and blockers
• How to build trust and shorten sales cycles through content
• Why founder storytelling is more important than ever
⸻
⏱️ Episode Highlights and Timestamps
00:00 Welcome and intro
02:00 Mark’s background as both technologist and creative
06:00 Why great technology fails without great marketing
07:30 The trap of hiring big company marketers too early
10:45 Why small teams win in early GTM
14:00 The missing skill in most marketing hires
17:00 How to know if the market actually needs your product
20:00 Understanding the real buyer versus the visible buyer
23:00 Buying committees, decision blockers, and internal politics
27:00 Why founders misread senior titles in enterprise sales
30:00 Mapping the buyer journey with precision
32:00 The underrated power of content and use case clarity
36:00 Where founders should start if they have no content
38:00 The role of documentation in technical sales
40:00 What AI first marketing looks like in action
43:00 Founders using PRDs to generate full GTM assets
47:00 What should always stay human in AI powered marketing
51:00 Human tone, emotions, and authenticity versus perfect AI output
55:00 Why social algorithms reward provocation, not perfection
58:00 Features vs benefits in modern marketing
01:02:00 Final insights and where to follow Mark
⸻
🔗 Resources Mentioned
• Mark Donnigan website: https://GrowthStage.Marketing
• Mark Donnigan on LinkedIn: https://www.linkedin.com/in/markdonnigan/
• Tools referenced: Gemini, ChatGPT 5.1, Claude, Perplexity Pro
In this conversation, Mehmet is joined by Gerald Beuchelt and Subu Rao, two cybersecurity leaders from Acronis, to unpack the evolving threat landscape, the rise of AI in both offense and defense, and why cyber resilience has become a board-level priority.
They break down what CISOs need to know, how MSPs can create new value, and what frameworks actually work in the real world. If you want a clear and practical blueprint for building resilience, this episode is for you.
👤 About the Guests
Gerald Beuchelt
Chief Information Security Officer at Acronis, with more than 14 years of experience securing global environments across multiple industries. Gerald leads cybersecurity, IT infrastructure, and corporate security strategy, with deep knowledge in AI-driven defense, risk management, and enterprise resilience.
https://www.linkedin.com/in/beuchelt/
Subu Rao
Senior Manager of Cybersecurity Solutions Strategy at Acronis, focused on cyber resilience for MSPs and mid-market organizations. Subu brings over 15 years of experience in identity security, cloud security, and resilience engineering across global security vendors.
https://www.linkedin.com/in/raos/
💡 Key Takeaways
• Cyber resilience and cybersecurity are not the same. One focuses on protection, the other on recovery and adaptation.
• AI is already used by attackers and defenders. Ignoring it increases risk.
• MSPs have a major opportunity to monetize resilience, not just protection.
• Most breaches still start with basic failures like weak passwords and unpatched systems.
• Boards do not want CVE numbers. They want business risk in plain language.
• The right balance between risk appetite and risk tolerance shapes the entire security program.
• Backups alone are not enough. Tested, measurable recovery plans are essential.
• Availability is often the forgotten piece of the CIA triad.
⸻
🎧 What Listeners Will Learn
• The current global threat landscape
• How AI is changing cyber offense and defense
• The difference between cybersecurity and cyber resilience
• What MSPs should do today to serve customers better
• How CISOs can communicate risk to non-technical boards
• Practical frameworks for resilience and business continuity
• Why regional exposure influences risk strategy
• The most common mistakes companies still make in 2025
⸻
⏱️ Episode Highlights & Timestamps
00:00 Introduction and welcome
01:00 Meet Gerald and Subu
04:00 The real state of cyber threats today
05:30 Why basic hygiene failures still cause most breaches
08:30 How attackers are using AI
10:00 The future of automated SOCs
12:00 Are threat patterns different by geography
15:00 Why every company is a target
16:00 Cybersecurity vs cyber resilience explained in simple terms
18:00 How to build resilience without enterprise budgets
21:00 MSPs and the opportunity to lead resilience consulting
24:30 Understanding crown jewels and business impact
26:00 How Acronis-style failover models change the game
29:00 Where boards should start with security frameworks
32:00 Risk appetite vs risk tolerance
36:00 Why security cannot decide in isolation
40:00 Compliance, mandates, and real world frameworks
45:00 How MSPs can craft resilience offerings
48:00 Final advice for CISOs and MSPs
51:00 Closing thoughts and wrap up
In this episode, Mehmet sits down with Radhika Dutt, author of Radical Product Thinking, to explore why OKRs and traditional performance frameworks often collapse under the realities of modern work. Radhika introduces OLA, a new approach built on puzzle-solving, continuous learning, and adaptability — designed for today’s fast-moving product, engineering, and startup environments.
Together, they break down the hidden “product diseases,” the dangers of vanity metrics, the myth of extrinsic motivation, and why teams need clarity instead of big, fluffy vision statements. This conversation is a mindset reset for anyone leading teams, building products, or trying to scale sustainably.
⸻
👤 About Radhika Dutt
Radhika Dutt is the author of Radical Product Thinking, an engineer by training, and a two-time founder. She built her first startup out of her MIT dorm room and has since become a leading voice on vision-driven product development. Radhika works with organizations around the world to help them escape the trap of short-term targets and build meaningful, world-changing products.
Find more about Radhika’s work here:
https://www.linkedin.com/in/radhika-dutt/
⸻
✨ Key Takeaways
• Why OKRs work in theory but fail in most modern organizations
• How goal-driven cultures create “performance theater” instead of real progress
• The difference between extrinsic and intrinsic motivation
• Why fluffy vision statements confuse teams instead of inspiring them
• How to define real problems before jumping into solutions
• The OLA framework: objectives, hypotheses, learnings, adaptations
• How OLA drives alignment, clarity, and honest learning
• Why founders should stop copying big-company playbooks
• How to communicate results to investors without vanity metrics
• Why adaptation speed is the true competitive advantage
⸻
🎧 What You’ll Learn
• How to replace rigid goal-setting with dynamic puzzle-solving
• How to build a product culture that values curiosity and experimentation
• How to avoid the biggest traps that kill innovation
• How AI hype influences bad decision-making and how to course-correct
• How leaders can create clarity without micromanaging
• How to apply OLA even if your company still uses OKRs
⸻
⏱️ Episode Highlights & Timestamps
00:00 — Welcome and intro
01:00 — Radhika’s early story and the mistakes that inspired Radical Product Thinking
06:00 — Why motivation systems today actually kill motivation
08:00 — The problem with fluffy, generic vision statements
11:00 — Why OKRs create the wrong incentives
14:00 — How OKRs evolved from 1940s manufacturing
18:00 — Why modern work requires a different approach
23:00 — Introduction to OLA and how puzzle-setting works
26:00 — How to apply OLA in sales, product, and engineering
34:00 — Using OLA to bring clarity and innovation
39:00 — Speed, experimentation, and continuous learning
44:00 — How to communicate progress to boards and investors
49:00 — Why founders must drop ego and embrace honesty
54:00 — Final advice and how to connect with Radhika
⸻
📚 Resources Mentioned
• Radical Product Thinking — Radhika’s book
• Free toolkits https://www.radicalproduct.com/
• OLA Toolkit (formerly OHL)
In this conversation, Jonathan breaks down the real state of AI adoption in GTM, why most revenue teams are still “stuck in the basics,” and how leaders can shift from dashboards to intelligence. He explains why CRM data hygiene is dead, how operational AI works behind the scenes, and what it truly means to run an AI native revenue team.
From first principles thinking to reinvented GTM playbooks, this is a roadmap for founders, CROs, RevOps leaders, and anyone building modern revenue organizations.
⸻
👤 About Jonathan Kvarfordt
Jonathan Kvarfordt is the VP of GTM Strategy & Marketing at Momentum.io. Known as “Coach” across the industry, he is the creator of GTM AI Academy with more than 10,000 participants, a university instructor, a strategic advisor, and a practitioner at the intersection of GTM, AI, and automation.
He works hands-on with leaders to operationalize AI, eliminate friction in revenue processes, and build next generation GTM systems.
https://www.linkedin.com/in/jmkmba/
⸻
💡 Key Takeaways
• AI adoption is overstated
Despite hype, only about 7 percent of companies operate with real “operational AI.”
• CRM data entry is the most underrated automation
AI driven CRM automation unlocks insights for reps, managers, and executives.
• The new GTM OS lives in tools like Slack
Revenue teams are moving away from 20 tabs into one unified operating layer.
• First principles thinking matters more than tools
Start with initiatives and gaps, not buying random AI tools.
• Human skills become more important, not less
The future seller is a strategist, negotiator, and relationship builder.
• Small teams have the biggest advantage
Fewer processes mean faster reinvention and cleaner AI powered workflows.
• AI native pipeline reviews are strategic
Not data entry sessions. Think signals, intelligence, and deal momentum.
⸻
🎧 What You Will Learn
• Why GTM fundamentals are still broken despite AI hype
• How AI changes forecasting, deal reviews, and revenue leadership
• The difference between “time saving AI” and “amplification AI”
• How to build AI native workflows inside your GTM stack
• Why founders should start automating earlier than they think
• Which sales skills matter most in the AI era
• Why CRM systems might look completely different in the future
⸻
⏱ Episode Highlights (Timestamps)
00:00 – Welcome and intro
01:00 – Jonathan’s journey and new VP role
03:00 – The truth about AI adoption in GTM
05:00 – Where companies struggle most with AI
07:00 – From dashboards to intelligence
10:00 – Why AI tools fail without clear initiatives
12:00 – Slack as the new operating system for GTM
15:00 – Why RevOps teams over engineer tech stacks
17:00 – CRM hygiene vs operational AI
19:00 – Time as the highest leverage automation area
21:00 – How AI shifts GTM playbooks
24:00 – The rise of AI powered buyer research
26:00 – The new pipeline review
29:00 – The most underrated automation in GTM
31:00 – Real win/loss data and bias removal
33:00 – What skills sellers need in the AI era
36:00 – “Let us go sell” culture and eliminating busywork
37:00 – When founders should start automating
39:00 – Reinvent vs optimize vs amplify
41:00 – The idea behind Jonathan’s book Ignite
44:00 – Will CRM even exist in the future?
48:00 – Which parts of sales AI might fully replace
50:00 – First principles thinking and GTM
52:00 – Final advice and where to find Jonathan
⸻
📚 Resources Mentioned
• GTM AI Academy
• The book Ignite your GTM With AI: https://www.amazon.com/dp/B0FRXGSDSN
In this episode, Mehmet sits down with Dr. Nico Augustin, Head of Research and Expeditions at OceanQuest, to uncover the mysteries of the deep ocean. From unexpected discoveries in the Atlantic to cutting edge underwater robotics, Dr. Nico reveals how little we know about the world beneath us and why the deep sea remains one of Earth’s last unexplored frontiers.
The conversation covers the science, technology, and leadership lessons behind modern ocean exploration, along with how emerging tech like AI and digital twins are reshaping the future of the field.
⸻
About the Guest
Dr. Nico Augustin is a marine geologist, expedition leader, and the Head of Research and Expeditions at OceanQuest, a pioneering non profit foundation advancing deep ocean discovery, innovation, and capacity building. With more than 20 years of research experience across the Atlantic, Arctic, and the Red Sea, he has led large scale mapping missions, discovered new hydrothermal systems, and mentored hundreds of young scientists.
Connect on LinkedIn
https://www.linkedin.com/in/nico-augustin-971a93308/
⸻
Key Takeaways
• The deep ocean is still one of Earth’s least explored environments.
• Modern expeditions rely on mapping, robotics, data, and multidisciplinary teams.
• AI will play a major role in making underwater vehicles more autonomous and safer.
• The deep ocean is far more active and diverse than older textbooks suggest.
• Leadership at sea is a masterclass in clarity, calmness, and adaptability.
• Exploration and storytelling are essential to inspire the next generation of ocean researchers.
⸻
What Listeners Will Learn
• How deep sea expeditions are planned and executed
• Why the Red Sea and Atlantic hold surprising geological mysteries
• The role of AI, digital twins, and robotics in underwater exploration
• How OceanQuest is training young scientists across Africa
• Leadership lessons from managing complex expeditions
• Why public awareness matters in ocean science
⸻
Episode Highlights
00:00 Introducing Dr. Nico Augustin
02:00 Childhood curiosity and the path to marine geology
04:00 Early expeditions and transformational moments
07:00 Mapping the unknown through interdisciplinary teams
08:30 Surprising discoveries from the Atlantic to the Red Sea
11:00 The first visual hydrothermal systems found in the Red Sea
14:00 How deep sea expeditions are designed and executed
17:00 AI, robotics, and digital twins shaping future exploration
22:00 OceanQuest’s Around Africa Expedition and its impact
28:00 Leadership lessons from uncertainty and high stakes operations
36:00 Collaboration between science and the private sector
39:00 What the deep ocean still hides from us
45:00 How to inspire public excitement for ocean discovery
50:00 Final thoughts and how to connect with Dr. Nico
⸻
Resources Mentioned
• OceanQuest: oqfoundation.org
• OceanQuest on Instagram, LinkedIn, and X
In this episode, Mehmet sits down with Harish Chandramowli, Head of AI at Good Day Software, to explore how AI is reshaping the future of fashion, retail, and e-commerce operations.
Harish shares his journey from cybersecurity engineering at Bloomberg and cloud security at MongoDB to building fashion-specific AI tools that solve real operational pain points around data chaos, messy workflows, and inventory waste.
This is a deep dive into verticalized AI, workflow automation, agentic systems, and the emerging category of Retail OS.
If you’re a founder, investor, or tech leader curious about applied AI or the future of retail automation, this episode is full of insight.
⸻
👤 About Harish Chandramowli
Harish is the Head of AI at Good Day Software, a fast-growing platform redefining how fashion and retail brands manage operations. With experience at Bloomberg and MongoDB, he brings a unique blend of security engineering, data modeling, and real-world problem solving into the retail tech world.
He previously founded FLA, a fashion operations startup, and now focuses on building AI-powered workflows and agents for e-commerce brands.
Harish’s LinkedIn : https://www.linkedin.com/in/scharish/
⸻
✨ Key Takeaways
• Why retail back-office operations are still broken and dominated by spreadsheets
• The rise of Retail OS and why ERP is becoming outdated
• Real examples of AI reducing hours of manual work
• Why agentic workflows matter more than chatbots
• The biggest unseen cost in e-commerce: data integrity failures
• The hidden value of vertical AI models
• How founders should think about AI “moats”
• Red flags Harish sees in AI startup pitches
• How non-technical founders can communicate with technical teams more effectively
• Why everyone is on a level playing field in this phase of AI
⸻
🎧 What You’ll Learn
• How to build AI systems for operational workflows
• Why fashion and retail create perfect environments for data-driven AI
• How to spot real vs fake AI innovation
• How AI can automate back-office processes like purchase orders, packing lists, and inventory reconciliation
• Why agent-based AI is the future
• How AI changes new-market entry strategies
• How founders can pitch AI in a credible, non-hyped way
⸻
⏱️ Episode Highlights (Timestamps)
(For YouTube + Spotify chapters)
00:00 — Welcome and introduction
01:00 — Harish’s journey: cybersecurity, Bloomberg, MongoDB
03:00 — Why retail operations are still broken
04:30 — Discovering the back-office pain points in fashion
06:30 — The spreadsheet problem killing profitability
08:30 — Why e-commerce is a brutal margin business
10:00 — Workflow chaos and data fragmentation
12:00 — Retail OS vs ERP and what the future looks like
14:00 — How AI powers Good Day Software
15:00 — Chatbots vs real AI vs agentic workflows
16:00 — Automating packing lists, PO ingestion, and email workflows
17:30 — Agents detecting inventory discrepancies
18:30 — Using localized data for new market expansion
20:00 — Verticalized AI and the rise of industry-specific LLMs
22:00 — Accounting differences across regions
24:00 — What founders need to know about AI moats
26:00 — Why real-world data is a superpower
28:00 — Changing consumer funnels: search, ads, and GPT shopping
30:00 — From engineer to business thinker: Harish’s mindset shift
32:00 — ChatGPT as a tool for business communication
34:00 — The biggest red flags in AI startup pitches
36:00 — Why automating everything is dangerous
38:00 — Final thoughts on curiosity, experimentation, and the AI era
39:00 — Where to reach Harish
⸻
📚 Resources Mentioned
• Good Day Software https://www.gooddaysoftware.com/
• MongoDB
• Shopify and e-commerce back-office operations
• Vertical AI applications
• Agentic workflows and email-based automation
In this episode, Mehmet sits down with VC and author Ben Wiener to unpack one of the most practical, founder-friendly pitching frameworks in the startup world today. Ben is the creator of the HEART Framework and the author of the bestselling business fable Fever Pitch. He breaks down why most pitches fail, how investors actually think, and how founders can use storytelling to turn curiosity into conviction.
This episode goes deep into the psychology of pitching, investor behavior, AI startup hype, and the traps founders unintentionally fall into when telling their story.
If you’re a founder raising capital, a builder crafting a strong narrative, or an operator helping startups pitch with clarity, this episode is a masterclass.
⸻
About the Guest: Ben Wiener
Ben Wiener is a professional venture capitalist, founder of a 12-year-old early stage VC fund, and the bestselling author of Fever Pitch. His HEART Framework has become a go-to model for founders seeking a structured, effective, and persuasive way to pitch investors. Ben is known for blending storytelling, psychology, and practical experience from thousands of pitch interactions to help founders succeed.
https://www.linkedin.com/in/benwiener/
⸻
What Listeners Will Learn
• How to structure a pitch that mirrors the investor brain.
• How to craft a belief statement that captures attention.
• How to avoid the fatal traps of overexplaining the tech.
• How to use interruptions, objections, and tough questions to your advantage.
• How to turn your pitch into a narrative investors want to follow.
• How to pitch at any stage, including pre-product and day zero.
• How founders can build trust even without traction.
• How AI founders can differentiate in a crowded landscape.
⸻
Episode Highlights (Timestamps)
00:00 — Mehmet opens the episode and introduces VC and author Ben Wiener.
01:00 — Ben on being a “professional VC and unprofessional author” and how Fever Pitch came to life.
03:00 — Why Ben chose to teach pitching through a business fable instead of a traditional book.
06:00 — How Guy Kawasaki ended up writing the foreword after a bold cold email.
08:00 — Teaching business through fiction and why it works.
09:00 — Introducing Mark, the protagonist of Fever Pitch, and why his struggle mirrors most founders.
11:00 — Why founders assume investors will understand their brilliance without proper structure.
14:00 — Deep dive into the HEART Framework and why order matters.
20:00 — Why team traits come last and not first.
22:00 — Why founders struggle to articulate their “why.”
26:00 — How investors’ subconscious minds evaluate pitches and search for red flags.
29:00 — Why pitch templates on the internet often mislead founders.
33:00 — What investors actually look for vs what they say they want.
35:00 — The danger of jumping straight into the tech.
38:00 — Alternatives vs competition and why they are not the same.
41:00 — Why interruptions during a pitch are a good sign.
45:00 — Mehmet and Ben share personal experiences about tough investor reactions.
48:00 — Pitching with no product and no traction: what founders can do.
50:00 — Why warm introductions matter 100 times more than cold ones.
54:00 — The 10–20–30 pitch rule and why less is more.
58:00 — Why AI is a double-edged sword for founders raising today.
01:02:00 — Mehmet’s reflection on using HEART as a compass for founders.
01:04:00 — Ben’s closing remarks and where founders can access free tools.
⸻
Resources Mentioned
• Fever Pitch by Ben Wiener : https://feverpitchbook.com/
• HEART Framework Tools and Free Pitch Deck Template: https://view.genially.com/682f26cc0eb98daa6299f431
• Guy Kawasaki’s work on pitching and “Start With Why”
• The Venture Mindset (book reference)
In this powerful conversation, Wesley Eugene, SVP North America at HIT Global, joins Mehmet to explore a new framework for technology leadership. They go deep into human centered design, why digital transformations fail, how AI forces us to rethink what it means to work, and why empathy is now a competitive advantage.
Wesley draws from years of experience in digital transformation, design thinking, and ITIL modernization. He shares the hidden gaps in traditional IT practices, the philosophical questions AI forces us to ask, and the skills leaders must build to stay relevant in the coming decade.
This episode is a thoughtful, practical, and timely reminder that technology is at its best when it elevates people.
👤 About Wesley Eugene
Wesley Eugene is the SVP North America at HIT Global, an organization focused on humanizing IT through integrated human centered design. Wesley has led major digital transformation programs, advised global enterprises, and worked alongside design pioneers including Ideal’s leadership team. He champions a future where technology is designed around people, not processes, and where AI augments human potential instead of replacing it.
🔥 Key Takeaways
• Most digital transformations fail because leaders lose sight of purpose and experience.
• True transformation is a business transformation, not a tech project.
• Technology without humanity becomes vanity and often leads to harm.
• The experience layer is becoming the most important layer in the tech stack.
• AI should serve as human augmentation rather than human replacement.
• Leaders must invest in empathy, storytelling, creativity, and curiosity.
• Regulation is not the enemy of innovation. It is the brake that lets innovation go fast safely.
• The rise of AI forces society to rethink work, value, consciousness, and what it means to be human.
• Creativity still happens when we disconnect. Nature remains the best CPU upgrade.
🎧 What You Will Learn
• Why human centered design is the missing link in IT and AI.
• The root causes of failed digital transformations across industries.
• How to build a purpose driven technology strategy that unites the whole company.
• Why every tech leader must become a storyteller.
• How to prepare your teams for the AI era.
• The ethical, environmental, and human considerations AI leaders must prioritize.
• Why curiosity is the most underrated leadership skill in tech today.
⏱️ Episode Highlights (Timestamps)
00:00 Welcome and intro
01:00 The mission behind HIT Global and humanizing IT
04:00 Lessons from IDEO, design thinking, and rapid prototyping
07:00 Why technology needs to be humanized now
10:00 The experience layer and the future of value creation
13:00 Why digital transformations fail
16:00 The story of buy in and the NASA janitor
18:00 Chasing tech vs transforming the business
21:00 Why IT is misunderstood and how to fix it
27:00 TBM and the importance of storytelling in tech
30:00 The promise of AI and the threat of losing the human
33:00 The seatbelt metaphor for responsible innovation
38:00 AI leaders, risk, and accountability
45:00 What AI forces us to confront about humanity
50:00 AI as human augmentation, not replacement
56:00 The skills leaders need for the next decade
59:00 Creativity, nature, and switching off screens
01:03 Final advice and how to learn more from HIT Global
📚 Resources Mentioned
• HIT Global Services: https://www.hitglobal.services/
• Human Centered Design for IT Service Management by Katrina McDermott
• IDEO and the history of the Apple Mouse
• TBM Council (Technology Business Management Framework)
• Humanizing AI Certification at HIT Global
• LinkedIn profile of Wesley Eugene: https://www.linkedin.com/in/wesleyeugene/
In this episode, Luv Kapur joins Mehmet to break down how composability is reshaping modern engineering. Luv is an engineering leader at Bit, working across their open source and enterprise platforms, and one of the earliest advocates for modular, reusable software as a way to unlock scale.
They explore why composability matters, how modular systems speed up delivery, and the cultural shift required inside engineering teams. Luv also shares real results from enterprise adoption, including faster iteration cycles, fewer defects, and measurable ROI in the eight-figure range. The conversation closes with a deep look into HopeAI, Bit’s AI architect designed to orchestrate existing components rather than generate endless code.
This is a practical and insightful episode for any CTO, engineering leader, or founder navigating the next era of platform development.
⸻
About Luv Kapur
Luv Kapur is an Engineering Lead and Solutions Architect at Bit. His background spans platform engineering, dev tooling, internal systems, and leading enterprise adoption of composable software. He has helped teams move from monolithic and fragmented architectures to modular systems that enable real speed, discoverability, and developer empowerment.
He now works across Bit’s open source ecosystem and Bit Cloud for enterprise, helping organizations adopt composability and shift toward a more scalable engineering model.
⸻
Key Takeaways
• Composability is an operating model that enables teams to build with reusable building blocks and ship faster.
• Modular architectures reduce defects, improve consistency, and increase transparency across engineering teams.
• Discoverability and ownership are core success factors. Without them, composability collapses into fragmentation.
• AI should act as an orchestrator, not a generator. The future belongs to systems that reuse proven components.
• Enterprise ROI from composability is measurable, from reduced iteration time to real cost savings in the millions.
• Citizen developers will play a bigger role as AI unlocks access to complex internal systems.
• Engineers will still be needed, but AI will free them to solve harder and more meaningful problems.
⸻
What You Will Learn
• How modular software accelerates delivery
• Why enterprises struggle with legacy systems and how bottom up adoption solves it
• How to measure success in composability using real metrics
• The cultural shift required for high performing engineering teams
• How AI can guide architecture instead of generating more code
• The role of discoverability, ownership, and inner source in large organizations
• What HopeAI is and how it works as an AI architect
⸻
Episode Highlights
00:00 Introduction and guest background
03:00 What composability really means and why it matters
06:00 Modular architectures explained with real world examples
10:00 What defines high performance engineering teams
14:00 Why companies fail when adopting composability
17:00 The shift from top down mandates to bottom up success
20:00 Tangible metrics teams can measure
23:00 AI as orchestrator versus generator
27:00 Why code reuse will define the next decade
31:00 Inside HopeAI and how it guides architecture
35:00 Enterprise results and real ROI
37:00 The future of platform development
41:00 Why engineers remain irreplaceable
42:00 How to connect with Luv Kapur
⸻
Resources Mentioned
• Bit (Open Source): https://bit.dev
• Bit Cloud (Enterprise): https://bit.cloud
• Luv Kapur on LinkedIn: https://www.linkedin.com/in/luvkapur/
In this powerful conversation, Christina Richardson — serial founder, resilience researcher, and founder of Foundology — joins Mehmet to unpack the real psychological journey of entrepreneurship.
Christina shares the story behind her 2 AM wake-up call that wasn’t a heart attack but a full nervous system collapse. That moment led her to study over 400 founders, uncover patterns of burnout, and build a framework that helps founders perform at their best without destroying themselves.
We dive deep into the myths of hustle culture, the neuroscience of performance, the four pillars of resilience, the importance of early warning signs, and why founders must learn to scale themselves as fast as they scale their startups.
This episode is essential listening for anyone building under pressure.
⸻
👤 About Christina Richardson
Christina Richardson is the founder of Foundology, a global resilience platform helping founders navigate stress, uncertainty, and the emotional demands of building a company. Through evidence-backed founder circles, community support, and tools like the upcoming Founder Fuel Gauge, Foundology equips founders with what most startup ecosystems overlook: human performance.
Christina is also an Associate Professor at University College London, where she teaches founder development, leadership, and performance psychology. As a serial entrepreneur with a small exit and a very real burnout story, her work sits at the intersection of research, resilience, and lived experience.
⸻
💡 Key Takeaways
• Why hustle culture and “9-9-6” thinking are biologically flawed
• What really causes burnout, panic attacks, and chronic overwhelm
• The emotional burden founders carry — team, family, investors, expectations
• Why founders stop performing well long before they burn out
• The four pillars of founder resilience:
• Why loneliness is a silent performance killer
• How to scale your leadership as the company scales
• Why equanimity is the most underrated founder skill
• How AI helps founders — and how it also fuels unhealthy pressure
• Why human connection will remain irreplaceable in the AI era
⸻
🎧 What You’ll Learn
• How to spot the first early-warning signs of burnout
• How to build a daily rhythm that supports clarity and flow
• Why recovery is as important as output
• How to replace guilt-driven work habits with resilient thinking
• Why founders perform better with structured peer circles
• How to avoid the trap of meddling as your team grows
• How ecosystems and investors can support founders — the right way
⸻
⏱️ Episode Highlights (Timestamps)
00:00 – Introduction and Christina’s story
02:00 – The 2 AM “heart attack” that changed everything
05:00 – The symptoms founders ignore: irritability, migraines, digestion issues
07:00 – The myth of the grind and the danger of ecosystem bravado
08:30 – Your brain under stress: the science of performance and recovery
11:00 – What the 400-founder resilience study revealed
13:00 – The four pillars of resilience
17:00 – The rise of founder circles and why they work
20:00 – Loneliness as a toxic performance blocker
22:00 – How founders can scale themselves alongside the company
25:00 – Leadership at scale: equanimity and coaching mindset
28:00 – The fine line between support and pressure from investors
34:00 – Why some people cross the entrepreneurial chasm and others don’t
38:00 – How AI helps and hurts founders
41:00 – Why human connection will always matter
42:00 – What’s next for Foundology
43:00 – Where to find Christina and Foundology
⸻
🔗 Resources Mentioned
• Foundology – Supporting Founder Resilience
• Founder Fuel Gauge (Early Access)
https://foundology.org/founder-fuel
• Join the Founder Fuel Community (Free)
https://foundology.org/community
• Christina Richardson on LinkedIn
Digital transformation isn’t about technology — it’s about leadership, culture, and execution. In this episode, veteran CTO and transformation expert Tory Bjorklund joins Mehmet to debunk hype-driven transformation, explain why most initiatives fail, and share his proven framework for executing technology-driven change that sticks.
Whether you’re scaling a startup or modernizing a large enterprise, this conversation brings clarity and practical wisdom to one of the most misunderstood journeys in tech.
⸻
👤 About the Guest
Tory Bjorklund is a serial entrepreneur, CTO, and transformation advisor with decades of experience leading large-scale technology and organizational change across manufacturing, fintech, and enterprise software. He is currently building Victoria Fide, focused on helping organizations succeed with transformational change, and is the author of The Digital Transformation Guidebook.
⸻
🔑 Key Takeaways
• Digital transformation fails when technology leads instead of business goals
• Why “go-live” is the beginning, not the finish line
• The role of leadership and communication in successful transformation
• AI reality check: where companies are going wrong
• How to reset a failing transformation before it’s too late
• Why ERP and enterprise tools remain underutilized
• Building a culture that embraces change, not fears it
⸻
📘 What You’ll Learn
• A 3-stage framework for transformation: Prepare → Execute → Sustain
• How to align executive teams and technology leaders
• Why transformation is continuous, not a project
• Practical steps for avoiding costly technology mistakes
• How to think about AI beyond the hype cycle
⸻
🧠 Episode Highlights
0:00 — Intro
1:20 — Tory’s journey across tech, manufacturing & consulting
4:30 — Tech push vs business pull: who drives innovation?
7:05 — Why 70% of digital transformations fail
10:40 — How to course-correct a failing initiative
14:20 — Defining success and ROI from day one
18:30 — The Prepare → Execute → Sustain model
22:40 — Who should own transformation inside the company
26:00 — AI reality: personal productivity vs enterprise value
32:00 — Why ERP & existing tools are still underutilized
37:20 — Industrial AI & the real disruption
39:40 — About Tory’s book
42:00 — Closing thoughts
⸻
🔗 Resources Mentioned
• Victoria Fide – https://victoriafide.com
• Tory’s upcoming book: The Digital Transformation Guidebook
• Connect with Tory on LinkedIn: https://www.linkedin.com/in/torybjorklund/