NextGen Studio

In this episode of NextGen Studio, I speak with Angeley Mullins, founder and CEO of Ateris Ventures, about the future of AI, go-to-market strategy, founder-led sales, and what it really takes to scale a startup in today’s market.

Angeley shares her experience, having helped scale high-growth startups and worked with major technology brands. She explains why founders cannot rely on product features alone, why AI tools are not a go-to-market strategy, and why critical thinking is becoming one of the biggest competitive advantages in the AI era.

The conversation explores how startups move from product-market fit to scalable growth, the difference between Series A and Series B GTM challenges, where AI creates real ROI in sales and marketing, and why the brand is still the original revenue driver.

Angeley also shares her perspective on women in tech leadership, the importance of building a personal brand, and why founders and CEOs need to use their voice, tell better stories, and build trust before the market is ready to buy.

Topics covered in this episode:

• AI in GTM strategy
• Founder-led sales and startup growth
• Product-market fit and scalability
• Why AI tools are not a strategy
• Inbound vs. outbound marketing in the AI era
• Brand as a revenue driver
• Series A vs. Series B GTM challenges
• Women in tech and leadership
• Why founders need to build visibility and trust

Listen to this episode if you’re a founder, CEO, startup operator, marketer, or growth leader thinking about how to use AI, branding, and go-to-market strategy to scale smarter.

In this episode, I speak with Brian Fletcher, co-founder of the AI-first consultancy FM and fractional CTO for growth-stage companies.

Brian shares why the traditional agency and consulting model is being disrupted, how AI-assisted development is making custom software more accessible, and why many companies are starting to question whether renting SaaS tools still makes sense. The conversation explores the rise of small senior teams, outcome-based consulting, AI automation, knowledge systems, and the future of technical leadership in an AI-driven business world.

We also discuss the difference between the “work of knowing” and the “work of deciding,” why AI can handle research, synthesis, reporting, and operational knowledge work — but human judgment, accountability, taste, and strategic decisions still matter.

This episode is especially relevant for founders, CTOs, business owners, consultants, and mid-market companies exploring how to use AI to improve workflows, automate processes, build smarter systems, and move faster without scaling headcount too early.

In this episode, I sit down with Steven Dickens, CEO and Founder of HyperFRAME Research, to explore what enterprise AI adoption looks like beyond the hype.

Steven is a leading industry analyst and one of the most trusted voices at the intersection of enterprise technology, AI strategy, and business transformation. HyperFRAME Research recently published the State of the Enterprise AI Stack 2026 report, based on insights from 544 senior technology and business leaders.

Together, we discuss the enterprise AI execution gap - why 78% of organizations say AI is strategically important, yet only 37% have a structured process to deploy it. The conversation explores what prevents companies from turning AI ambition into real implementation, including data quality, legacy infrastructure, security, cost, talent shortages, governance, and shadow AI.

Steven also shares practical insights on where companies are seeing real AI ROI today, including software development, customer support, call centers, SaaS tools, and personal productivity. The conversation covers AI readiness, large language model strategy, agentic workflows, the future of SaaS, AI governance, and why successful AI adoption is ultimately a people, process, and technology challenge.

If you are a founder, business leader, technology executive, or growth-focused person trying to understand how AI will reshape enterprise workflows, this episode offers a clear and grounded perspective on how to move from AI experimentation to real deployment.

Listen to the full episode to learn how business leaders can close the enterprise AI execution gap and build a more practical, secure, and scalable AI strategy.

Wie verändert KI die technische Gebäudeplanung, und was bedeutet das für Ingenieurbüros, TGA-Planer und die Zukunft der Baubranche?

In dieser Folge spreche ich mit Gilles Dostert, CEO und Co-Founder von Zenesis, einem Leipziger Deep-Tech-Startup, das die technische Gebäudeausrüstung mit KI und datenbasierten Systemen effizienter macht.

Gilles erklärt, wie eine echte „Intelligenzinfrastruktur“ für die TGA-Planung aussehen kann. Außerdem sprechen wir über die Herausforderungen beim Aufbau eines Deep-Tech-Startups, den Vertrauensaufbau im Markt, Funding, Skalierung und die Frage, wie sich die Rolle von Ingenieuren und TGA-Planern in den nächsten Jahren verändern wird.

In dieser Folge erfährst du:

– wie KI die TGA-Planung effizienter machen kann– warum strukturierte Daten entscheidend für KI-Ready-Unternehmen sind– welche Pain Points Ingenieurbüros heute besonders bremsen– warum Excel-Tabellen und Daten die Skalierung erschweren– wie sich BIM und KI in Zukunft ergänzen können– was Deep-Tech-Startups brauchen, um sich im AEC-Markt durchzusetzen– warum sich die Rolle von Planern von ausführender Arbeit hin zu prüfender und beratender Arbeit entwickeln wird– wie TGA-Unternehmen mit KI starten können, ohne ihre Prozesse komplett umzustellen

Diese Folge ist besonders spannend für Ingenieurbüros, TGA-Planer, Architekten, Bauunternehmen, PropTech-Startups und alle, die verstehen wollen, wie KI die Zukunft der Bauplanung verändert.

Wie verändert KI die technische Gebäudeplanung, und was bedeutet das für Ingenieurbüros, TGA-Planer und die Zukunft der Baubranche?

In dieser Folge spreche ich mit Gilles Dostert, CEO und Co-Founder von Zenesis, einem Leipziger Deep-Tech-Startup, das die technische Gebäudeausrüstung mit KI und datenbasierten Systemen effizienter macht.

Gilles erklärt, wie eine echte „Intelligenzinfrastruktur“ für die TGA-Planung aussehen kann. Außerdem sprechen wir über die Herausforderungen beim Aufbau eines Deep-Tech-Startups, die Überzeugungsarbeit im Markt, Funding, Skalierung und die Frage, wie sich die Rolle von Ingenieuren und TGA-Planern in den nächsten Jahren verändern wird.

In dieser Folge erfährst du:

– wie KI die TGA-Planung effizienter machen kann– warum strukturierte Daten entscheidend für KI-Ready-Unternehmen sind– welche Pain Points Ingenieurbüros heute besonders bremsen– warum Excel-Tabellen und Daten die Skalierung erschweren– wie sich BIM und KI in Zukunft ergänzen können– was Deep-Tech-Startups brauchen, um sich im AEC-Markt durchzusetzen– warum sich die Rolle von Planern von ausführender Arbeit hin zu prüfender und beratender Arbeit entwickeln wird– wie TGA-Unternehmen mit KI starten können, ohne ihre Prozesse komplett umzustellen

Diese Folge ist besonders spannend für Ingenieurbüros, TGA-Planer, Architekten, Bauunternehmen, PropTech-Startups und alle, die verstehen wollen, wie KI die Zukunft der Bauplanung verändert.

In dieser Podcast-Folge des NextGen Studio Podcasts spreche ich mit Nicolas Gresser, Gründer von 3D-bautec., einem Hamburger Deep-Tech-Startup, das 3D-Drucksysteme für die Bauindustrie entwickelt.

Die Baubranche steht vor großen Herausforderungen: Fachkräftemangel, steigende Baukosten, geringe Produktivitätssteigerung und der Druck, nachhaltiger und effizienter zu bauen.

Nicolas erklärt, wie 3D-Druck im Bauwesen helfen kann, Rohbauprozesse zu automatisieren, Bauunternehmen effizienter zu machen und neue Möglichkeiten für die Zukunft des Bauens zu schaffen.

Im Gespräch geht es um die Frage: Wie werden wir in Zukunft bauen?

Wir sprechen über:

- wie die Idee zu 3D-bautec entstanden ist - warum 3D-Druck besonders im Rohbau wirtschaftlich spannend ist - wie eine automatisierte Baustelle der Zukunft aussehen könnte - welche Rolle BIM, digitale Modelle und KI spielen- welche Herausforderungen Deep-Tech- und Hardware-Startups beim Markteintritt haben - warum Networking, Startup-Ökosysteme und Förderungen für Gründer so wichtig sind

Diese Episode ist besonders spannend für Architekt:innen, Bauunternehmen, AEC-Founder, Immobilienentwickler, PropTech- und ConTech-Startups sowie alle, die sich für die Zukunft von Bau, KI, Automatisierung und nachhaltiger Innovation interessieren.

Wenn du verstehen möchtest, wie 3D-Druck, KI und Automatisierung die Bauindustrie verändern, ist diese Folge für dich.

In this episode of the NextGen Studio Podcast, I speak with Carol Eastman, California-based tech entrepreneur, two-time founder with successful exits, and CEO of ReadyAI, to discuss one of the most urgent challenges facing companies today: AI governance, AI compliance, and secure enterprise AI adoption.

As employees rapidly adopt tools like ChatGPT, Claude, Grok, and other AI platforms, many companies are facing a growing risk: sensitive company data being shared without proper oversight. This is known as shadow AI, and it is becoming one of the biggest security and compliance concerns for modern organizations.

Carol explains why AI governance is no longer optional, how companies can protect themselves from data leaks, prompt injection, privacy violations, model manipulation, and compliance failures, and why leadership teams need to create clear guardrails before AI adoption scales across the business.

This conversation is especially valuable for CEOs, founders, executives, IT leaders, CISOs, HR teams, and business owners who want to use AI safely, responsibly, and strategically.

In this episode, we cover:

- Why AI governance and AI compliance are becoming business-critical
- The biggest risks of ungoverned AI adoption
- What shadow AI looks like inside companies
- How prompt injection can threaten business security
- Why AI security is everyone’s responsibility
- How companies can train employees to use AI safely
- What good AI governance actually looks like
- How to start implementing AI compliance without overwhelm
- Why leadership, legal, IT, HR, and security teams need to work together
- The future of secure enterprise AI adoption

Carol also shares lessons from building and selling two companies, what she has learned about leadership, and why passion, initiative, and team spirit remain essential traits in an AI-powered business world.

If you are a founder, CEO, or business leader looking to adopt AI without creating unnecessary risk, this episode will help you understand where to start and how to build a smarter, safer AI strategy.

In this episode of the NextGen Studio, I speak with Tim Gosnell, CEO of Common Thread AI, to explore how AI, customer data, and revenue operations are reshaping the future of business growth.

We discuss the real difference between using AI as a “magic bullet” and applying it strategically to solve clearly defined business problems. The conversation explores why technical founders often struggle with go-to-market communication, how software engineers can learn to explain complex products in simple language, and why customer experience should be seen as one connected journey across marketing, sales, customer success, and revenue operations.

This conversation is especially valuable for founders, CEOs, revenue leaders and AI entrepreneurs who want to move beyond disconnected tools and build smarter, data-driven systems for growth. The episode also reflects the podcast’s focus on helping leaders scale with AI-powered systems, operational efficiency, business intelligence, and strategic leadership.

In this episode, we cover:

• Tim’s journey from software engineering to AI entrepreneurship
• Why building a great product is not enough without strong go-to-market communication
• The importance of customer relationships in SaaS and AI businesses

• How revenue operations connects marketing, sales, and customer experience

• Why AI coding tools are only as strong as the person operating them
• The risks of vibe coding, security gaps, and poorly built AI systems
• How companies misunderstand AI by expecting it to solve undefined problems
• Why customer data, context, and business intelligence are becoming essential for growth

For leaders who want to stop guessing, connect the dots across their customer journey, and use AI to build more intelligent, future-ready companies, this episode offers an insightful look at what AI can actually do when paired with strategy, data, and strong business thinking.

In this episode of the NextGen Studio Podcast, I speak with Jim Recker, co-founder and CEO of Invenir AI, about one of the biggest gaps in modern tech companies: product teams are moving faster than ever but go-to-market teams are struggling to keep up.

After decades working with Silicon Valley companies like WebEx, BlueJeans, Mural, Dialpad and more, Jim shares why the next major business challenge is not just product velocity, it’s revenue velocity.

We explore how AI is transforming product launches, marketing, sales enablement, cybersecurity, enterprise adoption, and the future of work. Jim also shares fresh insights around why AI security, deepfakes, governance, and compliance should now be top priorities for every business leader.

In this conversation, we discuss:

– Why product development has accelerated but go-to-market has not

– The rise of LaunchOps and the gap between DevOps and RevOps

– How AI can reduce launch timelines from weeks to days

– Why AI security and deepfakes are becoming major enterprise risks

– Which jobs are most exposed to AI disruption

– The future of AI engineers, cybersecurity, and human-centered roles

– How enterprises can adopt AI without compromising IP or governance

– Why critical thinking and faster decision-making will matter more than ever

This episode is for founders, CEOs, startup leaders, enterprise executives, and anyone interested in AI, go-to-market strategy, cybersecurity, product launches and the future of work.

NextGen Studio is a business-first podcast for leaders exploring AI, B2B insights and smarter systems for future-ready companies.

What does it really take to transform an enterprise in the age of AI?

In this episode of the NextGen Studio Podcast, I sit down with Partha Gopalan, founder of Adyan Consulting.

We go beyond the surface of AI hype and break down what actually happens inside large organizations when they try to modernize their systems, processes and data.

From legacy ERP systems to AI-ready architectures, Partha shares what separates companies that successfully transform from those that stay stuck.

In this episode, we cover:

– Why data readiness is the #1 blocker to AI success

– The evolution from process-driven to data-driven enterprises

– What most companies get wrong in ERP transformation projects

– How to move from tribal knowledge to real data intelligence

– The role of governance, compliance and risk in enterprise AI

– Why AI won’t replace humans but will redefine every role

– How autonomous agents will shape the next 10–15 years of business