We’re standing at the edge of an AI-driven future, and most people don’t realize how fast we’re getting there.

In this episode of Let’s Talk AI, Nathan Labenz joins us to share insights from years at the forefront of AI development. We cover everything from the disruptive potential of AI-powered content creation to the deep ethical debates around autonomy, alignment, and safety.

This is an urgent conversation because the decisions we make now—about adoption, guardrails, and governance—will define the next decade.

Top Insights:

• There is radical uncertainty about AI's future.

• Nathan Labence's mission is to understand AI's current state.

• AI is transforming content creation and marketing.

• Hands-on experience with AI is crucial for understanding its capabilities.

• AI can provide services that were previously expensive and inaccessible.

• The ideal user experience is for AI to automate tasks seamlessly.

• AI's rapid adoption is unprecedented in history.

• Ethical considerations around AI consciousness are complex.

• AI can outperform humans in specific tasks, but has weaknesses.

• The future of AI holds both exciting opportunities and significant risks.

Connect with Nathan Labenz

• Nathan Labenz’ Website - https://www.nathanlabenz.com/

• Nathan Labenz on LinkedIn - https://www.linkedin.com/in/nathanlabenz

• Nathan Labenz on X - https://x.com/labenz

• The Cognitive Revolution - https://www.cognitiverevolution.ai/

Connect with Thomas Bustos

• Thomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/

• Let’s Talk AI - https://thomasbustos.substack.com/

• Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai

• Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAP

Hosted by Ausha. See ausha.co/privacy-policy for more information.

Most people think entrepreneurship is about having a groundbreaking idea. Pedro Goes disagrees.

In this episode, the CEO of InEvent reveals why ideas are overrated, and why execution, adaptability, and timing matter far more. He shares unfiltered insights into securing funding, scaling globally, and leveraging AI-driven innovation to transform the events industry.

We also dive into remote leadership, the brutal realities of startup life, and the surprising role luck plays in success. If you’ve been fed the “follow your passion” narrative, this episode will challenge everything you thought you knew about entrepreneurship.

Top Insights:

• An idea's worth is tied to its revenue potential.

• AI can transform event technology in innovative ways.

• Starting a company often requires minimal initial investment.

• Persistence is key in securing funding and acceptance into accelerators.

• Founders must maintain a clear vision for their company.

• Effective decision-making involves prioritizing resources wisely.

• Market validation is crucial for product success.

• Iterative growth allows for focus and adaptation in business.

• Building an end-to-end platform enhances value propositions.

• Leadership in remote teams requires fairness and clear communication.

Connect with Pedro Goes

• Pedro Goes on LinkedIn - https://www.linkedin.com/in/pedrogoes/

• InEvent - https://inevent.com/

• Pedro Goes on X - https://x.com/goesinevent

Connect with Thomas Bustos

• Thomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/

• Let’s Talk AI - https://thomasbustos.substack.com/

• Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai

• Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAP

Hosted by Ausha. See ausha.co/privacy-policy for more information.

Data science freelancing is a test of both technical skill and strategic adaptability.

In our conversation with Jérémy Arancio, we dissect the frameworks he uses to thrive: relentless upskilling, leveraging platforms like LinkedIn for visibility, and distinguishing between hype and practical tools in AI.

From the nuanced differences of GenAI vs. NLP to the tactical mindset shift freelancing requires, this episode breaks down what separates sustainable data science careers from those that fizzle out.

Top Insights:

• Freelancing is a means to learn and grow.

• You will never feel fully prepared to start freelancing.

• The journey of freelancing can be both rewarding and challenging.

• AI should be used to solve specific business problems.

• Content creation can help build connections and opportunities.

• Choosing the right vehicle for your career is crucial.

• Growth often comes from discomfort and challenges.

• Networking on platforms like LinkedIn is valuable for career advancement.

• Understanding the difference between Gen.AI and NLP is important.

• Continuous learning is essential in the fast-paced tech industry.

Connect with Jeremy Arancio

• Jeremy Arancio on LinkedIn - https://cz.linkedin.com/in/jeremy-arancio

• Read his articles - https://medium.com/@jeremyarancio

• Jeremy Arancio on GitHub - https://github.com/JeremyArancio

• Email him - jeremyarancio.freelance@gmail.com

  
  

Connect with Thomas Bustos

• Thomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/

• Let’s Talk AI - https://thomasbustos.substack.com/

• Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai

• Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAP

Hosted by Ausha. See ausha.co/privacy-policy for more information.

AI is evolving fast, but are our systems, ethics, and infrastructure keeping up?

In this episode, Thomas Bustos and Marijn Markus break down the complex interplay between innovation and responsibility in artificial intelligence and machine learning. They examine current limitations in explainability and bias, and unpack what it will take to build scalable, transparent, and human-centric systems.

With examples from healthcare and finance, and a strong focus on aligning AI with social good, this episode offers both technical depth and strategic perspective. Whether you’re designing ML pipelines or debating LLM regulation, this conversation delivers insight you won’t want to miss.

Top Insights:

• Ethical and Data Challenges: AI systems must navigate ethical considerations and data privacy concerns, ensuring transparency and accountability.

• Innovation and Impact: AI has the potential to revolutionize industries, from healthcare to finance, by driving advancements and creating new opportunities.

• Regulatory and Legacy Issues: Balancing innovation with necessary regulations and overcoming legacy systems are key challenges for AI adoption.

• Bias and Misinformation: Addressing bias in AI models and combating misinformation are critical for ensuring AI's positive impact on society.

• Job Market Evolution: While AI may automate some jobs, it also creates new opportunities, emphasizing the need for adaptability and skill diversification.

• Human Responsibility: The importance of human oversight in AI systems is crucial, as technology should serve humanity's best interests.

Connect with Marijn Markus

• Marijn Markus on LinkedIn - https://www.linkedin.com/in/marijnmarkus

• Capgemini - https://www.capgemini.com/

  
  

Connect with Thomas Bustos & Let's Talk AI

• Thomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/

• Substack - https://thomasbustos.substack.com/

• Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai

• Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAP

Hosted by Ausha. See ausha.co/privacy-policy for more information.

What do you really need to thrive as a data engineer today?

Ananth Packkildurai joins us to cut through the noise. From his experience building systems at Slack to his current role in data engineering, Ananth reveals what skills truly stand the test of time, like SQL, data modeling, and a deep understanding of user needs.

We also explore how the rise of Generative AI is changing the game, what observability means in practice, and why chasing the latest trend might not be your best move.

Clear, practical, and refreshingly honest.

This episode is for anyone who wants to grow with intention.

Top Insights:

• Data engineering is at a pivotal moment, similar to the industrial revolution.

• The demand for data engineering skills is rapidly increasing.

• Understanding SQL is crucial as it constitutes the majority of data workloads.

• Feature prioritization should focus on high yield, low effort projects.

• Observability is essential for building reliable data systems.

• Scaling challenges often arise from unexpected user demand spikes.

• Product thinking is important in data engineering to meet user needs.

• GenAI has the potential to revolutionize data engineering practices.

• Exploring various aspects of data engineering is beneficial before specializing.

• Real-world observation can enhance understanding of data engineering concepts.

Connect with Ananth Packkildurai

• Ananth Packkildurai on LinkedIn - https://www.linkedin.com/in/ananthdurai

• Data Engineering Weekly by Ananth Packkildurai - https://www.dataengineeringweekly.com/

  
  

Connect with Thomas Bustos

• Thomas Bustos on LinkedIn - https://www.linkedin.com/in/thomasbustos/

• Let’s Talk AI - https://thomasbustos.substack.com/

• Let’s Talk AI on YouTube - https://www.youtube.com/@lets-talk-ai

• Let’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAP

Hosted by Ausha. See ausha.co/privacy-policy for more information.

🎙️ Who is Reuven Lerner?
Reuven Lerner is a seasoned Python and Pandas instructor with over 30 years of experience in programming and teaching. He is dedicated to helping individuals enhance their careers through the Python language. With a background that includes an MIT education in computer science and a PhD in learning sciences, Reuven combines his industry experience with innovative teaching methods to empower learners.

💡 In this episode...
... Reuven shares insights from his extensive career, discussing his current projects that focus on improving online courses and engaging learners through newsletters. He emphasizes the importance of project-based learning and understanding deeper concepts in technology, rather than just syntax. Reuven reflects on the challenges of traditional education and the need for innovative teaching methods. He also addresses the impact of AI on learning and the significance of hands-on experience in skill development. Listeners will find encouragement to embrace programming as a journey and learn how acquiring these skills can lead to fulfilling career opportunities.

Reuven Lerner: https://www.linkedin.com/in/reuven/

Thomas Bustos: https://www.linkedin.com/in/thomasbustos/

Follow Let's Talk AI:
🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/
📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai
🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/

Hosted by Ausha. See ausha.co/privacy-policy for more information.

🎙️ Who is Peter Gostev?

Peter Gostev is the Head of AI at Moonpig, specializing in generative AI and its transformative applications in e-commerce. With a strong background in structured problem-solving and data analytics, Peter emphasizes the importance of collaboration and rapid prototyping to drive innovation in AI projects.

💡 In this episode...

... we explore Peter's journey in the AI landscape, discussing the balance between delivering immediate value and fostering innovative experimentation. He shares insights on the distinctions between classical and generative AI, highlighting their respective use cases in structured and unstructured data. Peter elaborates on how generative AI can enhance data quality and operational efficiency, particularly in customer service through automation and insights extraction.

The conversation also addresses the challenges of integrating AI into software development, advocating for specialized teams to effectively manage new technologies. Peter encourages continuous learning and experimentation in AI, urging listeners to engage with emerging tools and models to drive innovation in their own practices.

Peter Gostev: https://www.linkedin.com/in/peter-gostev/

Follow Let's Talk AI:

✉️ Newsletter 👉 http://eepurl.com/ijZ8qz

🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/

📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai

📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/

🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/

🌐 Website 👉 https://lets-talk-ai.com/

Hosted by Ausha. See ausha.co/privacy-policy for more information.

🎙️ Who is Daniel Lenton?

Daniel Lenton is the CEO of Unify, on a mission tounify and simplify the LLM landscape. He has a background in machine learning deployment, as well as in robotics and computer vision. Daniel is an intellectual and creative problem solver who values consistency, balance, and expectation management when building a startup.

💡 In this episode...

... we discuss Daniel's background in machine learning deployment and pursuit of interests in robotics and computer vision. He shares insights on effective communication, user discovery, and gaining insights from customer sales calls for building a successful start-up. He values consistency, balance, and expectation management and credits YC for giving him productivity tips to achieve this. He believes in prioritizing joy and ethics and acknowledges advancements and limitations in AI and AGI.

Daniel Lenton: https://www.linkedin.com/in/daniellenton/

Thomas Bustos: https://www.linkedin.com/in/thomasbustos/

Artistic Direction & Video: Maxence Kerhoas

Follow Let's Talk AI:

✉️ Newsletter 👉 http://eepurl.com/ijZ8qz

🎙️ Podcast 👉 http://smartlink.ausha.co/let-s-talk-ai/

📹 Youtube 👉 https://www.youtube.com/@lets-talk-ai

📷 Instagram 👉 https://www.instagram.com/lets_talk_ai/

🎞️ TikTok 👉 https://www.tiktok.com/@letstalkai/

🌐 Website 👉 https://lets-talk-ai.com/

Hosted by Ausha. See ausha.co/privacy-policy for more information.