Let's Talk AI

• #86 - Neural Maze: Guiding the Next Wave of AI Engineers | Miguel Otero Pedrido

  The world of AI engineering is exploding. Every week, there’s a new framework, a new tool, a new breakthrough. For beginners and even mid-career engineers, it can feel overwhelming. Where do you even start?In this episode of Let’s Talk AI, Miguel explains why hands-on learning beats passive theory, why systems thinking is the real skill every AI engineer needs, and why observability—understanding what’s happening inside your models and systems—is non-negotiable if you want to build responsibly.For anyone looking to break into AI engineering, this episode offers a roadmap: stop chasing every trend, start focusing on systems, and above all…Build, learn, and grow.Top Insights:Neural Maze aims to help aspiring engineers navigate the overwhelming AI landscape.Building AI systems requires thinking in terms of systems, not just code.Observability is crucial for deploying AI systems in production.Learning by building projects is the most effective way to gain skills.Filo Agents project connects philosophy with gaming, showcasing innovative applications of AI.The value of code has shifted; engineers must adapt to new technologies.Miguel encourages staying out of the hype and focusing on building meaningful projects.He plans to expand Neural Maze into a community for self-contained courses.Connect with Miguel Otero PedridoMiguel Otero Pedirdo on LinkedInMiguel Otero Pedrido on SubstackMiguel Otero Pedrido on Medium.com Miguel Otero Pedrido on GitHubMiguel Otero Pedrido on XThe Neural Maze on SubstackThe Neural Maze on YouTubeConnect with Thomas BustosThomas Bustos on LinkedInLet’s Talk AILet’s Talk AI on YouTubeLet’s Talk AI on SpotifyHosted by Ausha. See ausha.co/privacy-policy for more information.

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• #85 - AI Is Moving Faster Than You Think: Here’s What to Know | Nathan Labenz

  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 Labenz'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 LabenzNathan Labenz’ Website - https://www.nathanlabenz.com/Nathan Labenz on LinkedIn - https://www.linkedin.com/in/nathanlabenzNathan Labenz on X - https://x.com/labenzThe Cognitive Revolution - https://www.cognitiverevolution.ai/Connect with Thomas BustosThomas 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/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.

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• #84 - Entrepreneurship Lessons You Won’t Learn in Business School | Pedro Goes

  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 GoesPedro Goes on LinkedIn - https://www.linkedin.com/in/pedrogoes/InEvent - https://inevent.com/Pedro Goes on X - https://x.com/goesineventConnect with Thomas BustosThomas 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/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.

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• #83 - The Truth About Freelancing in Data Science (And How to Succeed) | Jeremy Arancio

  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 ArancioJeremy Arancio on LinkedIn - https://cz.linkedin.com/in/jeremy-arancioRead his articles - https://medium.com/@jeremyarancioJeremy Arancio on GitHub - https://github.com/JeremyArancioEmail him - [email protected] with Thomas BustosThomas 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/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.

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• #82 - What Every Aspiring Data Engineer Needs to Know in 2025 | Ananth Packkildurai

  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 PackkilduraiAnanth Packkildurai on LinkedIn - https://www.linkedin.com/in/ananthduraiData Engineering Weekly by Ananth Packkildurai - https://www.dataengineeringweekly.com/ Connect with Thomas BustosThomas 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-aiLet’s Talk AI on Spotify - https://open.spotify.com/show/6mVjFvdEkZDCTXpIuuSLAPHosted by Ausha. See ausha.co/privacy-policy for more information.

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