app01 Wed, 14 Oct 2026 01:47:29 +0000 Fireside (https://fireside.fm) Teaching Python - Episodes Tagged with “Llm” https://www.teachingpython.fm/tags/llm Thu, 28 Aug 2025 00:00:00 -0400 Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology. en-us episodic We're two computer science educators learning and teaching Python Sean Tibor and Kelly Paredes Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology. no Python, Python programming, learn Python, teaching Python, computer science education, coding education, programming for beginners, Python for beginners, computational thinking, code literacy, debugging, software development, software engineering, data science, artificial intelligence, AI literacy, AI-assisted coding, generative AI, machine learning, cybersecurity, cloud computing, cloud infrastructure, APIs, databases, systems thinking, technical education, STEM education, educational technology, edtech, curriculum design, instructional design, professional learning, teacher professional development, coding for students, computer science curriculum, physical computing, robotics, responsible AI, digital literacy, data literacy, technology leadership, developer education, technical coaching, lifelong learning, learning to code, teaching programming, real-world programming, coding with AI, Python podcast, computer science podcast, technology education podcast, programming podcast Sean Tibor and Kelly Paredes sean.tibor@gmail.com Episode 150: LLMs with Simon WIllison https://www.teachingpython.fm/150 5f687661-ce06-44b5-935e-fb1a2394c97b Thu, 28 Aug 2025 00:00:00 -0400 Sean Tibor and Kelly Paredes 150 LLMs with Simon WIllison full Sean Tibor and Kelly Paredes Kelly and Sean chat with Simon Willison about the promises and perils of using large language models in Python education. They explore how LLMs can accelerate learning while discussing security concerns like prompt injection, the importance of building foundational skills before introducing AI tools, and strategies for maintaining student engagement in an AI-powered world. 1:36:27 no <p>In this milestone 150th episode, hosts Kelly Schuster-Paredes and Sean Tibor sit down with Simon Willison, co-creator of Django and creator of Datasette and LLM tools, for an in-depth conversation about artificial intelligence in Python education.</p> <p>The discussion covers the current landscape of LLMs in coding education, from the benefits of faster iteration cycles to the risks of students losing that crucial "aha moment" when they solve problems independently. Simon shares insights on prompt injection vulnerabilities, the importance of local models for privacy, and why he believes LLMs are much harder to use effectively than most people realize.</p> <p>Key topics include:</p> <ul> <li><strong>Educational Strategy</strong>: When to introduce AI tools vs. building foundational skills first</li> <li><strong>Security Concerns</strong>: Prompt injection attacks and their implications for educational tools</li> <li><strong>Student Engagement</strong>: Maintaining motivation and problem-solving skills in an AI world<br></li> <li><strong>Practical Applications</strong>: Using LLMs for code review, debugging, and rapid prototyping</li> <li><strong>Privacy Issues</strong>: Understanding data collection and training practices of major AI companies</li> <li><strong>Local Models</strong>: Running AI tools privately on personal devices</li> <li><strong>The "Jagged Frontier"</strong>: Why LLMs excel at some tasks while failing at others</li> </ul> <p>Simon brings 20 years of Django experience and deep expertise in both web development and AI tooling to discuss how educators can thoughtfully integrate these powerful but unpredictable tools into their classrooms. The conversation balances excitement about AI's potential with realistic assessments of its limitations and risks.</p> <p>Whether you're a coding educator trying to navigate the AI revolution or a developer interested in the intersection of education and technology, this episode provides practical insights for working with LLMs responsibly and effectively.</p> <p>Resources mentioned:</p> <ul> <li>Simon's blog: simonwillison.net</li> <li>Mission Encodable curriculum</li> <li>Datasette and LLM tools</li> <li>GitHub Codespaces for safe AI experimentation</li> </ul><p>Special Guest: Simon Willison.</p> artificial intelligence, LLM, large language models, Python education, Django, Simon Willison, prompt injection, coding education, AI in schools, programming curriculum, ChatGPT, Gemini, educational technology, computer science teaching In this milestone 150th episode, hosts Kelly Schuster-Paredes and Sean Tibor sit down with Simon Willison, co-creator of Django and creator of Datasette and LLM tools, for an in-depth conversation about artificial intelligence in Python education.

The discussion covers the current landscape of LLMs in coding education, from the benefits of faster iteration cycles to the risks of students losing that crucial "aha moment" when they solve problems independently. Simon shares insights on prompt injection vulnerabilities, the importance of local models for privacy, and why he believes LLMs are much harder to use effectively than most people realize.

Key topics include:

  • Educational Strategy: When to introduce AI tools vs. building foundational skills first
  • Security Concerns: Prompt injection attacks and their implications for educational tools
  • Student Engagement: Maintaining motivation and problem-solving skills in an AI world
  • Practical Applications: Using LLMs for code review, debugging, and rapid prototyping
  • Privacy Issues: Understanding data collection and training practices of major AI companies
  • Local Models: Running AI tools privately on personal devices
  • The "Jagged Frontier": Why LLMs excel at some tasks while failing at others

Simon brings 20 years of Django experience and deep expertise in both web development and AI tooling to discuss how educators can thoughtfully integrate these powerful but unpredictable tools into their classrooms. The conversation balances excitement about AI's potential with realistic assessments of its limitations and risks.

Whether you're a coding educator trying to navigate the AI revolution or a developer interested in the intersection of education and technology, this episode provides practical insights for working with LLMs responsibly and effectively.

Resources mentioned:

  • Simon's blog: simonwillison.net
  • Mission Encodable curriculum
  • Datasette and LLM tools
  • GitHub Codespaces for safe AI experimentation

Special Guest: Simon Willison.

Support Teaching Python

]]> In this milestone 150th episode, hosts Kelly Schuster-Paredes and Sean Tibor sit down with Simon Willison, co-creator of Django and creator of Datasette and LLM tools, for an in-depth conversation about artificial intelligence in Python education.

The discussion covers the current landscape of LLMs in coding education, from the benefits of faster iteration cycles to the risks of students losing that crucial "aha moment" when they solve problems independently. Simon shares insights on prompt injection vulnerabilities, the importance of local models for privacy, and why he believes LLMs are much harder to use effectively than most people realize.

Key topics include:

  • Educational Strategy: When to introduce AI tools vs. building foundational skills first
  • Security Concerns: Prompt injection attacks and their implications for educational tools
  • Student Engagement: Maintaining motivation and problem-solving skills in an AI world
  • Practical Applications: Using LLMs for code review, debugging, and rapid prototyping
  • Privacy Issues: Understanding data collection and training practices of major AI companies
  • Local Models: Running AI tools privately on personal devices
  • The "Jagged Frontier": Why LLMs excel at some tasks while failing at others

Simon brings 20 years of Django experience and deep expertise in both web development and AI tooling to discuss how educators can thoughtfully integrate these powerful but unpredictable tools into their classrooms. The conversation balances excitement about AI's potential with realistic assessments of its limitations and risks.

Whether you're a coding educator trying to navigate the AI revolution or a developer interested in the intersection of education and technology, this episode provides practical insights for working with LLMs responsibly and effectively.

Resources mentioned:

  • Simon's blog: simonwillison.net
  • Mission Encodable curriculum
  • Datasette and LLM tools
  • GitHub Codespaces for safe AI experimentation

Special Guest: Simon Willison.

Support Teaching Python

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