Podcasts about prompt engineering

AI Assisted Coding: Pachinko Coding—What They Don't Tell You About Building Apps with Large Language Models, With Alan Cyment In this BONUS episode, we dive deep into the real-world experience of coding with AI. Our guest, Alan Cyment, brings honest perspectives from the trenches—sharing both the frustrations and breakthroughs of using AI tools for software development. From "Pachinko coding" addiction loops to "Mecha coding" breakthroughs, Alan explores what actually works when building software with large language models. From Thermomix Dreams to Pachinko Reality "I bought into the Thermomix coding promise—describe the whole website and it would spit out the finished product. It was a complete disaster." Alan started his AI coding journey with high expectations, believing he could simply describe a complete application and receive production-ready code. The reality was far different. What he discovered instead was an addictive cycle he calls "Pachinko coding" (Pachinko, aka Slot Machines in Japan)—repeatedly feeding error messages back to the AI, hoping each iteration would finally work, while burning through tokens and time. The AI's constant reassurances that "this time I fixed it" created a gambling-like feedback loop that left him frustrated and out of pocket, sometimes spending over $20 in API credits in a single day. The Drunken PhD with Amnesia "It felt like working with a drunken PhD with amnesia—so wise and so stupid at the same time." Alan describes the maddening experience of anthropomorphizing AI tools that seem brilliant one moment and completely lost the next. The key breakthrough came when he stopped treating the AI as a person and started seeing it as a function that performs extrapolations—sometimes accurate, sometimes wildly wrong. This mental shift helped him manage expectations and avoid the "rage coding" that came from believing the AI should understand context and maintain consistency like a human collaborator. Making AI Coding Actually Work "I learned to ask for options explicitly before any coding happens. Give me at least three options and tell me the pros and cons." Through trial and error, Alan developed practical strategies that transformed AI from a frustrating Pachinko machine into a useful tool: Ask for options first: Always request multiple approaches with pros and cons before any code is generated Use clover emoji convention: Implement a consistent marker at the start of all AI responses to track context Small steps and YAGNI principles: Request tiny, incremental changes rather than large refactoring Continuous integration: Demand the AI run tests and checks after every single change Explicit refactoring requests: Regularly ask for simplification and readability improvements Take two steps back: When stuck in a loop, explicitly tell the AI to simplify and start fresh Choose the right tech stack: Use technologies with abundant training data (like Svelte over React Native in Alan's experience) The Mecha Coding Breakthrough "When it worked, I felt like I was inside a Lego Mecha robot—the machine gave me superpowers, but I was still the one in control." Alan successfully developed a birthday reminder app in Swift in just one day, despite never having learned Swift. He made architectural decisions and guided the development without understanding the syntax details. This experience convinced him that AI represents a genuine new level of abstraction in programming—similar to the jump from assembly language to high-level languages, or from procedural to object-oriented programming. You can now think in English about what you want, while the AI handles the accidental complexity of syntax and boilerplate. The Cost Reality Check "People writing about vibe coding act like it's free. But many people are going to pay way more than they would have paid a developer and end up with empty hands." Alan provides a sobering cost analysis based on his experience. Using DeepSeek through Aider, he typically spends under $1 per day. But when experimenting with premium models like Claude Sonnet 3.5, he burned through $5 in just minutes. The benchmark comparisons are revealing: DeepSeek costs $4 for a test suite, DeepSeek R1 plus Sonnet costs $16, while Open AI's O1 costs $190. For non-developers trying to build complete applications through pure "vibe coding," the costs can quickly exceed what hiring a developer would cost—with far worse results. When Thermomix Actually Works "For small, single-purpose scripts that I'm not interested in learning about and won't expand later, the Thermomix experience was real." Despite the challenges, Alan found specific use cases where AI truly delivers on the "just describe it and it works" promise. Processing Zoom attendance logs, creating lookup tables for video effects, and other single-file scripts worked remarkably well. The pattern: clearly defined context, no need for ongoing maintenance, and simple enough to verify the output without deep code inspection. For these thermomix moments, AI proved genuinely transformative. The Pachinko Trap and Tech Stack Matters "It became way more stable when I switched to Svelte from React Native and Flutter, even following the same prompting practices. The AI is just more proficient in certain tech stacks." Alan discovered that some frameworks and languages work dramatically better with AI than others, likely due to the amount of training data available. His e-learning platform attempts with React Native and Flutter kept breaking, but switching to Svelte with web-based deployment became far more stable. This suggests a crucial strategy: choose mainstream, well-documented technologies when planning AI-assisted projects. From Coding to Living with AI Alan has completely stopped using traditional search engines, relying instead on LLMs for everything from finding technical documentation to getting recommendations for books based on his interests. While he acknowledges the risk of hallucinations, he finds the semantic understanding capabilities too valuable to ignore. He's even used image analysis to troubleshoot his father's cable TV problems and figure out hotel air conditioning controls. The Agile Validation "My only fear is confirmation bias—but the conclusion I see other experienced developers reaching is that the only way to make LLMs work is by making them use agility. So look at who's dead now." Alan notes the irony that the AI coding tools that actually work all require traditional software engineering best practices: small iterations, test-driven development, continuous integration, and explicit refactoring. The promise of "just describe what you want" falls apart without these disciplines. Rather than replacing software engineering principles, AI tools seem to validate their importance. About Alan Cyment Alan Cyment is a consultant, trainer, and facilitator based in Buenos Aires, specializing in organizational fluency, agile leadership, and software development culture change. A Certified Scrum Trainer with deep experience across Latin America and Europe, he blends agile coaching with theatre-based learning to help leaders and teams transform. You can link with Alan Cyment on LinkedIn.

In this issue of the Future of Cyber newsletter, Sean Martin digs into a topic that's quietly reshaping how software gets built—and how it breaks: the rise of AI-powered coding tools like ChatGPT, Claude, and GitHub Copilot.These tools promise speed, efficiency, and reduced boilerplate—but what are the hidden trade-offs? What happens when the tools go offline, or when the systems built through them are so abstracted that even the engineers maintaining them don't fully understand what they're working with?Drawing from conversations across the cybersecurity, legal, and developer communities—including a recent legal tech conference where law firms are empowering attorneys to “vibe code” internal tools—this article doesn't take a hard stance. Instead, it raises urgent questions:Are we creating shadow logic no one can trace?Do developers still understand the systems they're shipping?What happens when incident response teams face AI-generated code with no documentation?Are AI-generated systems introducing silent fragility into critical infrastructure?The piece also highlights insights from a recent podcast conversation with security architect Izar Tarandach, who compares AI coding to junior development: fast and functional, but in need of serious oversight. He warns that organizations rushing to automate development may be building brittle systems on shaky foundations, especially when security practices are assumed rather than applied.This is not a fear-driven screed or a rejection of AI. Rather, it's a call to assess new dependencies, rethink development accountability, and start building contingency plans before outages, hallucinations, or misconfigurations force the issue.If you're a CISO, developer, architect, risk manager—or anyone involved in software delivery or security—this article is designed to make you pause, think, and ideally, respond.

Anita Verma is Senior Advisor at Dell Technologies. The discussion centres around employee influence, thought leadership, and how organisations can harness their people as authentic brand advocates. With over 25 years of experience in learning and development, she has successfully managed global programs, developed strategic partnerships, and created engaging content to drive a sales pipeline that serves all IT audiences, at all levels too. Anita is certified in Generative AI and Prompt Engineering and hold a National Diploma in Business Administration and Management from Richmond upon Thames College, and a Level 4 qualification in Adult Teaching from City & Guilds of London Art School. Trained by the Association of Talent Development, Boston, USA in the art of Creative Training Techniques under the instruction of Bob Pyke. Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome back to the Alt Goes Mainstream podcast.Today's episode provides a fascinating window into the world of private equity value creation and how AI can help transform both portfolio company and investment firm processes and operations to create value.We sat down in New York with Hg Partner and Head of Value Creation Chris Kindt to dive into how he spearheaded the growth of the firm's in-house value creation efforts and has built a high-performing team to meet the evolving needs of portfolio companies.Chris brings 15 years of experience in architecting and driving value creation to bear, with 11 years of experience at Hg and another 8 years as a consultant at BCG and Parthenon.Chris and his team are responsible for driving value across a portfolio of 55 companies that represents over $180B in enterprise value and would represent the second largest software company in Europe after SAP if it were a conglomerate.Chris and I had a thought-provoking discussion about value creation and the impact of AI on investing and operating companies. We discussed:How to build a high-performing value creation team.Where value creation has the biggest impact.How AI is transforming investment processes.How Hg has become an “AI-first” investment firm.Where AI will have the most impact in a company today and why agentic AI is transforming certain roles and processes within companies.How professionals can generate the most leverage from utilizing AI – without having cognitive decline.Why prompting and prompt engineering is so critical in the age of AI (and how you can use your weekends to perfect prompt engineering).How a management team can buy into AI and why the current time period represents an interesting opportunity for incumbents, particularly for those building mission-critical enterprise software.Thanks Chris for sharing your expertise and wisdom on company building and AI. We hope you enjoy.Note: this episode was filmed in August 2025.A word from AGM podcast sponsor, Ultimus Fund SolutionsThis episode of Alt Goes Mainstream is brought to you by Ultimus Fund Solutions, a leading full-service fund administrator for asset managers in private and public markets. As private markets continue to move into the mainstream, the industry requires infrastructure solutions that help funds and investors keep pace. In an increasingly sophisticated financial marketplace, investment managers must navigate a growing array of challenges: elaborate fund structures, specialized strategies, evolving compliance requirements, a growing need for sophisticated reporting, and intensifying demands for transparency.To assist with these challenging opportunities, more and more fund sponsors and asset managers are turning to Ultimus, a leading service provider that blends high tech and high touch in unique and customized fund administration and middle office solutions for a diverse and growing universe of over 450 clients and 1,800 funds, representing $500 billion assets under administration, all handled by a team of over 1,000 professionals. Ultimus offers a wide range of capabilities across registered funds, private funds and public plans, as well as outsourced middle office services. Delivering operational excellence, Ultimus helps firms manage the ever-changing regulatory environment while meeting the needs of their institutional and retail investors. Ultimus provides comprehensive operational support and fund governance services to help managers successfully launch retail alternative products.Visit www.ultimusfundsolutions.com to learn more about Ultimus' technology enhanced services and solutions or contact Ultimus Executive Vice President of Business Development Gary Harris on email at gharris@ultimusfundsolutions.com.We thank Ultimus for their support of alts going mainstream.Show Notes00:00 Message from our Sponsor, Ultimus01:18 Welcome to the Alt Goes Mainstream Podcast02:10 Guest Introduction: Chris Kindt03:58 Chris Kindt's Background and Journey05:43 Value Creation at Hg06:55 Pre-Investment and Diligence Process07:44 Management Team Dynamics08:40 Common Value Creation Interventions11:14 Building a Cross-Functional Team12:31 Scaling the Value Creation Team15:40 Measuring Value Creation Impact17:49 Investment Philosophy: Inch Wide, Mile Deep19:28 Partnerships with Management Teams20:03 Embedding AI in Value Creation20:24 Internal vs External AI Applications21:47 AI First Culture22:18 Effective AI Utilization24:04 Prompt Engineering and Whispering26:25 Choosing the Right AI Models26:50 AI Models: Strengths and Weaknesses27:42 Transformative Impact of AI28:21 Skills Needed in the AI Era28:26 AI's Role in Investment Firms28:55 Core Insights and Judgements29:04 The Core Skillset and Efficiency29:12 Philosophical Questions on AI and Talent Development30:18 Building Grit in the Age of AI31:12 Maintaining Discipline with AI32:08 AI as a Value Creation Lever32:35 Operational Efficiency and Copilots33:43 Emergence of Reasoning Models and Agentic Frameworks34:31 10x Efficiency in Engineering36:24 Challenges in Implementing AI37:16 AI Immersion Strategy Days39:52 Organizational Agility and AI42:15 AI's Impact on Investment Strategies43:26 AI in Mergers and Acquisitions45:29 The Importance of Proprietary Data47:12 AI Fatigue and Disillusionment48:07 Building AI Products and Agentic Products48:58 Hg's Internal AI Incubator49:59 The Next Wave of AI51:19 Voice and Multimodality in AI51:55 Globalization and Internationalization of AI53:35 Overestimating and Underestimating AI's Impact54:54 The Competitive Landscape of AI55:42 The Future of Value Creation with AI56:23 Conclusion and Final ThoughtsEditing and post-production work for this episode was provided by The Podcast Consultant.

This is an outstanding AI based discussion of my post, What's All The Fuss, Prompt Engineering Isn't New.  I've noticed the discussions seem much better when they are talking about AI.  I suppose that's natural, we love talking about ourselves  ;-)  Enjoy! Here's the link to the original post:  https://partnersinexcellenceblog.com/whats-all-the-fuss-prompt-engineeringisnt-new/ 

In this Alter Everything Episode, we sit down with Nick Schrock, CTO and founder of Dagster Labs, to discuss the essentials of AI data readiness, the challenges organizations face in context engineering, and the importance of governance in AI-driven data workflows. If you choose to tune in, you will learn how to prepare your data for AI, implement effective data pipeline strategies, and navigate organizational AI mandates. Panelists: Nick Shrock, Founder @ Dagster Labs - LinkedInMegan Bowers, Sr. Content Manager @ Alteryx - @MeganBowers, LinkedInShow notes: Dagster Labs Interested in sharing your feedback with the Alter Everything team? Take our feedback survey here!This episode was produced by Megan Bowers, Mike Cusic, and Matt Rotundo. Special thanks to Andy Uttley for the theme music.

New Episode! Tell us your feedback! Is Your Company Safe From AI Attacks?This episode covers the intersection of artificial intelligence and cybersecurity, exploring how AI can be used for both protection and malicious purposes. We examine how AI is used to create advanced ai cybercrime and deep fakes, and the rising threat of social engineering attacks. Learn how ai cybersecurity can help defend against ai hackers and other emerging threats. Feeling Kind? Consider Supporting Our Channel by subscribing! Over 84% of viewers do not subscribe to our channel! 

John Berryman (Arcturus Labs; early GitHub Copilot engineer; co-author of Relevant Search and Prompt Engineering for LLMs) has spent years figuring out what makes AI applications actually work in production. In this episode, he shares the “seven deadly sins” of LLM development — and the practical fixes that keep projects from stalling. From context management to retrieval debugging, John explains the patterns he's seen succeed, the mistakes to avoid, and why it helps to think of an LLM as an “AI intern” rather than an all-knowing oracle. We talk through: - Why chasing perfect accuracy is a dead end - How to use agents without losing control - Context engineering: fitting the right information in the window - Starting simple instead of over-orchestrating - Separating retrieval from generation in RAG - Splitting complex extractions into smaller checks - Knowing when frameworks help — and when they slow you down A practical guide to avoiding the common traps of LLM development and building systems that actually hold up in production. LINKS: Context Engineering for AI Agents, a free, upcoming lightning lesson from John and Hugo (https://maven.com/p/4485aa/context-engineering-for-ai-agents) The Hidden Simplicity of GenAI Systems, a previous lightning lesson from John and Hugo (https://maven.com/p/a8195d/the-hidden-simplicity-of-gen-ai-systems) Roaming RAG – RAG without the Vector Database, by John (https://arcturus-labs.com/blog/2024/11/21/roaming-rag--rag-without-the-vector-database/) Cut the Chit-Chat with Artifacts, by John (https://arcturus-labs.com/blog/2024/11/11/cut-the-chit-chat-with-artifacts/) Prompt Engineering for LLMs by John and Albert Ziegler (https://amzn.to/4gChsFf) Relevant Search by John and Doug Turnbull (https://amzn.to/3TXmDHk) Arcturus Labs (https://arcturus-labs.com/) Watch the podcast on YouTube (https://youtu.be/mKTQGKIUq8M) Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk)

AI Quick Take: Mastering Prompt Engineering On this episode host Adam Turinas explores the critical concept of prompt engineering. This skill is fundamental in transforming how you use AI tools like ChatGPT, Claude, and Perplexity in your professional work. Most people are using these robust AI systems like glorified search engines, but to unlock their full potential for marketing, sales enablement, and content creation, mastering prompt engineering is essential. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen/

- Simulation Theory, AI, and Robots for Survival (0:11) - Global Political Tensions and Predictions (1:33) - Economic and Social Implications of Global Conflict (6:49) - The Era of Easy Money and Affordable Goods Ending (7:55) - Preparing for a Collapsing Economy (20:50) - Using AI and Robots for Survival and Decentralization (30:50) - The Role of Drones and Ground-Based Robots (43:32) - The Future of AI and Robotics in Society (56:02) - The Importance of Financial Preparedness (1:01:21) - The Role of AI in Defining Wealth and Success (1:13:48) - Mike Adams' Background and Skills (1:23:20) - The Importance of Clear Instructions for AI (1:25:50) - AI Agents and Their Applications (1:28:42) - Prompt Engineering and AI Skills (1:33:02) - Philosophical and Ethical Considerations of AI (1:34:33) - AI and Human Depopulation Vectors (1:43:05) - The Role of AI in Government and Society (1:47:35) - The Future of Human-AI Relationships (2:00:04) - The Ethical Implications of AI Development (2:02:59) - The Potential for AI to Replace Human Labor (2:04:41) For more updates, visit: http://www.brighteon.com/channel/hrreport  NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

Unlock the future of recruiting with this episode of The Full Desk Experience. In this special FDE+, host Kortney Harmon sits down with Matt Strain — seasoned technology leader, AI educator, and founder of The Prompt. Drawing on his experience as Adobe's former Head of Innovation, Matt brings a fresh perspective on how artificial intelligence is reshaping the recruiting and staffing industry.In their conversation, Matt explores why curiosity, resilience, and a willingness to experiment are essential traits for executives and recruiters who want to stand out in the age of AI. He shares real-world examples of how AI can streamline everything from sourcing and screening to assessment and selection, while also emphasizing where human judgment and trust remain irreplaceable. Along the way, he introduces a practical framework of mindset, skill set, and tool set that leaders can use to navigate uncertainty, integrate AI confidently, and drive stronger outcomes.Whether you're dipping your toes into AI for the first time or looking to refine your strategy, this discussion offers hands-on insights you can put into practice right away. Tune in to discover how to transform AI-driven curiosity into a true competitive advantage._________________Follow Matt Strain on LinkedIn at: LinkedIn | MattFollow Crelate on LinkedIn: https://www.linkedin.com/company/crelate/Want to learn more about Crelate? Book a demo hereSubscribe to our newsletter: https://www.crelate.com/blog/full-desk-experience

ভাবুন তো আপনি যদি একটি কম্পিউটারকে এমনভাবে কথা বলতে শেখাতে পারেন যেন সে আপনার জন্য ব্লগ লিখে দেয়, ছবি আঁকে, কোড বানায়, এমনকি ব্যবসায়িক পরামর্শও দেয় তাও আবার একেবারে আপনার ইচ্ছেমতো! তাহলে ব্যাপার টা কেমন হবে? আপনার কাছে বিষয়টা অসম্ভব মনে হচ্ছে না? এই অসম্ভবকে সম্ভব করেছে AI বা কৃত্রিম বুদ্ধিমত্তা। আর এই AI-কে সঠিকভাবে কাজ করাতে যে দক্ষতা প্রয়োজন সেটাই হলো Prompt ইঞ্জিনিয়ারিং। এই বিষয় নিয়ে এই Podcast এ আলোচনা করা হয়েছে। Artificial Intelligence-এর অসীম ক্ষমতাকে কাজে লাগিয়ে ফ্রিল্যান্সিং করে খুব সহজে প্রতি মাসে ২০০০-৩০০০ ডলার ইনকাম করতে চাইলে, অথবা AI-এর সাহায্যে কন্টেন্ট ক্রিয়েট, ডিজাইন সেল এবং আরো বিভিন্ন উপায়ে Passive Income করতে চাইলে জয়েন করুন এই কোর্সে ➤ https://www.msbacademy.com/course/artificial-intelligence-masterclass

Prompt engineering can feel like a secret language. April Dunnam returns to explain how Prompt Coach helps everyone speak it more clearly. From refining prompts to checking compliance and teaching best practices, Prompt Coach provides users with a smoother start to using Copilot and agents. We also cover when to roll it out, how it supports adoption, and why prompt libraries matter.   Prompt Coach is open source. Explore it and the community prompt libraries here: https://github.com/pnp/powerplatform-prompts https://github.com/pnp/copilot-prompts

In this AI Quick Take episode, I explore the critical concept of prompt engineering. This skill is fundamental in transforming how you use AI tools like ChatGPT, Claude, and Perplexity in your professional work. Most people are using these robust AI systems like glorified search engines, but to unlock their full potential for marketing, sales enablement, and content creation, mastering prompt engineering is essential.AI systems are competent, but they need context, constraints, and clear objectives to deliver truly valuable results. In the episode, I will review the Five Layer Framework for crafting effective prompts: Define the role and contextSet specific objectivesClarify audience and use caseEstablish format and constraintsDefine success criteriaI also walk through practical examples in market research, campaign planning, and sales enablement, showing how this structured approach can save 20-30 hours of manual work while delivering superior results.Key Topics Covered:"(00:00:00) - Episode Introduction""(00:03:00) - What is Prompt Engineering?""(00:06:00) - Basic vs. Engineered Prompt Example""(00:07:00) - The Five Layer Framework""(00:11:00) - Using AI to Help Create Better Prompts""(00:12:00) - Market Research and Analysis Applications""(00:14:00) - Campaign Strategy and Planning""(00:15:00) - Sales Enablement Applications""(00:16:00) - Advanced Prompt Engineering Techniques""(00:20:00) - Common Mistakes to Avoid""(00:21:00) - Closing and Resources"For a detailed walkthrough of AI prompt engineering, ⁠check out our "How To" guide.⁠If you are interested in discussing this or any other topic, let's have a chat.  ⁠Reach out to me directly⁠ to schedule a no-obligation discussion. This isn't a sales call, but rather an opportunity to talk through your LinkedIn questions and challenges.⁠Follow me on LinkedIn⁠.Subscribe to The HealthTech Marketing Show on ⁠Spotify⁠ or watch us on ⁠YouTube⁠ for more insights into marketing, AI, ABM, buyer journeys, and beyond!Thank you to our presenting sponsors, ⁠HIMSS⁠, a leader in advancing health equity, digital innovation, and data-driven care through technology, policy, and community collaboration. And also ⁠HealthcareNOW⁠, 24/7 expert shows, interviews, and podcasts, powering healthcare leaders with innovation, policy, and strategy insights.

En este episodio, exploraremos la ingeniería de prompts, definida como el diseño y optimización de instrucciones para la inteligencia artificial avanzada. Es una habilidad crucial para obtener resultados precisos, útiles y en el formato que necesitas. En el mundo actual, saber formular buenas preguntas a la IA se ha convertido en el "nuevo buscar en Google" y en una ventaja competitiva indispensable. Es aprender a comunicarse eficazmente con la IA. Aprenderás por qué la ingeniería de prompts es fundamental para sacarle provecho a la IA más allá de lo básico, mejorando la calidad, precisión y utilidad de las respuestas y reduciendo las "alucinaciones" de los modelos. Esta práctica es un proceso iterativo que implica entender cómo funcionan los modelos de IA generativa, cómo procesan e interpretan el texto y cómo pequeñas variaciones en la redacción del prompt pueden generar resultados completamente diferentes. Cubriremos técnicas esenciales y avanzadas, aplicables a modelos de lenguaje grandes (LLMs) como GPT, Gemini, Grock, Claude y Deepseek, así como a IA de generación de imágenes. Recordaremos que los LLM son motores de predicción que pronostican las siguientes palabras basándose en el prompt, no poseen conciencia en el sentido humano. Las técnicas que abordaremos incluyen: • Roll Prompting o "Actúa como": Asignar un rol específico a la IA (experto, tutor, profesor, gerente de marketing, agente de ventas, médico, psicólogo) para guiar una comunicación contextualizada y precisa. La especificidad del rol (ej., "doctor especializado en pediatría") es clave para obtener mejores resultados. • Formato de Salida o Formatting Enhancement: Indicar el formato exacto que deseas para la respuesta (JSON, XML, YAML, tabular, viñetas, cadenas de texto específicas, etc.). Esto es crucial para la manipulación posterior de los datos. • Shot Prompting (Zero, One, Few-Shot): Proporcionar ejemplos (ninguno, uno o varios) para guiar al modelo hacia el tipo, formato y estructura de respuesta deseado. Múltiples ejemplos ayudan a captar la complejidad y las variaciones del escenario. • Uso de Delimitadores: Emplear palabras clave o símbolos (comillas triples, triples guiones, corchetes angulares, tags de XML, triple igual) para separar diferentes partes del prompt (instrucciones, contexto, ejemplos) para un mejor entendimiento por parte de la IA y para prevenir ataques de "prompt injection". • Contexto Detallado: Ofrecer información exhaustiva sobre el escenario, la empresa, la tarea o la audiencia para que la IA genere respuestas más relevantes y adaptadas. • Instrucciones Paso a Paso (Chain of Thought / Guided Prompting): Desglosar tareas complejas en una secuencia clara de pasos, solicitando a la IA que "piense en voz alta" o que "razone paso a paso" para mejorar la precisión y calidad de su razonamiento. • Metaprompting: Usar la IA para que te ayude a crear o mejorar tus propios prompts, pidiéndole que actúe como un ingeniero de prompts. • Placeholders: Utilizar marcadores temporales dentro de un prompt para representar variables o texto que será reemplazado, muy útil para generar plantillas reutilizables. • Patrón de Reflexión: Indicar al modelo que trabaje en su propia solución y luego la compare con otra (que él mismo pudo haber creado o que fue proporcionada) para mejorar la calidad de las respuestas. • Patrón React (Reasoning + Action): Invita al modelo a razonar y a tomar acciones (como visitar sitios web o realizar búsquedas específicas) antes de llegar a una conclusión, siendo más potente que el Chain of Thought en ciertos escenarios. • Filtro Semántico: Utilizado para identificar y filtrar datos confidenciales (como números de tarjeta de crédito) en documentos o prompts, asegurando la privacidad y el cumplimiento de regulaciones. • Prompt Highlighting: Emplear negritas, subrayados o viñetas para enfocar la atención del LLM y obtener mejores respuestas. • Instrucciones Positivas vs. Restricciones Negativas: Es más claro decirle a la IA lo que quieres que haga (instrucción positiva) que lo que no quieres que haga (restricción negativa), aunque estas últimas son útiles para evitar contenido dañino o formatos estrictos. • Automatic Prompt Engineering: Un método para generar prompts de manera automática, utilizando metaprompts, donde un prompt escribe otros prompts. • Roles del Prompt (Sistema, Usuario, Asistente): Comprender cómo interactúan estos roles para dar contexto, propósito e instrucciones específicas al modelo, y cómo el rol de asistente puede usarse para simular ejemplos y mejorar la calidad. Este podcast está especialmente diseñado para analistas de datos que buscan potenciar su trabajo con la inteligencia artificial, con ejemplos prácticos en la transformación, creación de cálculos y adopción de visualizaciones de datos. La práctica constante es clave para dominar esta habilidad. ¡Prepárate para llevar tus habilidades de comunicación con la IA al siguiente nivel!

In dieser Folge spreche ich offen über die Chancen und Herausforderungen, die Künstliche Intelligenz für unsere Arbeitswelt mit sich bringt. Ich zeige auf, warum es nicht um Jobverlust, sondern um Jobwandel geht, und wie wir alle von neuen digitalen Kompetenzen profitieren können. Basierend auf aktuellen Studien und meinen eigenen Erfahrungen gebe ich Einblicke in die Berufe der Zukunft, von KI-Compliance bis Prompt Engineering. Es geht darum, die eigene Rolle aktiv zu gestalten und den Wandel als Karrierebooster zu nutzen. Lass dich inspirieren, wie du mit dem richtigen Mindset und Eigeninitiative deine Karriere neu denken und gestalten kannst.

For every English learner, AI can feel like both a miracle and a threat. Can it really do the work for you? The answer is more complex and exciting than you think. Our latest article is a practical guide that shows how AI is the ultimate language tutor for the core skills of reading, writing, speaking, and listening. But more importantly, it unpacks the new, crucial skill for the modern world: Prompt Engineering. Learn the techniques of being specific, providing context, and setting constraints with side-by-side examples of bad vs. good prompts. It's time to stop seeing AI as a crutch and start using it as a creative partner. https://englishpluspodcast.com/from-grammar-to-prompts-why-ai-makes-your-english-skills-more-valuable-than-ever/ To unlock full access to all our episodes, consider becoming a premium subscriber on Apple Podcasts or Patreon. And don't forget to visit englishpluspodcast.com for even more content, including articles, in-depth studies, and our brand-new audio series and courses now available in our Patreon Shop! #LearnEnglish #AIinEducation #PromptEngineering #LanguageLearning #FutureSkills

In this episode of The ROCC Pod, we dive deep into the world of emotionally intelligent AI with Christine Chubenko of CodeBaby. Jon hosts solo while Lisais away, and together with Christine, we explore how AI is reshaping business efficiency, customer interaction, and our daily digital experience.We begin by learning about CodeBaby, a platform that powers emotionally intelligent avatars capable of handling repetitive customer service tasks on behalf of businesses. These avatars go far beyond the likes of "Clippy" — they can smile, laugh, and emulate human responses, allowing businesses to provide 24/7 assistance that reflects their brand tone and values. Christine emphasizes that users maintain full control over their data and avatar behavior, which can evolve over time as the business grows or shifts.Christine shares examples from retail and healthcare. In stores, avatars answer common customer questions, freeing up human staff to focus on higher-priority tasks. In medical practices, avatars or even holograms can offer patients a safe space to ask questions — particularly beneficial for older patients who may hesitate to speak directly to doctors. ("But they're so busy!")As we discuss the broader AI landscape, Christine explains her career roots in computer science and AI, dating back to the 1990s. While the foundation of AI has remained rooted in pattern recognition and statistical models like k-nearest neighbor, the scale and sophistication of modern AI have exploded. She debunks the myth that AI is sentient — emphasizing that despite the human-like responses, these systems are still just machines built by humans with clear limitations and no true consciousness.We explore how AI is already part of our everyday lives through Siri, Alexa, social media algorithms, smart appliances, and personalized streaming suggestions. Christine argues that AI's role is to reduce tedious tasks — not replace humans entirely. Jobs that require emotional nuance, tactile presence, or creativity (like nurses or preschool teachers) remain well out of AI's reach. Meanwhile, automation can fill gaps where businesses struggle to hire, like in food service or basic admin roles.Christine also breaks down what makes AI emotionally intelligent: prompt engineering. It's not just about asking a question; it's about asking it the right way, setting the tone, and defining the persona you want the AI to emulate. For instance, telling ChatGPT to answer as a cardiovascular surgeon or in a humorous tone drastically alters the output.To close, Christine encourages listeners who are curious about AI to simply sign up for a tool like ChatGPT and ask, “Where do I start?” That simple first step leads to powerful learning. She reminds us that while AI may seem intimidating, it's just another tool — and it's one we can all learn to wield effectively.More:Email Christine: cchubenko@codebaby.comCodeBaby Website: https://www.codebaby.com/ Learn more about the Royal Oak Chamber of Commerce: https://www.royaloakchamber.com/Connect with our hosts:Jon Gay from JAG in Detroit Podcasts - http://www.jagindetroit.com/Lisa Bibbee from Century 21 Northland - http://soldbylisab.com/

- Endorsement of Pete Chambers for Texas Governor (0:10) - Chambers' Commitment to Decentralized Medicine and Humanitarian Efforts (1:41) - Importance of Prompt Engineering in AI (4:26) - AI's Role in Software Development and Prompt Engineering Techniques (5:53) - Prediction of a Major Robotics Hoax (19:27) - Comparison of Mainstream Deodorants and Health Ranger Store Deodorant (28:54) - Health Benefits of Purple Okra and Anthocyanins (40:02) - RFK Jr's Investigation into Psychiatric Medications and School Shootings (42:53) - Texas' Role in the Future of the United States (51:09) - Nutritional Tips for Enjoying Barbecue (55:42) - Energy Consumption and Water Usage by Data Centers (1:08:35) - Impact of Data Centers on Texas' Power Grid (1:19:53) - Economic and Environmental Concerns (1:20:58) - Water and Land Use Conflicts (1:23:37) - Governor's Role and Citizen-Led Governance (1:26:36) - Border Security and Governor Abbott's Performance (1:27:34) - Health and Human Services Expenditures (1:34:46) - Education and Food Security Initiatives (1:49:40) - Challenges of Political Corruption and Centralization (1:51:09) - Vision for Texas' Future (2:08:42) For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

Artificial Intelligence is no longer just a buzzword — it's already finding its way into Quality Assurance (QA) and Regulatory Affairs (RA) in the medical device industry. But what does this mean for compliance professionals? Is AI a powerful tool to accelerate regulatory processes, or a risky shortcut that could jeopardize compliance? In this new episode of the Medical Device Made Easy Podcast, Monir El Azzouzi sits down with RJ Kedziora (Estenda) to explore the opportunities and risks of using AI in regulatory compliance. Together, they discuss: Why more QA/RA teams are experimenting with AI tools like ChatGPT, Gemini, Claude, and Grok How to integrate AI into different product design and regulatory phases The role of Prompt Engineering and why it matters in compliance Practical tips for creating effective AI prompts The warnings and risks you should keep in mind when relying on AI How agencies like the FDA are beginning to explore AI for dossier reviews

Today, we're joined by a familiar voice and a musically inclined CPG thought leader: Chris Perry of firstmovr. He's spent the last several months educating brands on how to prepare for a new age of product discovery and conversion paths with the dawn of AI-enabled search.  We're thrilled to have him back to share key insights and practical takeaways from his recent trainings. Tune in to find out more! KEY TAKEAWAYS In this episode, Julie, Jordan, and Chris discuss: The Changing Digital Shelf: How the digital shelf continues to evolve rapidly and the growing importance of frictionless and personalized shopping experiences driven by AI. Personal Experiences with AI Search: How tools like Rufus and ChatGPT are influencing their own shopping behaviors. Choice Paralysis and AI Solutions: Choice overload for consumers and how agentic AI tools can curate and simplify decision-making, much like a “Costco experience” for endless online assortments. Training and Transition for Brands: Chris details the challenge of bringing legacy organizations up to speed, highlighting the need to expand skillsets from basic e-commerce “math” to effectively leveraging AI “calculator” tools. Brand Case Studies and Shopper Journeys: Through real shopping scenarios (e.g., searching for whitening toothpaste for sensitive teeth), Chris explains how AI-driven search results can differ from traditional ones, urging brands to rethink content strategy and optimization. Prompting and Shopper-Centric Content: Tips for brands to analyze and adapt to AI tools' pre-filled questions and dynamic prompts, which often reveal emerging shopper concerns and influence purchase considerations. Practical Optimization Insights: Actionable steps brands can take, such as focusing on clear, shopper-centric product content and continually testing how products show up in AI-influenced search environments. Looking Ahead: The future convergence of search and AI, predicting that the lines between “search bar” and “AI assistant” will soon blur, fundamentally changing shopper expectations. Tips for Brands: Brands are encouraged to treat the digital shelf as an ongoing process, not a project, and to use practical experimentation, shopper empathy, and iterative optimization to stay ahead.   MENTIONED IN THIS EPISODE Connect with Chris Perry Learn more about firstmovr Connect with our host, Julie Spear Connect with our host, Jordan Ripley Learn more about Acadia

Struggling with technical debt and code quality? Learn how a technical coach can help your team level up.In this episode, Emily Bache, a Samman technical coach, shares her proven method for building better engineering teams through structured learning and collaborative coding. We explore ensemble programming, learning hours, and why AI makes fundamental engineering practices more important than ever.Key topics discussed:The role of a Technical Coach and the Samman Method explainedHow AI amplifies good engineering practices instead of replacing themHow to use ensemble programming to achieve single-piece flowRunning effective ensemble sessions and avoiding common failure modesWhy learning is part of the work, not only a side activityWhy pull requests should not be the primary tool for mentoring junior developersThe dangerous trend of “vibe coding” with AI toolsTimestamps:(00:00) Trailer & Intro(02:22) Career Turning Points(03:23) Being Part of Modern Engineering YouTube Channel(04:27) The Role of a Technical Coach(05:42) The Impact of AI on Technical Coaching(08:20) Sofware Engineering is a Learning Process(09:55) Optimizing Learning With Samman Method(11:40) The Samman Method: Ensemble (Mob Programming)(14:59) The Main Benefit of Ensemble: Single Piece Flow(17:26) How to Do Ensemble and Avoid Common Failure Modes(20:27) The Types of Coding to Ensemble On(22:12) The Importance of Trust, Communication, and Kindness(23:52) Common Things Development Teams Are Struggling With(25:37) Prompt Engineering(27:16) The Samman Method: Learning Hours(29:08) Learning is Part of the Work(31:32) The Practice of Learning as a Team(34:39) The Constraint When Learning from Pull Requests(36:30) Putting Aside Time for Learning Hours(39:14) Becoming a Technical Coach(41:23) How to Measure the Effectiveness of Technical Coaching(43:52) Danger of AI Assisted Coding(46:59) The (Still) Important Skills in the AI Era(49:56) Why We Should Not Refactor Through AI(52:41) The Samman Method & Technical Coaching Resources(53:29) 3 Tech Lead Wisdom(54:56) Finding Mentors for Career Progression_____Emily Bache's BioEmily Bache is an independent consultant, YouTuber and Technical Coach. She works with developers, training and coaching effective agile practices like Refactoring and Test-Driven Development.Emily has worked with software development for 25 years, written two books and teaches courses on platforms including Pluralsight and O'Reilly. A frequent conference speaker, Emily has been invited to keynote at prestigious developer events including EuroPython, Craft and ACCU. Emily founded the Samman Technical Coaching Society in order to promote technical excellence and support coaches everywhere.Follow Emily:LinkedIn – linkedin.com/in/emilybacheX – x.com/emilybacheMastodon – sw-development-is.social/web/@emilybacheGitHub – github.com/emilybacheWebsite – emilybache.comSamman Coaching – sammancoaching.orgYouTube – youtube.com/@EmilyBache-tech-coachModern Software Engineering – youtube.com/@ModernSoftwareEngineeringYTLike this episode?Show notes & transcript: techleadjournal.dev/episodes/230.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

- Announcement of Enoch AI Engine Upgrade (0:03) - Accessing Enoch AI Engine (2:29) - Prompt Engineering and Use Cases (4:59) - Challenges and Successes in Training Enoch (9:25) - Applications and Benefits of Enoch AI Engine (12:21) - Demonstration and Comparison with Other AI Engines (18:10) - Support and Future Plans (1:06:27) - Enoch's Impact on Independent Media (1:17:07) - Conclusion and Call to Action (1:17:27) For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

How Pennant Moldings Uses AI and Traditional B2B MarketingB2B Marketing Excellence & AI Podcast with Donna PetersonIndustrial marketing isn't like selling shoes or software. It takes time, trust, and a strong understanding of how real relationships drive long-term results.In this episode, I sit down with Brian Contini, VP of Sales and Marketing at Pennant Moldings, to hear what's actually working for their team right now. We talk about how they're combining traditional methods—like trade shows and in-person visits—with smart use of AI to support research, improve outreach, and build stronger customer connections.Whether you're in metals, plastics, or any industrial space, this episode is full of practical takeaways you can use right away.Top 5 Topics We Cover:Why traditional marketing still works—and when to use itHow Pennant is using AI to streamline sales researchWhat's working in email marketing todayThe importance of knowing your audience in technical industriesHow to maintain trust while integrating new tools like AIWhat You Can Do Today:Revisit your email outreach—are you focusing on the recipient's challenge first?Identify one traditional tactic (like trade shows or phone calls) that deserves renewed attention.Choose one AI tool that could save you time with research or outreach—start testing it in a small way.Talk to your sales team: Where do they feel AI supports their efforts—and where does it get in the way?Let's keep the conversation going:How are you helping your industrial brand stand out and build stronger relationships?Leave a comment, send me a message, or reach out at dpeterson@worldinnovators.com. I'd love to hear what's working for you.If this episode helped you in any way, consider leaving a quick review. It helps us continue sharing real strategies that support industrial brands doing meaningful work.

In this technical deep dive, Generation AI explores the evolution from prompt engineering to context engineering - a critical shift in how we build intelligent AI systems. Hosts Ardis Kadiu and Petar Djordjevic from Element451 break down why static prompts are no longer enough and how dynamic context management is the key to creating truly smart agents. They explain the technical architecture behind retrieval augmented generation (RAG), discuss the challenges of building multi-agent systems that coordinate effectively, and reveal how Element451's new bulk jobs feature represents the cutting edge of context engineering in higher education. The episode concludes with an analysis of Mark Zuckerberg's vision for "personal superintelligence" - always-on AI assistants that remember everything about you. This matters because institutions need to understand that the success of AI agents depends entirely on having rich, well-structured data and proper context management - not just smart models.Introduction and the Shift from Prompt to Context Engineering (00:00:00)Welcome back Petar Djordjevic as co-host for the third timeThe transformation from static prompt libraries to dynamic context systemsWhy GPT-4's evolution to reasoning models changed everythingHow agents use tools to gather real-time information instead of relying on frozen knowledgeDefining Context Engineering vs Prompt Engineering (00:04:11)Context engineering as managing dynamic information for AI tasksThe evolution from one-shot prompt problems to complex agent workflowsHow automation requirements drove the need for context engineeringWhy "it's their first day on the job every day" for AI modelsDeep Dive into RAG (Retrieval Augmented Generation) (00:17:17)The complete RAG pipeline: from user query to accurate responseBreaking down queries into multiple intents for better resultsVector databases and metadata attachment for information storageThe importance of combining keyword search with semantic searchAdvanced RAG Techniques and Challenges (00:21:08)Data preparation: parsing PDFs and extracting meaningful chunksWhy semantic search alone isn't enough - the CS101 problemRe-ranking and post-processing to get the most relevant resultsHow to handle citations and build user trust in AI responsesBuilding Complex Agent Systems at Element451 (00:33:08)Element451's new Bulk Jobs feature as a case studyThe research phase: gathering student data, interaction history, and contextWhy data-rich platforms are essential for successful agentsMoving from segment-based personalization to true "segment of one"Context Pruning and Tool Selection (00:41:31)Why you can't just throw all data into the context windowPerformance degradation with large contexts - the needle in haystack problemSelecting the right tools for each task (SMS vs WhatsApp example)How to compress and adapt content for optimal performanceMulti-Agent Coordination and State Management (00:46:48)The challenge of multiple agents working on the same studentContext writing: how agents remember what they did and whyPreventing redundant actions across different departmentsBuilding systems that coordinate like experienced teamsCommon Mistakes in Context Engineering (00:50:17)The danger of being "lazy about context" and assuming AI is smart enoughWhy domain expertise is crucial for building effective agentsThe importance of vertical-specific agents (Cursor, Harvey, Sierra examples)How Element451 leverages its CRM data for education-specific agentsThe Future: Personal Superintelligence (00:53:18)Mark Zuckerberg's vision of always-on, memory-rich personal AIMeta's glasses as the computing platform of the futureAndrej Karpathy's small model with massive context approachChallenges: ambient monitoring, recall/summary, lifelong memory files - - - -Connect With Our Co-Hosts:Ardis Kadiuhttps://www.linkedin.com/in/ardis/https://twitter.com/ardisDr. JC Bonillahttps://www.linkedin.com/in/jcbonilla/https://twitter.com/jbonillxAbout The Enrollify Podcast Network:Generation AI is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too! Enrollify is made possible by Element451 — The AI Workforce Platform for Higher Ed. Learn more at element451.com.

- Discovery of Secret Room in FBI Building (0:11) - Criticism of FBI and Intelligence Agencies (1:24) - Challenges with Burn Bags and Document Destruction (2:48) - Lack of Arrests and Legal Challenges (5:26) - Summary of Document Findings (9:25) - Trump Administration's Legal Strategy (11:54) - Hopes for Mass Arrests (15:08) - Challenges with Power Grid and AI Data Centers (25:17) - Impact of Tariffs on Transformer Supply (46:48) - Future of Energy and Decentralized Solutions (1:09:21) - Introduction of Enoch AI Engine (1:15:24) - Challenges with AI Data and Personal Experiences (1:25:51) - Development and Performance of the AI Engine (1:28:19) - Decentralization and Open-Source AI (1:30:34) - Training Data and AI Capabilities (1:33:59) - Prompt Engineering and AI Applications (1:40:28) - Challenges and Future of AI Development (1:55:27) - Censorship and Regulatory Concerns (1:57:29) - Global AI Competition and Technological Advancements (2:06:23) - Economic and Political Implications of AI (2:18:04) - Geopolitical Shifts and Centralized Power (2:25:24) - Demoralization and Betrayal of American Dream (2:39:28) - Apocalypse Accelerationism and Christian Zionism (2:42:43) - Critique of Religious Institutions and Their Teachings (2:46:44) - Historical Context and Modern Implications (2:49:42) - Cults and Their Influence on Global Events (2:52:32) - The Role of Media and Education in Shaping Perceptions (2:55:27) - The Impact of Religious Supremacy on Global Conflict (3:12:55) - The Role of Individual Actions in Promoting Peace (3:19:24) - The Future of Global Peace and Understanding (3:21:06) For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

This interview was recorded for the GOTO Book Club.http://gotopia.tech/bookclubRead the full transcription of the interview hereJames Phoenix - Co-Author of "Prompt Engineering for Generative AI"Mike Taylor - Co-Author of "Prompt Engineering for Generative AI"Phil Winder - Author of "Reinforcement Learning" & CEO of Winder.AIRESOURCESJameshttps://x.com/jamesaphoenix12https://www.linkedin.com/in/jamesphoenixhttps://understandingdata.comMikehttp://saxifrage.xyzhttps://twitter.com/hammer_mthttps://www.linkedin.com/in/mjt145Philhttps://twitter.com/DrPhilWinderhttps://linkedin.com/in/drphilwinderhttps://winder.aiLinkshttps://brightpool.devhttps://karpathy.aihttps://help.openai.com/en/articles/6654000https://gemini.google.comhttps://dreambooth.github.iohttps://github.com/microsoft/LoRAhttps://claude.aihttps://www.langchain.com/langgraphDESCRIPTIONLarge language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation.With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems.* Book description: © O'ReillyRECOMMENDED BOOKSJames Phoenix & Mike Taylor • Prompt Engineering for Generative AIPhil WiBlueskyTwitterInstagramLinkedInFacebookCHANNEL MEMBERSHIP BONUSJoin this channel to get early access to videos & other perks:https://www.youtube.com/channel/UCs_tLP3AiwYKwdUHpltJPuA/joinLooking for a unique learning experience?Attend the next GOTO conference near you! Get your ticket: gotopia.techSUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

Вступайте в лучшее русскоязычное ИИ сообщество от @itbeard : https://itbeard.com/evocode Нас можно найти: 1. Telegram: https://t.me/proConf 2. Youtube: https://www.youtube.com/c/proconf 3. SoundCloud: https://soundcloud.com/proconf 4. Itunes: https://podcasts.apple.com/by/podcast/podcast-proconf/id1455023466 5. Spotify: https://open.spotify.com/show/77BSWwGavfnMKGIg5TDnLz

Want better outputs from AI? Get our free Prompt Engineering guide: https://clickhubspot.com/cnj Episode 69: Why do so many AI-generated websites end up looking generic—and how can you use “vibe coding” to stand out with truly designer-level style? Nathan Lands (https://x.com/NathanLands) sits down with design legend Meng To (https://x.com/MengTo), founder of Design+Code and creator of innovative tools like Aura, to deliver a practical masterclass on prompting AI for web design that's not just beautiful, but memorable and conversion-friendly. In this episode, Meng shares his approach to breaking free from generic, templated looks by leveraging a precise design vocabulary, including layouts, color theory, typography, animations, and unique assets. Learn how to use free resources and smart prompting techniques to turn basic AI outputs into custom-crafted sites that reflect your taste and business needs. If you care about making your site stand out in the age of AI tools like Lovable, V0, and Aura, don't miss this hands-on walkthrough! Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) Improving AI Design with Aura (05:32) Single-File HTML/CSS Design Simplicity (07:27) Defining "Beautiful Site" Concepts (10:19) Modern Skeuomorphism and Typography Trends (15:22) Master AI Prompt Engineering (16:16) Website Design: The Hero Component (20:13) AI-Generated Dynamic Color Schemes (22:51) Personalized AI: Create Your Solution — Mentions: Meng To: https://www.linkedin.com/in/mengto/ Design+Code: https://designcode.io/ Aura: https://aura.design/ Spline: https://spline.design/ Unicorn Studio: https://unicorn.studio/ Lovable: https://lovable.so/ V0: https://v0.dev/ Cursor: https://www.cursor.so/ Get the guide to build your own Custom GPT: https://clickhubspot.com/tnw — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by Hubspot Media // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

In this episode of Hands-On IT, host Landon Miles is joined by Automox Security Engineer Henry Smith for a deep dive into prompt engineering and how it's transforming the way IT and security teams work with AI.From crafting high-quality prompts to auditing and hardening code using large language models like Claude and ChatGPT, Landon and Henry share real-world insights, practical strategies, and lessons learned from implementing AI in secure development workflows.They also explore:Why context is king when prompting AISecurity implications of AI-generated codeTips for optimizing token usage and context windowsHow Automox engineers are experimenting safely with AIWhether you're a developer, security professional, or IT leader, this episode offers actionable advice and forward-thinking perspectives on integrating AI into your workflow.

$2 Million Amazon Seller REVEALS How to Use AI to Automate Your Entire BusinessBook A FREE Strategy Call with Carter from VA Fastlane : https://bit.ly/4jeDLC4 In episode 115 of The Side Hustle Experiment Podcast  John (https://www.instagram.com/sidehustleexperiment/) and Drew  (https://www.instagram.com/realdrewd/) talk with Nick Spisak (https://www.instagram.com/nickspisak_/) He's a former software engineer turned 7-figure Amazon FBA seller — who shares exactly how he's using AI tools like ChatGPT, Claude, and Gemini to automate nearly every part of his Amazon business.Whether you're new to Amazon FBA, tired of managing VAs, or just curious about how to leverage AI to scale, this is a masterclass in the future of e-commerce automation.✅ What You'll Learn in This Episode: ✔️ How Nick built a $2.1M Amazon business while working full-time ✔️ The exact AI tools and workflows he uses daily ✔️ How to replace VAs with AI agents (and when you shouldn't) ✔️ Why prompt engineering is the #1 skill Amazon sellers need ✔️ How to build a lean, hyper-efficient FBA operation with AINick breaks down his systems, shares real-world examples, and gives you the blueprint to automate your Amazon business — no coding experience required.

Christoph Magnussen ist Unternehmer, KI-Experte und Verfechter einer modernen Arbeitskultur. In dieser Folge erklärt er, warum Neugier wichtiger ist als Kontrolle – und wie KI den Arbeitsalltag verändern kann, wenn man ihre Grenzen kennt. In dieser Episode erfährst du: - Warum die „996-Kultur“ aus Asien kein Modell für die Zukunft ist – und was stattdessen zählt: Effizienz, Kreativität und Vertrauen. - Wie KI-Tools wie Sprachassistenten und Textgeneratoren sinnvoll im Arbeitsalltag eingesetzt werden – von Workshopvorbereitung bis Onboarding. - Welche Chancen und Grenzen KI wirklich hat – und warum „Prompt Engineering“ zur Schlüsselkompetenz wird. - Wieso eine Vier-Tage-Woche funktionieren kann – und welche Herausforderungen es dabei noch gibt. - Wie Christoph den steigenden Energiebedarf von KI-Technologien einschätzt – und welche Verantwortung damit einhergeht. Christoph Burseg auf LinkedIn: [https://www.linkedin.com/in/christophburseg](https://www.linkedin.com/in/christophburseg) Kontaktiere uns über Instagram: [https://www.instagram.com/vodafonebusinessde/](https://www.instagram.com/vodafonebusinessde/)

In this episode of B2B Marketing Excellence, Donna Peterson breaks down the intimidating term “prompt engineering” and shows how it's simply a smarter, more consistent way to work—no tech degree required.Drawing from her experience with generative AI and recent insights from the Vanderbilt Prompt Engineering course, Donna shares practical ways to use prompts for repetitive marketing tasks like campaign planning and list recommendations. You'll hear how creating simple, reusable prompts not only saves time but also ensures your whole team is aligned—producing clear, professional results.You'll also learn:Why prompting is more about conversation than coding.How a well-written prompt becomes a shortcut you can use again and again.The difference between prompts and templates—and how to use both for better outcomes.At World Innovators, we focus on providing tools and strategies that make your work easier, your messaging clearer, and your outcomes more consistent. This episode offers practical examples to help you build confidence using AI in a way that's simple and effective.For a step-by-step walkthrough, refer to "Prompt Engineering Examples for Business Teams: 3 ChatGPT Prompt Templates to Boost Productivity" video on YouTube- https://youtu.be/FAlcjTx_xUo?si=uQv6-naLnQGIkn4S.Episode Timestamps:00:00 – Welcome & why the term “prompt engineering” can feel overwhelming00:38 – What prompting really is (and what it's not)01:33 – The early struggles: over-explaining and second-guessing03:02 – Aha moment from the Vanderbilt course04:47 – Using prompts to simplify and speed up repetitive tasks06:14 – Real-world example: Scheduling campaigns with one simple prompt10:22 – Understanding the difference between prompts and templates12:59 – Encouragement to just start talking to your AI assistantIf you found this episode helpful, subscribe to the World Innovators YouTube Channel for more practical ideas on B2B marketing and using AI tools effectively.Leave a review to help us spread the word about quality marketing that puts people first.If you need help building your prompt library or training your team, reach out directly to Donna at dpeterson@worldinnovators.com.

Is AI the Fourth Pillar of Infrastructure?Infrastructure doesn't go away — it layers. And today, AI is emerging as a new foundational layer alongside compute, storage, and networking.Erik Torenberg interviews a16z's Martin Casado, Jennifer Li, and Matt Bornstein breaking down how infrastructure is evolving in the age of AI — from models and agents to developer tools and shifting user behavior.We dive into what infra actually means today, how it differs from enterprise, and why software itself is being disrupted. Plus, we explore the rise of technical users as buyers, what makes infra companies defensible, and how past waves — from the cloud to COVID to AI — are reshaping how we build and invest. Timestamps: (00:00) Introduction (01:49) Defining Infrastructure in the AI Era(03:15) The Fourth Pillar: AI's Role in Infrastructure(06:01) Historical Context and Evolution of Infrastructure(08:20) The Impact of AI on Software Development(10:18) Investment Strategies and Market Dynamics(17:02) Developer Tools and AI Integration(20:57) Defensibility in the AI Landscape(22:16) Founders' Intuition and Industry Progress(22:26) Defensibility in AI Infrastructure(24:00) Expansion and Contraction Phases in the Industry(24:35) The Role of Layers in Market Consolidation(27:43) The Future of AI Models and Specialization(29:27) The Decade of AI Agents(29:54) Context Engineering and New Infrastructure(34:23) The Evolution of Software Development(42:13) Horizontal vs. Vertical Integration in AI(43:54) Conclusion and Final Thoughts Resources: Find Martin on X: https://x.com/martin_casadoFind Jennifer on X: https://x.com/JenniferHliFind Matt on X: https://x.com/BornsteinMatt Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

In dieser Folge des Zeit- und Selbstmanagement-Podcasts mit Thomas Mangold dreht sich alles um die Frage, wie wir im Zeitalter der Künstlichen Intelligenz (KI) beruflich relevant bleiben können. Basierend auf einer spannenden Frage aus der Selbstmanagement Rocks Masterclass spricht Thomas darüber, welche Fähigkeiten und Kompetenzen im KI-Zeitalter besonders gefragt sind – von kritischem und strategischem Denken über Empathie und Kreativität bis hin zu praktischen Skills wie Prompt Engineering und No-Code-Tools. Er zeigt, wie wichtig es ist, nicht nur auf technische Neuerungen zu reagieren, sondern auch die Angst vor Veränderungen in produktive Energie umzuwandeln. Dazu gibt es wertvolle Tipps, wie du mit negativen Gedanken rund um KI und Jobverlust umgehen kannst und wie du deinen persönlichen Werkzeugkoffer für die Zukunft zusammenstellst. Viel Spaß beim Zuhören – und lass dich inspirieren, deine Fähigkeiten für die Arbeitswelt von morgen weiterzuentwickeln! **Hier geht es zum Werbepartner dieser Podcast-Folge**: https://selbst-management.biz/podcast-partner Links: - Kostenloser Mangold-Academy Bonus-Bereich: https://my.mangold.academy/anmeldung-vip-bereich-2/ - Goodie des Monats: https://my.mangold.academy/courses/einstieg-in-das-selbstmanagement/lessons/goodie-des-monats/ - SelbstmanagementRocks Masterclass: https://selbst-management.biz/selbstmanagement-rocks-masterclass/ - Mein LinkedIn Profil: https://www.linkedin.com/in/thomasmangold/

Jacob Visovatti and Conner Goodrum of Deepgram speak with host Kanchan Shringi about testing ML models for enterprise use and why it's critical for product reliability and quality. They discuss the challenges of testing machine learning models in enterprise environments, especially in foundational AI contexts. The conversation particularly highlights the differences in testing needs between companies that build ML models from scratch and those that rely on existing infrastructure. Jacob and Conner describe how testing is more complex in ML systems due to unstructured inputs, varied data distribution, and real-time use cases, in contrast to traditional software testing frameworks such as the testing pyramid. To address the difficulty of ensuring LLM quality, they advocate for iterative feedback loops, robust observability, and production-like testing environments. Both guests underscore that testing and quality assurance are interdisciplinary efforts that involve data scientists, ML engineers, software engineers, and product managers. Finally, this episode touches on the importance of synthetic data generation, fuzz testing, automated retraining pipelines, and responsible model deployment—especially when handling sensitive or regulated enterprise data. Brought to you by IEEE Computer Society and IEEE Software magazine.

Kieran Flanagan is the CMO at HubSpot, where he's led the transformation of their growth strategy from SEO-led to multi-channel and AI-powered. Formerly SVP of Marketing, he helped scale HubSpot's user base to millions and revenue past $2B. Before HubSpot, he drove breakout growth at Marketo and Salesforce. Kieran is one of the most respected voices in SaaS marketing and a pioneer in growth-driven content strategy. Agenda: 00:03 – The Death of Growth Teams? Kieran's Wild Prediction 06:44 – AI Innovation Pods: The New Org Structure for Startups 10:18 – Email Personalization That Tripled Conversions 13:21 – From Software Budget to Labor Budget: The Shift is Happening 16:35 – The Big Lie: Why Autonomous Agents Still Suck 19:24 – The Secret Sauce Behind HubSpot's Email AI Stack 21:44 – Segment-Based Marketing Is Dead. Enter Micro Audiences. 24:15 – Content Collapse: Why Google Organic Is Getting Torched 30:52 – The Future of AI SEO: 1 Product, 100 Pages, Infinite Prompts 33:16 – Memory = Moat: Why ChatGPT Is Becoming Unbeatable 35:46 – Prompt Engineering is the New Coding: Here's How to Win 41:03 – The Death of the Middle Manager Marketer 46:17 – OpenAI vs. Anthropic: Kieran's $400M Bet 48:00 – Europe Is Falling Behind: The Harsh Truth on Regulation 52:39 – CMO Playbook 2025: Micro-Audiences, Creator-Led, AI at Scale    

AI expert Nate B. Jones joins Michael Krigsman on CXOTalk episode 883 to discuss prompting strategies and how they impact the performance of large language models (LLMs). Learn how to use ChatGPT to generate better results and understand the importance of AI prompt engineering. Discover effective methods to improve AI productivity using proper prompting techniques.

O Impacto da IA Generativa no Presente e Futuro dos DadosPrepare-se para uma conversa de altíssimo nível sobre como a Inteligência Artificial Generativa está transformando o mundo dos dados, das empresas e das carreiras. Neste episódio, Luan Moreno recebe Eduardo Ordax, Líder de IA Generativa na AWS, e Mateus Oliveira para discutir, sem rodeios, os impactos reais da IA no mercado.O que você vai aprender neste episódio:Como a IA Generativa está mudando a forma como construímos pipelines, produtos e soluções de dados.Os principais desafios que empresas enfrentam ao implementar GenAI — e por que tecnologia não é mais o problema, mas sim pessoas e dados.O papel da Engenharia de Dados no mundo da IA e como ela se conecta com conceitos como LLMOps, Fine-Tuning, Prompt Engineering e Data-Centric AI.Por que o domínio dos fundamentos nunca foi tão importante para quem trabalha (ou quer trabalhar) com dados e IA.Reflexões sobre o futuro das carreiras em dados e IA — será que os engenheiros de dados, cientistas de dados e desenvolvedores serão substituídos ou terão um papel ainda mais relevante?As diferenças entre usar IA para brincar no ChatGPT e levar IA para resolver problemas de negócios no mundo real, em escala e em produção.Este é um papo sobre IA. É uma imersão completa sobre os desafios, as oportunidades e a visão de futuro para quem trabalha com dados, engenharia, machine learning e inteligência artificial. Luan Moreno = https://www.linkedin.com/in/luanmoreno/

Conor Grennan and Jaeden discuss the latest advancements in AI video generation, particularly focusing on Mid Journey's new capabilities. They explore the quality of video outputs, the legal challenges posed by Disney, and the importance of prompt engineering in achieving desired results. The conversation emphasizes the ongoing relevance of human creativity in the age of AI tools, highlighting that while AI can assist in content creation, the vision and taste of human creators remain irreplaceable.AI Applied YouTube Channel: https://www.youtube.com/@AI-Applied-PodcastTry AI Box: ⁠⁠https://AIBox.ai/⁠⁠Conor's AI Course: https://www.ai-mindset.ai/coursesConor's AI Newsletter: https://www.ai-mindset.ai/Jaeden's AI Hustle Community: https://www.skool.com/aihustle/aboutChapters00:00 Introduction to AI and Video Generation01:13 Mid Journey's Video Generation Capabilities04:03 Innovative Video Effects and Techniques06:42 Legal Challenges and Copyright Issues10:50 The Future of Mid Journey and AI Technology11:49 Prompt Engineering and Artistic Vision

Sander Schulhoff is the OG prompt engineer. He created the very first prompt engineering guide on the internet (two months before ChatGPT's release) and recently wrote the most comprehensive study of prompt engineering ever conducted (co-authored with OpenAI, Microsoft, Google, Princeton, and Stanford), analyzing over 1,500 academic papers and covering more than 200 prompting techniques. He also partners with OpenAI to run what was the first and is the largest AI red teaming competition, HackAPrompt, which helps discover the most state-of-the-art prompt injection techniques (i.e. ways to get LLMS to do things it shouldn't). Sander teaches AI red teaming on Maven, advises AI companies on security, and has educated millions of people on the most state-of-the-art prompt engineering techniques.In this episode, you'll learn:1. The 5 most effective prompt engineering techniques2. Why “role prompting” and threatening the AI no longer works—and what to do instead3. The two types of prompt engineering: conversational and product/system prompts4. A primer on prompt injection and AI red teaming—including real jailbreak tactics that are still fooling top models5. Why AI agents and robots will be the next major security threat6. How to get started in AI red teaming and prompt engineering7. Practical defense to put in place for your AI products—Brought to you by:Eppo—Run reliable, impactful experimentsStripe—Helping companies of all sizes grow revenueVanta—Automate compliance. Simplify security—Where to find Sander Schulhoff:• X: https://x.com/sanderschulhoff• LinkedIn: https://www.linkedin.com/in/sander-schulhoff/• Website: https://sanderschulhoff.com/• AI Red Teaming and AI Security Masterclass on Maven: https://bit.ly/44lLSbC• Free Lightning Lesson “How to Secure Your AI System” on 6/24: https://bit.ly/4ld9vZL—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Sander Schulhoff(04:29) The importance of prompt engineering(06:30) Real-world applications and examples(10:54) Basic prompt engineering techniques(23:46) Advanced prompt engineering techniques(29:00) The role of context and additional information(39:24) Ensembling techniques and thought generation(49:48) Conversational techniques for better results(50:46) Introduction to prompt injection(52:27) AI red teaming and competitions(54:23) The growing importance of AI security(01:02:45) Techniques to bypass AI safeguards(01:05:21) Challenges in AI security and future outlook(01:18:33) Misalignment and AI's potential risks(01:25:03) Final thoughts and lightning round—Referenced:• Reid Hoffman's tweet about using AI agents: https://x.com/reidhoffman/status/1930416063616884822• AI Engineer World's Fair: https://www.ai.engineer/• What Is Artificial Social Intelligence?: https://learnprompting.org/blog/asi• Devin: https://devin.ai/• Cursor: https://www.cursor.com/• Inside Devin: The world's first autonomous AI engineer that's set to write 50% of its company's code by end of year | Scott Wu (CEO and co-founder of Cognition): https://www.lennysnewsletter.com/p/inside-devin-scott-wu• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Granola: https://www.granola.ai/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder & CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Technique #3: Examples in Prompts: From Zero-Shot to Few-Shot: https://learnprompting.org/docs/basics/few_shot?srsltid=AfmBOor2owyGXtzJZ8n0fJVCctM7UPZgZmH-mBuxRW4t9-kkaMd3LJVv• The Prompt Report: Insights from the Most Comprehensive Study of Prompting Ever Done: https://learnprompting.org/blog/the_prompt_report?srsltid=AfmBOoo7CRNNCtavzhyLbCMxc0LDmkSUakJ4P8XBaITbE6GXL1i2SvA0• State-of-the-Art Prompting for AI Agents | Y Combinator: https://www.youtube.com/watch?v=DL82mGde6wo• Use XML tags to structure your prompts: https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/use-xml-tags• Role Prompting: https://learnprompting.org/docs/basics/roles?srsltid=AfmBOor2jcxJQvWBZyFa030Qt0fIIov3hSiWvI9VFyjO-Qp478EPJIU7• Is Role Prompting Effective?: https://learnprompting.org/blog/role_prompting?srsltid=AfmBOooiiyLD-0CsCYZ4m3SDhYOmtTyaTzeDo0FvK_i1x1gLM8MJS-Sn• Introduction to Decomposition Prompting Techniques: https://learnprompting.org/docs/advanced/decomposition/introduction?srsltid=AfmBOoojJmTQgBlmSlGYQ8kl-JPpVUlLKkL4YcFGS5u54JyeumUwlcBI• LLM Self-Evaluation: https://learnprompting.org/docs/reliability/lm_self_eval• Philip Resnik on X: https://x.com/psresnik• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Introduction to Ensembling Prompting: https://learnprompting.org/docs/advanced/ensembling/introduction?srsltid=AfmBOooGSyqsrjnEbXSYoKpG0ZlpT278NHQA6Fd8gMvNTJlWu7-qEYzh• Random forest: https://en.wikipedia.org/wiki/Random_forest• Chain-of-Thought Prompting: https://learnprompting.org/docs/intermediate/chain_of_thought?srsltid=AfmBOoqwE7SXlluy2sx_QY_VOKduyBplWtIWKEJaD6FkJW3TqeKPSJfx• Prompt Injecting: https://learnprompting.org/docs/prompt_hacking/injection?srsltid=AfmBOoqGgqbfXStrD6vlw5jy8HhEaESgGo2e57jyWL8lkZKktt_P6Zvn• Announcing HackAPrompt 2.0: The World's Largest AI Red-Teaming Hackathon: https://learnprompting.org/blog/announce-hackaprompt-2?srsltid=AfmBOopXKsHxy4aUtsvPCUtEu7x74NCAEnlTIdNzo7nfMDVwZ9ilTlkp• Infant with rare, incurable disease is first to successfully receive personalized gene therapy treatment: https://www.nih.gov/news-events/news-releases/infant-rare-incurable-disease-first-successfully-receive-personalized-gene-therapy-treatment• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan• Copilot: https://copilot.microsoft.com/chats/rcxhzvKgZvz8ajUrKdBtX• GitHub Copilot: https://github.com/features/copilot• Defensive Measures: https://learnprompting.org/docs/prompt_hacking/defensive_measures/introduction• Sam Altman on X: https://x.com/sama• Three Laws of Robotics: https://en.wikipedia.org/wiki/Three_Laws_of_Robotics• Anthropic's new AI model turns to blackmail when engineers try to take it offline: https://techcrunch.com/2025/05/22/anthropics-new-ai-model-turns-to-blackmail-when-engineers-try-to-take-it-offline/• Palisade Research: https://palisaderesearch.org/• When AI Thinks It Will Lose, It Sometimes Cheats, Study Finds: https://time.com/7259395/ai-chess-cheating-palisade-research/• A.I. Chatbots Defeated Doctors at Diagnosing Illness: https://www.nytimes.com/2024/11/17/health/chatgpt-ai-doctors-diagnosis.html• 1883 on Paramount+: https://www.paramountplus.com/shows/1883/• Black Mirror on Netflix: https://www.netflix.com/title/70264888• Daylight Computer: https://daylightcomputer.com/• Theodore Roosevelt's quote: https://www.goodreads.com/quotes/622252-i-wish-to-preach-not-the-doctrine-of-ignoble-ease• HackAPrompt 2.0: https://www.hackaprompt.com/—Recommended books:• Ender's Game: https://www.amazon.com/Enders-Ender-Quintet-Orson-Scott/dp/0812550706• The River of Doubt: Theodore Roosevelt's Darkest Journey: https://www.amazon.com/River-Doubt-Theodore-Roosevelts-Darkest/dp/0767913736—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lennysnewsletter.com/subscribe

Logan Kilpatrick from Google DeepMind talks about the latest developments in the Gemini 2.5 model family, including Gemini 2.5 Pro, Flash, and the newly introduced Flashlight. Logan also offers insight into AI development workflows, model performance, and the future of proactive AI assistants. Links Website: https://logank.ai LinkedIn: https://www.linkedin.com/in/logankilpatrick X: https://x.com/officiallogank YouTube: https://www.youtube.com/@LoganKilpatrickYT Google AI Studio: https://aistudio.google.com Resources Gemini 2.5 Pro Preview: even better coding performance (https://developers.googleblog.com/en/gemini-2-5-pro-io-improved-coding-performance) Building with AI: highlights for developers at Google I/O (https://blog.google/technology/developers/google-ai-developer-updates-io-2025) We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Em, at emily.kochanek@logrocket.com (mailto:emily.kochanek@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Special Guest: Logan Kilpatrick.

Tauche ein in die Welt des Prompt Engineerings mit Joel Kaczmarek und Ruppert Bodmeier! In dieser Episode von digital kompakt geht es um die Kunst, KI-Modelle so zu steuern, dass sie genau das liefern, was du brauchst. Ruppert, ein Experte für Innovationsentwicklung bei Disrooptive, teilt seine Erfahrungen und Herausforderungen auf dem Weg zur perfekten KI-Nutzung. Erfahre, wie du durch gezieltes Prompt Engineering Wettbewerbsvorteile schaffen kannst und warum der Kontext dabei entscheidend ist. Lass dich inspirieren und entdecke, wie du die Zukunft der KI für dich nutzen kannst! Du erfährst... …wie Ruppert Bodmeier die Kunst des Prompt Engineering meistert und einzigartige Lösungen schafft …warum Beharrlichkeit und Resilienz im Umgang mit KI entscheidend sind …wie du durch präzise Kontextdefinitionen bessere KI-Ergebnisse erzielst …welche Rolle APIs spielen, um Wettbewerbsvorteile mit KI zu sichern …wie du mit modularen Befehlen und Ketten einzigartige Projekte realisierst __________________________ ||||| PERSONEN |||||

Mark Ericksen, creator of the Elixir LangChain framework, joins the Elixir Wizards to talk about LLM integration in Elixir apps. He explains how LangChain abstracts away the quirks of different AI providers (OpenAI, Anthropic's Claude, Google's Gemini) so you can work with any LLM in one more consistent API. We dig into core features like conversation chaining, tool execution, automatic retries, and production-grade fallback strategies. Mark shares his experiences maintaining LangChain in a fast-moving AI world: how it shields developers from API drift, manages token budgets, and handles rate limits and outages. He also reveals testing tactics for non-deterministic AI outputs, configuration tips for custom authentication, and the highlights of the new v0.4 release, including “content parts” support for thinking-style models. Key topics discussed in this episode: • Abstracting LLM APIs behind a unified Elixir interface • Building and managing conversation chains across multiple models • Exposing application functionality to LLMs through tool integrations • Automatic retries and fallback chains for production resilience • Supporting a variety of LLM providers • Tracking and optimizing token usage for cost control • Configuring API keys, authentication, and provider-specific settings • Handling rate limits and service outages with degradation • Processing multimodal inputs (text, images) in Langchain workflows • Extracting structured data from unstructured LLM responses • Leveraging “content parts” in v0.4 for advanced thinking-model support • Debugging LLM interactions using verbose logging and telemetry • Kickstarting experiments in LiveBook notebooks and demos • Comparing Elixir LangChain to the original Python implementation • Crafting human-in-the-loop workflows for interactive AI features • Integrating Langchain with the Ash framework for chat-driven interfaces • Contributing to open-source LLM adapters and staying ahead of API changes • Building fallback chains (e.g., OpenAI → Azure) for seamless continuity • Embedding business logic decisions directly into AI-powered tools • Summarization techniques for token efficiency in ongoing conversations • Batch processing tactics to leverage lower-cost API rate tiers • Real-world lessons on maintaining uptime amid LLM service disruptions Links mentioned: https://rubyonrails.org/ https://fly.io/ https://zionnationalpark.com/ https://podcast.thinkingelixir.com/ https://github.com/brainlid/langchain https://openai.com/ https://claude.ai/ https://gemini.google.com/ https://www.anthropic.com/ Vertex AI Studio https://cloud.google.com/generative-ai-studio https://www.perplexity.ai/ https://azure.microsoft.com/ https://hexdocs.pm/ecto/Ecto.html https://oban.pro/ Chris McCord's ElixirConf EU 2025 Talk https://www.youtube.com/watch?v=ojL_VHc4gLk Getting started: https://hexdocs.pm/langchain/gettingstarted.html https://ash-hq.org/ https://hex.pm/packages/langchain https://hexdocs.pm/igniter/readme.html https://www.youtube.com/watch?v=WM9iQlQSFg @brainlid on Twitter and BlueSky Special Guest: Mark Ericksen.

When legal ops meets the AI data revolution, what does it actually look like on the ground? In this episode, Mary O'Carroll sits down with Aaron Bromagem, Head of Legal Operations at Snowflake, to talk about what it means to lead legal ops inside one of the top AI and data companies—and why the role today is barely recognizable from just a few years ago. Aaron shares how his team is navigating breakneck change, massive expectations from leadership, and a vendor landscape that's expanding faster than anyone can track. If you've ever felt like your strategy gets outdated before you even finish writing it down, this one's for you. In this episode: Navigating Uncertainty: Aaron opens up about what it's like to lead in an environment where priorities shift every quarter—and why nimbleness beats planning. GCs as Technologists: The modern general counsel is demanding more data, faster delivery, and deeper insights. Here's what that means for legal ops. The Rise of the Legal Data Model: How Snowflake built a system to turn legal operations data into reliable enterprise intelligence—and why it's powering product features now. Prompt Engineering vs. Agent Workflows: As AI evolves, are we moving from writing prompts to building complex legal workflows powered by agents? The Vendor Maze: Why every legal tech vendor says the same thing—and how Aaron separates the useful from the fluff. A New Profile for Legal Ops: Technical backgrounds, data fluency, and an operations-first mindset—Aaron and Mary discuss how the ideal candidate is changing. If you're in legal ops and feel like you're barely keeping up with the pace of change, you're not alone. But as Aaron shows, with the right mindset and tools, there's huge opportunity in the chaos. Follow Mary on LinkedIn Rate and review on Apple Podcasts

This week I had the pleasure of sitting down with Gary Waldron, an author and speaker who has truly mastered the art of reinvention. With a fascinating career trajectory that spans 44 jobs, including being a school teacher, consultant, and even a topless waiter, Gary shares his profound insights on adapting to change and the necessity of reinvention in today’s volatile world. We had violent agreement on so many topics that it's like Gary is 'a brother from another mother'. We explored topics surrounding his book, "Mastering the Art of Reinvention," and delved into the mindset shifts required to view life’s challenges as growth opportunities. Gary also discusses how to harness AI's power effectively in one’s career for those looking to reinvent themselves, allowing for growth without traditional boundaries. What You'll Learn: The Concept of Reinvention: Understand why reinvention is not solely the end goal but a continual process of adapting to new opportunities. The Role of Genetics in Change: Discover the link between the dopamine receptor gene and novelty-seeking behaviour, explaining why some are more inclined to embrace change. Understanding and Leveraging AI: Learn how AI can propel personal and professional growth by providing democratised access to information and creative exploration. Coping with Life Changes: Gain insights into handling significant life transitions, such as career shifts or personal upheavals, through Gary's personal experiences. Creating a Growth Mindset: Develop a mindset that views challenges as experiments, encouraging proactive action rather than fear-induced paralysis. Key Takeaways: Embrace Change: Accept that change is constant and inevitable; the more you practice adaptation, the easier it becomes. Mindset Matters: How you perceive challenges—as either threats or opportunities—significantly influences your ability to navigate them. Quality Prompts Make a Difference: In the age of AI, the quality of the questions you ask can dictate the usefulness of the solutions you receive. Authenticity and Values: Aligning your actions with your core values such as authenticity can guide you successfully through transformations. Living Fully in the Present: While planning for the future is crucial, excessive focus on it or dwelling in the past can detract from present contentment. Resources: Visit Gary Waldon: For more insights and services, including speaking engagements and consulting, check out Gary's website. Gary's Latest Book: "Mastering the Art of Reinvention" is available in all major bookstores for those interested in exploring these ideas further. Personal Development Guides: For ongoing personal growth tips, subscribe to our podcast for more enriching discussions. Support the Podcast: If you found this episode enlightening, we’d love your support! Consider subscribing, rating, and leaving a review on your favourite podcast platform to help us reach others who might benefit from these conversations. Support and Share: Share this episode with someone navigating change; it might provide the encouragement and direction they need. 00:38 Mastering the Art of Reinvention 01:48 The Dopamine Gene and Novelty Seeking 03:08 Navigating Career Changes 04:13 Diverse Job Experiences 09:07 Personal Growth and Challenges 23:36 The Role of Values in Reinvention 32:03 AI and the Future of Work 34:31 Exploring AI in Book Design 35:15 The Power of Prompt Engineering 37:18 Turning Challenges into Growth Opportunities 38:11 The Six-Step Process of Reinvention 38:33 Embracing Change and Building Resilience 39:36 The Importance of Self-Reflection 44:35 The Role of Action in Overcoming Fear 48:32 Living in the Present Moment 50:38 The Illusion of Happiness 01:01:56 The Power of Laughter and Enjoyment See omnystudio.com/listener for privacy information.

A live SXSW panel on how employee complaints illuminate the path to organizational innovation.Wrong question: How can AI revolutionize productivity in my organization?Right question: What do my employees hate most about their jobs?For the Portland Trail Blazers, a winning game plan for AI implementation didn't begin with a tech-first approach — it began with a talk-first one. “The whole concept was to talk about pain points," explains David Long, VP of Digital Innovation, describing the "Lunch and Launch" sessions where employees could openly share frustrations about their daily work. “People really enjoy talking about what they hate about their jobs,” says Christa Stout, Executive Vice President and Chief Strategy & Innovation Officer, and as they did, they illuminated opportunities for optimization. “By getting this insight across the whole company, it is already opening our eyes [to how] we can potentially transform the business more broadly,” Stout says.In this special live episode of Think Fast, Talk Smart, recorded at SXSW, host Matt Abrahams leads a panel with Long, Stout, and Stanford colleague Jeremy Utley, exploring how "catharsis catalyzes change.” For any team wanting to implement new technology or rethink workflows, these experts reveal how creating space for complaints can catalyze meaningful innovation throughout an organization.Episode Reference Links:Jeremy UtleyDavid LongChrista StoutEp.77 Quick Thinks: AI Has Entered The Chat – A "Conversation" with ChatGPTEp.134 How to Chat with Bots: The Secrets to Getting the Information You Need from AI  Connect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedInChapters:(00:00) - Introduction (04:42) - The Business Behind Basketball (06:13) - Why AI and Why Now? (07:21) - Collaborating with the Team (08:39) - The Lunch & Launch Method (11:11) - Branding AI Initiatives (12:29) - David Detractor & Kelly Kindness (16:00) - Human Connection through AI (16:45) - Auditing for Brand Consistency (18:53) - AI in National Parks (21:36) - Making AI Personal (22:58) - Using AI to Learn AI (27:27) - Encouraging AI in the Workplace (30:21) - Change Management: Iteration Over Perfection (34:07) - Start with Curiosity and Empower Action (37:50) - Communication Ingredients (39:22) - Conclusion   ********This episode is sponsored by LinkedIn. Dare to discover what's next. Explore your job potential at LinkedIn. Become a Faster Smarter Supporter by joining TFTS Premium.  

What if the world's most connected tech investor handed you his mental playbook? Elad Gil, an investor behind Airbnb, Stripe, Coinbase and Anduril, flips conventional wisdom on its head and prioritizes market opportunities over founders. Elad decodes why innovation has clustered geographically throughout history, from Renaissance Florence to Silicon Valley, where today 25% of global tech wealth is created. We get into why he believes AI is dramatically under-hyped and still under-appreciated, why remote work hampers innovation, and the self-inflicted wounds that he's seen kill most startups.   This is a masterclass in pattern recognition from one of tech's most consistent and accurate forecasters, revealing the counterintuitive principles behind identifying world-changing ideas.  Disclaimer: This episode was recorded in January. The pace of AI development is staggering, and some of what we discussed has already evolved. But the mental models Elad shares about strategy, judgment, and high-agency thinking are timeless and will remain relevant for years to come. Approximate timestamps: Subject to variation due to dynamically inserted ads. (2:13) - Investing in Startups (3:25) - Identifying Outlier Teams (6:37) - Tech Clusters (9:55) - Remote Work and Innovation (11:19) - Role of Y Combinator (15:19) - The Waves of AI Companies (20:24) - AI's Problem Solving Capabilities (26:13) - AI's Learning Process (30:41) - Prompt Engineering and AI (32:00) - AI's Role in Future Development (34:37) - AI's Impact on Self-Driving Technology (40:16) - The Role of Open Source in AI (43:23) - The Future of AI in Big Players (44:23) - Regulation and Safety Concerns in AI (49:11) - Common Self-Inflicted Wounds (51:34) - Scaling the CEO and Avoiding Conventional Wisdom (55:21) - Workplace Culture (58:39) - Patterns Among Outlier CEOs (1:15:50) - Remote Work and its Implications (1:18:47) - The Impact of Clusters and Exceptional Individuals (1:25:41) - Investing in Defense Technology (1:27:38) - Business Model Shift in the Defense Industry (1:31:46) - Changes in Warfare SHOPIFY: Upgrade your business and get the same checkout I use. Sign up for your one-dollar-per-month trial period at shopify.com/knowledgeproject NORDVPN: To get the best discount off your NordVPN plan go to nordvpn.com/KNOWLEDGEPROJECT. Our link will also give you 4 extra months on the 2-year plan. There's no risk with Nord's 30 day money-back guarantee! Newsletter - The Brain Food newsletter delivers actionable insights and thoughtful ideas every Sunday. It takes 5 minutes to read, and it's completely free. Learn more and sign up at ⁠fs.blog/newsletter⁠ Upgrade — If you want to hear my thoughts and reflections at the end of the episode, join our membership: ⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/membership⁠⁠⁠ and get your own private feed. Watch on YouTube: ⁠@tkppodcast Learn more about your ad choices. Visit megaphone.fm/adchoices

Prepare to see banking in a new light! Cindi Howson and Macquarie Bank's data trailblazer, Ashwin Sinha (Chief Data Officer), go deep into the AI revolution transforming financial services. Discover how one of Australia's most dynamic financial institutions, Macquarie Bank, is wielding the disruptive force of generative AI, not just for efficiency, but to combat high-stakes threats like fraud. Plus, discover the remarkable evolution of the data analyst from report-generator to AI-powered strategic powerhouse!Key Moments: Drivers of Digital Transformation (04:36): Ashwin outlines the key factors driving a digital transformation and early cloud adoption, emphasizing customer obsession, improving turnaround times, and ensuring technology reliability.  Leveraging Dual Cloud Providers (12:25): Ashwin discusses Macquarie Bank's use of AWS for infrastructure and core applications and Google Cloud (GCP) for its digital and data stack, including AI capabilities.  The Power of Gen AI in Analytics (14:16): Ashwin explores the role of generative AI in enhancing productivity for data analysts, particularly through prompt engineering and tools like ThoughtSpot.  Empowering Analysts Through Evolution (16:56): Ashwin details Macquarie Bank's successful strategy for evolving the data analyst role by proactively introducing self-service analytics, emphasizing upskilling, and enabling analysts to concentrate on higher-impact activitiesCombating Data Risk and Fraud Prevention (26:04): Ashwin discusses the increasing threat of scams and fraud and details Macquarie's two-pronged approach: educating customers and employing AI and machine learning to detect and prevent fraudulent activities.  Importance of Prompt Engineering (32:57): Ashwin stresses the significance of prompt engineering as a general-purpose technology that can drive productivity across various business functions, not just within technical roles.  Key Quotes:"There is always a big backlog in most organizations, which you cannot get done just because you do not have enough capacity. You cannot prioritize them. You cannot execute fast enough. And so, what prompt engineering and GenAI broadly does is take away the low-value tasks that you could just use AI and machine learning to do for you." - Ashwin Sinha"Prompt engineering—even though it has 'engineering' in it— I see that as a general-purpose technology. It's a bit like we've just got access to a super powerful search with a lot more analytical and reasoning capability. That's how I think of the usage of any of the foundational or large language models for, you know, the general population who are not in engineering or technical roles. Whether they're in business roles, sales and distribution, finance, marketing, or any of those functions, the use of prompt engineering just enables the next level of productivity for them. - Ashwin SinhaMentionsPrompt Engineering in the Age of AIAI Agent GovernanceThoughtSpot Spotter: Your AI AnalystScuba Diving and the History of the Liberty Shipwreck in BaliThe Importance of Child Education in IndiaGuest Bio Ashwin Sinha is the Chief Data Officer and Executive Director at Macquarie Bank, where he oversees the strategy and execution of Data and AI. Before joining Macquarie in 2019, Ashwin was a Partner at KPMG, leading the Data business. He has also held various global software engineering, start-up, and consulting roles over the past 22 years, focusing on data and digital transformations. Outside work, Ashwin is passionate about child education and macroeconomics Hear more from Cindi Howson here. Sponsored by ThoughtSpot.