Chris Creates With AI

Episode Title: Diving Prompt First: What is a Prompt?S02 - E12🧠 What REALLY is a Prompt? Why Does it Matter?We use prompts every day when interacting with AI—but what exactly is a prompt, and why does it matter so much? 🤔🔥 In this episode, we break it down! 🔥💡 Chris Tansey’s deep dive into "What is a Prompt?" explains how AI understands and responds to human input. Whether you're just starting with AI or you're a seasoned pro, understanding how to craft better prompts will take your AI interactions to the next level!📖 What You’ll Learn: 🔹 What is a Prompt? The bridge between your intent and AI’s output. 🔹 User Prompts vs. System Prompts: What's the difference, and why does it matter? 🔹 The Power of Specificity: How to get better results by crafting clearer prompts. 🔹 AI as a GPS? A Waiter? 🚗🍽️ Mind-blowing analogies that explain how prompts work. 🔹 The Future of AI Prompts: Could AI anticipate your needs before you even ask?📚 Want to take your prompt engineering skills further? Check out Chris Tansey’s Amazon Kindle book: 🛒 Managing Digital Capital: A Prompt Engineer's Perspective 👉 Get Your Copy HereThis book explores how managing AI agents is just like managing human teams, offering a structured approach to AI workflows and practical strategies for digital optimization.✨ Key Themes: ✔️ How structured AI prompting can maximize efficiency & creativity. ✔️ Why trust & autonomy matter in AI-human collaboration. ✔️ How to design prompts that produce high-value, reliable outputs. ✔️ Ethical AI considerations and adaptability.💡 Want to learn even more? 📌 Visit 👉 ChrisCreatesWithAI.com🎙 What’s the best AI prompt you’ve ever crafted? Drop a comment below!🔔 Like & Subscribe for more deep dives into AI, automation, and next-level prompting!#AI #Automation #PromptEngineering #AIWorkflow #ManagingDigitalCapital #ChrisTansey

Episode Title: Diving Prompt First: Guide to Real-Life Use Cases for Template-Defined AI AgentsS02 - E11🚀 How AI Agents Are Actually Being Used – Real-World Applications!AI is everywhere, but how do businesses, researchers, and creators actually use it in day-to-day operations? 🤔💡 Chris Tansey’s latest deep dive into templated AI agent definitions reveals the real-world use cases where AI is making a real impact. If you’ve ever wondered how structured AI can streamline workflows, generate insights, and even boost creativity, this episode is for you!📖 What You’ll Learn: 🔹 What Are Template-Defined AI Agents? A quick recap on how structured AI works. 🔹 5 Game-Changing Use Cases where AI is making an impact today. 🔹 Content Discovery & Curation: AI as your personalized digital curator. 🔹 Scientific & Environmental Reporting: AI-powered eco-friendly translators. 🔹 Creative Content Generation: Can AI actually be a muse? Spoiler: Yes! 🔹 Business Intelligence & Decision Support: AI as your data-driven strategic advisor. 🔹 User-Generated Data Analysis: AI for sentiment analysis and customer insights. 🔹 The 5 Core Principles that make AI work efficiently and reliably in any field.📚 Want to master AI workflow design? Check out Chris Tansey’s Amazon Kindle book: 🛒 Managing Digital Capital: A Prompt Engineer's Perspective 👉 Get Your Copy HereThis book breaks down how the principles of human capital management can be applied to AI agent oversight, making AI work like a structured workforce.✨ Key Themes: ✔️ AI as a workforce: The structured approach to managing AI like an employee. ✔️ The role of trust & autonomy in AI: Micromanaging AI is as bad as micromanaging people. ✔️ How to optimize AI workflows for efficiency & accuracy. ✔️ AI ethics & adaptability: Navigating the challenges of bias, fairness, and responsible AI use.💡 Thinking about implementing AI in your business? Learn how templated AI design can revolutionize your workflow!📌 Read more at 👉 ChrisCreatesWithAI.com🎙 Which of these AI use cases excites you the most? Drop a comment below!🔔 Like & Subscribe for more deep dives into AI, automation, and the future of work.#AI #Automation #PromptEngineering #AIWorkflow #BusinessIntelligence #ManagingDigitalCapital #ChrisTansey

Episode Title: Diving Prompt First: High-Level Guide to Templated AI Agent Creation ProcessS02 - E10🎯 Want AI That Actually Works? Follow This 7-Step Blueprint!AI assistants promise to revolutionize our workflow, but too often, they fall short—like a jammed printer right when you need it most. 😩💡 Enter Chris Tansey’s templated approach to AI agent creation! This episode breaks down his high-level guide into a step-by-step process so you can build AI that delivers real results.📖 What You’ll Learn: 🔹 Why Templates? Stop reinventing the wheel—consistency is key. 🔹 The 7 Steps to AI Success 🚀 Define role, set goals, give clear instructions, structure output, and more. 🔹 Structured vs. Flexible AI—When to define outputs and when to allow creativity. 🔹 How to scale your AI agents without them becoming a bottleneck. 🔹 Why iterative feedback loops are the secret to long-term AI success.📚 Want to dive even deeper? Check out Chris Tansey’s book: 🛒 Managing Digital Capital: A Prompt Engineer's Perspective Available now on Amazon Kindle 👉 Get Your Copy HereThis book explores how time-tested human capital management principles apply to AI agent oversight—bridging the gap between human leadership and digital automation.✨ Key Themes: ✔️ Clear Communication: The secret to better AI responses and stronger leadership. ✔️ Iterative Feedback: How AI prompting mirrors performance coaching. ✔️ AI Capabilities & Limitations: Managing AI like a well-structured workforce. ✔️ Trust & Autonomy: Why micromanaging AI is just as bad as micromanaging people. ✔️ Ethics & Adaptability: How to ensure fairness in hybrid workforces.💡 Tired of AI that overpromises and underdelivers? Learn how templated AI design can transform how you work!📌 Read more at 👉 ChrisCreatesWithAI.com🎙 What’s one task you’d automate with a templated AI agent? Drop your ideas in the comments!🔔 Like & Subscribe for more deep dives into AI, automation, and the future of work.#AI #Automation #PromptEngineering #AIWorkflow #ScalableAI #ManagingDigitalCapital #ChrisTansey

Micro-Management as AI Prompting - A Detailed Guide

Managing Contractors and AI - A Parallel Approach

AI Prompting and Human Capital Communication Parallels

Managing Digital and Human Capital Key Parallels

Self-Reflective Leadership Managing Digital & Human Capital

We dive deep into Comparing Managing LLMs with Managing Employees (With Prompt Examples).

We dive into Comparing Managing LLMs with Managing Employees.

We discover how Goal Oriented Frameworks our useful for successful chatbot interactions

We compare communicating with Chatbots to communicating with Rain Man.

We discuss a technique called self-consistency which enhances the reasoning capabilities of large language models (LLMs). This technique involves prompting an LLM to generate multiple reasoning paths for a question and then selecting the most consistent answer among these paths. This method improves the accuracy and reliability of LLMs, particularly for tasks requiring complex reasoning, such as arithmetic and commonsense reasoning.

ART addresses the limitations of traditional Chain-of-Thought (CoT) prompting by enabling LLMs to decompose tasks into multiple steps and utilize external resources, ultimately improving their performance on tasks requiring reasoning and complex problem-solving.

ReAct (Reason + Act) is a prompting technique that enhances the capabilities of Large Language Models (LLMs) by enabling them to reason, plan, and interact with external tools and data sources. This technique aims to overcome the limitations of traditional LLMs, which are restricted to their training data, leading to more accurate, reliable, and sophisticated applications.

A technique that enhances large language models (LLMs) by integrating them with external knowledge sources.

Large Language Models Are Human-Level Prompt Engineers.

Discover the Next Level of AI Interaction

AI That Thinks Like We Do:

Unraveling AI’s Thought Process

Building Complex Ideas, One Prompt at a Time

Maximizing Context with Targeted Examples

Mastering the Art of Zero-Shot Responses

A comprehensive guide to prompt engineering, a crucial aspect of working with large language models (LLMs)