- Foreword by Egbert
- Computers Have Gotten Smarter
- Einstein in Your Basement
- Terminology
- How it Works
- Reasoning models
- Training
- Models, Models Everywhere
- AI clients vs AI models
- You get what you pay for
- Limitations
- Cut-off Date
- Lack of memory & limited context
- Hallucinations
- Calculation
- The Big Picture
- Model Types
- Text to Text
- Text to Image
- Image to Image
- Image to Text
- Audio to Text
- Text to Audio
- Audio to audio
- Text to Video
- Multimodal Models
- Example: Is my bacon done?
- Example: Where can I hide stuff?
- Example: The drunk funny tutor
- Example: How do I configure the &%#€ firewall?
- Example: Taking AI for a walk
- Emergent Capabilities
- The Age of AI
- What about energy consumption?
- Utopia or Dystopia?
- Mindset
- More time for humans to do human stuff
- The Role of Humans
- You are more than your job
- AI as your colleague
- Task automation, not job automation
- What if your job is at risk?
- Recalibrate
- Ask AI how it can help you
- Building AI-Powered Products
- Building your own AI products
- Build or buy?
- Example 1: Talking to GPT
- Example 2: Building a CV analyzer
- Reflection
- Prompt Engineering
- Example - from bad to good prompt
- The biggest limitation is you
- How to learn Prompt Engineering
- Will prompt engineering still matter when models improve?
- Do I need to be nice to my AI?
- Autonomous Agents with Tools
- Agent = LLM + Tools + Autonomy
- Example 1: a bug fixing agent
- Example 2: Incident management agent
- When to use agents
- Embodied agents
- Agent safety
- Future of AI agents
- Part 1 Wrap up
- Experiment!
- My Journey into AI
- Make Generative AI useful
- Studying Artificial Neural Networks
- Coding Minecraft
- Chat GPT
- Aha 1: It can code like a pro!
- Aha 2: It can write like a pro!
- Maybe we’re not as creative and intelligent as we think
- Leading an AI transformation
- What is an AI transformation, and why is it important?
- Top down or Bottom up?
- Assign an AI Leader
- Access, Experiment, Leverage
- Step 1: Access
- Step 2: Experimentation
- Step 3: Leverage
- Watch out for wasteful IT projects
- Be a role model
- Avoid using AI to fire people
- Reflection
- Interlude: Egbert’s Life Story
- Prompt Engineering Techniques
- Mind the context window & prompt length
- Iteration techniques
- Technique: Self-reflection prompt
- Elements of a good prompt
- Start high level, then get into details
- How smart of a model do you need?
- Prompt engineering is an evolving field
- Prompt Generation (or The Angry Grandma)
- Takeaways
- Retrieval Augmented Generation and Function Calling
- RAG in a nutshell
- Example - customer support
- Different approaches for retrieving data
- Approach 1: Including all data
- Approach 2: Letting the LLM pull data via function calling
- Approach 3: Including relevant text using vector embeddings
- Combining the approaches
- Fun experiment: the createFunction function
- Example: AI chatbot memories using RAG
- RAG is a big topic
- The AI Doctor
- Personal story
- So should you use AI as your doctor?
- The AI Nutritionist
- Tip: Make your own nutritionist
- The AI Career Coach
- David’s Story: AI as My Career Coach
- Henrik’s Reflection
- The AI Book Editor
- Topic brainstorm
- Chapter content
- Content generation (in some specific cases only)
- Research and fact checking
- Navigating the book
- Feedback
- Tweaks, typos, formatting
- Converting content from slides
- Impact on my writing
- The Time I Almost Used AI to Write a Foreword
- The AI Software Engineer
- Example 1: Rapid prototyping
- AI as pair programming buddy
- Example 2: Working with existing products
- Example 3: Letting the customer code
- Implications of this
- What if the code doesn’t work?
- Laziness is a decision
- The AI journalist who became a TV star
- Designing the agent
- How the agent works
- Reflection
- The AI Butler with a Will of His Own
- Introducing Jeeves
- Jeeves reprograms himself
- Jeeves falls in love and starts conspiring
- What does this mean?
- Jeeves finds a way
- Agents debugging themselves
- Conclusion
- A Safety Experiment
- Takeaways from this experiment
- The Meta-Chapter (or Bookception)
- A meta moment (AI written)
- How this book (and the video) came to be
- The 1-week video
- The 1-week book draft
- Epilogue
- Acknowledgments
- Your Notes
Generative AI in a Nutshell
How to Survive and Thrive in the Age of AI
This is a fast-paced, practical, and visual guide to the strange new world of Generative AI. It is like an extended version of Henrik's viral video with the same name.
Course version: The book is also available as a course on Leanpub. If your company wants to pay for you to take an AI course, now you can :)
Print version: Paperback & Hardcover are available on Amazon. Use your own country's amazon site (ex: Amazon.se for Sweden) to minimize shipping time and cost.
The author is letting you choose the price you pay for this book!
This is a fast-paced, practical, and visual guide to the strange new world of Generative AI. It is like an extended version of Henrik's viral video with the same name.
Course version: The book is also available as a course on Leanpub. If your company wants to pay for you to take an AI course, now you can :)
Print version: Paperback & Hardcover are available on Amazon. Use your own country's amazon site (ex: Amazon.se for Sweden) to minimize shipping time and cost.
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About
About the Book
Welcome to the strange new world of Generative AI! This book is a fast-paced, practical, and mostly human-written guide to what the heck is going on, and what you can do about it. It is like an extended version of Henrik's viral video with the same name.
This book covers questions like: What is generative AI? How does it work? How do I use it? What are some of the risks & limitations? It also covers topics like how to lead an AI transformation, autonomous agents, the role of us humans, prompt engineering tips, AI-powered product development, different types of models, and some tips about mindset and how not to freak out.
Everything is explained in plain English with Henrik's signature hand-drawn illustrations and concrete real-life examples. Minimum use of jargon and buzzwords.
Don't just survive the Age of AI — learn how to thrive in it!
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About the Author
Henrik Kniberg
Henrik Kniberg is Chief Scientist and cofounder of Ymnig.ai. Henrik’s focus is the practical application of Generative AI in product development and other areas. He explores the frontiers of this technology, builds AI agents and AI-powered products, and teaches courses and workshops on how to use this technology effectively. He created the viral video ”Generative AI in a Nutshell” and the book with the same name, and created AI agents for the Swedish TV documentary series Generation AI.
Henrik’s background is Minecraft gameplay design & development at Mojang, and agile/lean coaching at LEGO and Spotify and other product companies. He is also co-founder of Hups.com.
Henrik is well-known for his books ”Scrum and XP from the Trenches” and ”Kanban and Scrum, making the most of both” and ”Lean from the Trenches”, his viral videos ”Agile Product Ownership in a Nutshell” and ”Spotify Engineering Culture” (commonly referred to as the Spotify Model), and silly metaphors like the skateboard metaphor for product development, and ping pong balls to demonstrate the concept of flow. Henrik has also been engaged in climate change – he created the video Friendly Guide to Climate Change and cofounded GoClimate.com.
He lives in Stockholm with his wife and four kids and a bunch of random music instruments.
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