Think Big Insights
Bite-sized insights from the Think Big Newsletter — leadership principles, business frameworks, tool reviews, and the AI terminology that actually matters.
Have Backbone; Disagree and Commit in the Age of AI
I was at Tech Arena last week. This is one of the biggest tech events in the Nordics - a place to catch the leading trends, talk to startups, investor, politicians, and users.
Read article →Rethinking How We Design AI Experiences
For years, the design process for digital products has followed a familiar sequence: research users, create personas, map journeys, write problem statements, brainstorm solutions, wireframe, test, iterate.
Read article →Shape of AI: A Pattern Library for AI UX Design
In Section 2 I argued that the old design process isn't producing great AI experiences - and that teams need new principles for building products people actually love.
Read article →What Are MCP Apps?
In Issue #12, I introduced term MCP - the open standard that acts as a "USB-C port for AI," letting AI models connect to external tools and data sources through a universal interface. Since then, MCP has grown rapidly.
Read article →Agent Teams: The Next Frontier of AI Business Value
I ran two sessions this week with AI champions at a customer I'm working with. The topic: what agents actually mean, and what the role of humans becomes when working with them.
Read article →Base44 Academy: Building Apps Without Code
If 2026 is the year of agent teams, what happens when you apply that concept to software development itself?
Read article →Strive to Be Earth's Best Employer in the Age of AI
It's been a tough few weeks for some of my former AWS colleagues.
Read article →What Is AI Orchestration?
This Week's Term: Orchestration - the coordination of multiple AI agents, tools, or capabilities to accomplish complex tasks that no single component could handle alone.
Read article →AI Strategic Inflection Points: Transforming Business Models
Drawing on insights from MIT Sloan's Artificial Intelligence: Implications for Business Strategy program and Gartner research, this framework outlines key principles for successfully leading AI-driven transformation.
Read article →Google AI Studio and Gemini 2.5 Pro: Enterprise AI Powerhouse
When Mika writes about paradigm shifts - about recognizing when optimization stops being enough - he's describing something happening right now in one of the most consequential business tools ever built: Excel.
Read article →Invent and Simplify: Lessons from an AI-First Leader
Sometimes the best insights come from people who've lived through what the rest of us are only reading about. This issue features a guest article.
Read article →What Is an AI Moat?
A sustainable competitive advantage that protects a business from competitors, borrowed from the defensive trenches around medieval castles.
Read article →Claude Cowork: AI as a Collaborative Team Member
I need to be transparent about something: the tool I'm reviewing in this section is the same one I'm using to write this newsletter.
Read article →Hire and Develop the Best: Leading Hybrid Human-AI Teams
This month I onboarded a new team member. I thought carefully about what context they'd need to succeed - our goals, our working style, the projects in flight, where to find key documents.
Read article →The Unstructured Data Goldmine: Your Hidden AI Advantage
At the MLOps Sweden meetup last week, hosted at AI Sweden, I had two conversations that surfaced something worth spending time on.
Read article →What Are Centaur Teams?
This Week's Term: Centaur Teams - human-AI partnerships that combine human judgment with AI computational power, named after the mythological creature that was half-human, half-horse.
Read article →AI Readiness Assessment: Where Does Your Organization Stand?
When I work with executives, leadership teams, and AI tasks forces on their AI journey and stratgey, sooner or later a key question comes up: should they build AI solutions in-house, purchase them from vendors, or ado...
Read article →Deliver Results: Anthropic's Soul Documents and Value-Aligned AI
In 1942, Isaac Asimov introduced the Three Laws of Robotics - a set of rules designed to ensure robots would never harm humans. Simple, elegant, hierarchical.
Read article →VoiceInk: AI Transcription That Changes How You Capture Ideas
What if you could simply talk to all your applications? Not just dictation in a single app, but voice input that works everywhere - your email, Slack, AI assistants, documents.
Read article →What Is AI Inference?
This Week's Term: AI Inference - the process of running a trained AI model on real-time data to generate predictions, answers, or outputs. If training is learning, inference is putting that learning into practice.
Read article →AI and the Future of Work: Beyond Technical Transformation
When we think about how AI will transform the workforce, we often focus on technology and tools.
Read article →Ownership: Acting on Behalf of the Entire Company with AI
When I work with enterprise clients on AI strategy, I sometimes ask the following question: "Who owns the long-term implications of your AI decisions?"
Read article →TempoHack: AI-Powered Time Tracking I Built Myself
I watch a lot of podcasts and video content. It's one of my primary sources for ideas, frameworks, and insights that make their way into this newsletter and my client work.
Read article →What Is AI Slop?
This Week's Term: AI Slop - digital content of low quality that is produced usually in quantity by means of artificial intelligence.
Read article →Earn Trust: Vocal Self-Criticism in the Age of AI
In 1997, Garry Kasparov became the first person to "lose his job" to AI when IBM's Deep Blue defeated him in chess. For years, this defeat symbolized humanity's vulnerability to machines.
Read article →Perplexity for Enterprise Research
In this section I review one AI-powered application and demonstrate how it can be used to create value.
Read article →Productizing Internal AI Tools: From Efficiency to Revenue
Slack started as an internal communication tool at a gaming company. AWS began as Amazon's internal infrastructure.
Read article →What Is MCP (Model Context Protocol)?
This Week's Term: Model Context Protocol (MCP) - an open standard that enables AI assistants to connect with external data sources and tools through a universal interface, allowing applications to provide context to ...
Read article →Claude Innovation Skills: Systematizing Innovation with AI
Claude Innovation Skills: systematizing innovation with AI
Read article →Frugality: Accomplishing More with Less in the AI Era
When ChatGPT launched in November 2022, I became curious about how far I could stretch it. I asked myself a specific question: Could this become my innovation copilot?
Read article →Hackathons as Innovation Engines: From Events to Movements
In Issue #1, I introduced the three-bucket framework for AI business value: Boosting Productivity, Creating New Value, and Driving Disruption. We've explored productivity gains and disruption in previous issues.
Read article →What Is Interpretability vs. Utility?
This Week's Term: Interpretability vs.
Read article →From AI Pilots to Production: The MIT Maturity Model
Many organizations have run an AI pilot by now. The interesting question is: what happened next?
Read article →Custom GPTs: Building Specialized AI Assistants
In this section I explore one AI-powered capability and demonstrate how it can be used to create business value.
Read article →Success and Scale Bring Broad Responsibility
I was a few years into my time at Amazon Web Services when this principle was introduced in 2021.
Read article →What Are AI Agents? The Five Levels
AI Agents are autonomous AI systems that can reason about problems, decide which tools to use, take actions across multiple steps, and iterate on their work without human intervention at each decision point, moving be...
Read article →Customer Obsession Revisited: Your Shield Against the Innovation Graveyard
Amir has discussed this Leadership Principle in the first issue of his newsletter. No wonder that he started with this as this is undoubtedly the number one, the most important principle of all: Customer Obsession.
Read article →Mapping AI Value Across Modalities
As we've said several times before, the most common mistake I see is starting with the technology. Business leaders want to know which AI tool to buy, which model to use, which vendor to choose. But that's backwards.
Read article →Miro AI: Putting Intelligence on the Shared Canvas
Most AI tools solve for individual productivity. You ask ChatGPT a question, get an answer, and bring that answer back to your team.
Read article →What Is Multimodal AI?
This Week's Term: Multimodal AI - AI systems that can understand and generate content across multiple types of input and output: text, images, audio, video, and code, processing them together rather than in isolation.
Read article →Building the Business Case for AI Investments
When I review AI initiatives with business leaders, I see a concerning pattern. Teams are excited, budgets are allocated, tools are being evaluated. But when we ask "How exactly will this create value for your business?
Read article →Dive Deep: AI as a Force Multiplier for Understanding
For decades, business leaders faced an impossible choice when it came to understanding their markets, customers, or prospects: invest heavily in deep research or settle for surface-level insights you could afford.
Read article →LinkedIn AI Search: Finding the Right People Faster
The Human Problem: You need to find the right person. A co-founder who gets your vision. An expert who's solved the exact problem you're facing. An investor who backs companies like yours.
Read article →What Is Synthetic Data?
What it means: Synthetic data is artificially generated information that mimics the statistical properties and patterns of real-world data, but doesn't contain any actual observations from reality.
Read article →Driving Disruption: The Third AI Value Bucket
In Issue #1, I introduced a three-bucket framework for thinking about AI business value:
Read article →NotebookLM: Your AI Research Companion
In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →Think Big: The Leadership Principle That Defined Amazon
Most organizations approach AI by asking: "How can we use AI to do what we already do, but faster or cheaper?"
Read article →What Is Context Engineering?
This Week's Term: Context Engineering - the practice of deliberately structuring, curating, and providing the right information to AI systems to maximize output quality, accuracy, and relevance.
Read article →Canva AI: From Design Tool to Visual Productivity Suite
In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →Insist on the Highest Standards in the Age of AI
Insist on the Highest Standards - your role as a leader in the age of AI.
Read article →The Product Era of AI Has Arrived
In the last 60 days, we've witnessed a remarkable shift. OpenAI's Sora 2 hit 1 million downloads in five days with a complete video creation platform including social features and identity insertion.
Read article →What Is Vibe Coding?
Vibe coding is software development where AI generates most or all of the code based on high-level descriptions or prompts - it's all about the vibe, not the implementation details.
Read article →Learn and Be Curious: Why This Moment Demands It
Of all Amazon's Leadership Principles, "Learn and be Curious" is the one that resonates most with me personally. The principle states:
Read article →Teaching AI Your Workflows with Claude Skills
In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →What Is an AI Hallucination?
This Week's Term: AI Hallucination - when an AI model confidently generates false information that sounds plausible but has no basis in reality, essentially making things up rather than admitting uncertainty.
Read article →When AI Doesn't Know What You Know: Building Knowledge Moats
When I work with organizations on AI initiatives, I often hear: "We've implemented ChatGPT" or "We're using Claude" or "We're rolling out Copilot.
Read article →Are Right, A Lot: When AI Can't Tell You You're Wrong
Are right, a lot: when AI can't tell you you're wrong
Read article →The Five Levels of AI Autonomy
Everyone's racing to build "AI agents," but most companies are thinking about this wrong.
Read article →GloryHack: The Workflow-Amplified Approach to AI
In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →What Is Few-Shot Prompting?
This Week's Term: Few-shot prompting - the technique of providing AI with 2-5 examples of desired output before asking it to generate new content, enabling the model to learn the pattern and apply it to similar tasks.
Read article →Bias for Action Part 2: From Analysis Paralysis to AI Progress
Leadership Principles in the age of AI - move quickly with Bias for Action
Read article →Boosting Productivity: The First AI Value Bucket
For decades, getting insights from your data meant one of two things: either you knew SQL and could query databases directly, or you submitted requests to your data team and waited for reports.
Read article →ChatGPT Advanced Voice: Conversational AI That Listens
In this section I review one AI-powered application and demonstrate how it can be used to create value.
Read article →What Is Retrieval-Augmented Generation (RAG)?
This Week's Term: Retrieval-Augmented Generation (RAG) - an AI architecture that combines large language models with dynamic information retrieval, allowing models to fetch relevant documents or data before generating...
Read article →The AI Customer Journey Framework
In Issue #1, I introduced the three-bucket framework for AI value creation: Boosting Productivity, Creating New Value, and Driving Disruption.
Read article →Ainno: Turning Expertise into AI Companions
When Gunnar and Magnus from Amplify Innovation approached me about their Systematic Innovation Management program, they had a classic learning and development challenge: comprehensive, valuable content that learners n...
Read article →Bias for Action: Moving Quickly in the Age of AI
Leadership Principles in the age of AI - move quickly with Bias for Action
Read article →What Is Human-in-the-Loop (HITL)?
This Week's Term: Human-in-the-Loop (HITL) - a design pattern where AI systems operate with ongoing human oversight, intervention, or validation at critical decision points rather than running fully autonomously.
Read article →Creating New Value with Voiceflow
In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →Customer Obsession: Leading with Purpose in the Age of AI
Leadership Principles in the age of AI - start with Customer Obsession
Read article →The Three Buckets of AI Business Value
When I work with business leaders and their teams, one of the most common challenges I hear is: "We know AI is important, but there are so many tools and possibilities and we don't know where to start.
Read article →What Is Answer Engine Optimization (AEO)?
This Week's Term: Answer Engine Optimization (AEO) - the practice of optimizing content to appear in AI-powered answer summaries across ChatGPT, Claude, Google AI Overviews, Perplexity, and other LLMs.
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