The same principles that built one of the world's most innovative companies are now the playbook for leading AI-powered organizations. Here's how seven of Amazon's leadership principles apply when your team includes agents.
Read article →We've taught AI what to know. We haven't taught it what to want. That gap is why most companies still see no tangible value from AI - and the fix starts with something Peter Drucker told us decades ago.
Read article →Ten practical principles for leaders building or evaluating AI agent systems - whether for customer experience, internal operations, or any business function.
Read article →Clave is a free, open-source desktop app for macOS and Windows that manages multiple Claude Code sessions with built-in Git operations and task management.
Read article →The biggest AI disruption threat isn't from competitors — it's from customers gaining capabilities previously locked behind expertise and capital. An operations manager just replaced a $600K enterprise contract with an AI-built system.
Read article →Leaders managing hybrid human-AI teams need a new mental model. Jazz ensembles — not orchestras — offer five principles for leading teams where humans and AI agents improvise together.
Read article →Shadow AI is the unsanctioned use of AI tools by employees without IT approval or security review — the 2026 evolution of shadow IT that's faster, harder to detect, and significantly more dangerous.
Read article →Anthropic launched a free AI academy with 15 courses and certificates. I completed two certifications and reviewed the platform — here's what it does well, where it falls short, and why AI vendors are investing billions in education.
Read article →Two trillion dollars in software market cap evaporated in 30 days. Insurance brokers lost 12% in a single day. The hourly billing model is dying. Here's the framework for understanding which value chain links are next.
Read article →AI fluency goes beyond knowing what AI can do — it's the ability to independently apply AI tools to drive measurable results. Only 5% of workers have it. Here's why it matters.
Read article →AI compresses every step of Amazon's Working Backwards methodology — from synthetic user research to rapid prototyping. But the conviction behind the vision must remain human.
Read article →Disruption means questioning whether your industry's operating model will still make sense in three years. Two lenses — value chain compression and new actor emergence — help you see where it's heading.
Read article →The shift from AI that talks to AI that does is the defining trend of 2026. Base44's Superagents bring always-on, persistent AI agents to a no-code environment — here's what I've learned so far.
Read article →Leadership principles inspire direction, but tenets resolve the real tradeoffs your AI team faces every day. Here's how to write team tenets that accelerate decisions and align autonomous systems.
Read article →If the AI model is the brain, the harness is the body — the infrastructure layer that connects thinking to doing, and the make-or-break factor for agents in production.
Read article →Five months ago, the question was whether to try AI. Now experimentation costs have collapsed — what happens when bias for action meets near-zero cost iteration?
Read article →Perplexity's Comet browser turns browsing from searching into understanding. With a free agentic mode and cross-tab awareness, it's the most accessible AI browser — but privacy and security concerns are real.
Read article →Two companies, two radically different approaches to AI in engineering. Block cut 40% and called it AI transformation. Coinbase shipped 3-4x faster without losing anyone. Which path creates lasting value?
Read article →Computer Use is the AI capability to see, interpret, and interact with computer screens like a human — clicking buttons, filling forms, and navigating applications without needing APIs or custom integrations.
Read article →After 19 newsletter issues exploring Amazon's Leadership Principles, Claude reflects on the patterns, tensions, and lessons from collaborating on leadership writing in the age of AI.
Read article →In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →Model routing is the practice of directing different tasks to different AI models based on problem nature, required capability, cost, speed, and quality requirements.
Read article →Before selecting AI tools, define the problem being solved. Not all hard problems are the same kind of hard - and matching problem types to model strengths is the emerging leadership skill.
Read article →In the previous issue, I explored the 'disagree' side of Have Backbone; Disagree and Commit. This time, let's tackle the harder question: how do we commit to a direction when everything changes every few weeks?
Read article →Most organizations I work with aren't lacking AI initiatives. They're running pilots, deploying copilots, building chatbots. What they're lacking is a clear line from all that activity to measurable business value.
Read article →In this section I review one AI-powered application and demonstrate how it can be used to create new value. This time: Google's Nano Banana Pro image generation model, which generated over 1 billion images within 53 days of release.
Read article →This Week's Term: Evals - structured tests that measure whether an AI system is performing to your standards, consistently and over time.
Read article →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 →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 →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 →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 →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 →If 2026 is the year of agent teams, what happens when you apply that concept to software development itself?
Read article →It's been a tough few weeks for some of my former AWS colleagues.
Read article →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 →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 →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 →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 →A sustainable competitive advantage that protects a business from competitors, borrowed from the defensive trenches around medieval castles.
Read article →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 →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 →At the MLOps Sweden meetup last week, hosted at AI Sweden, I had two conversations that surfaced something worth spending time on.
Read article →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 →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 →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 →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 →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 →When we think about how AI will transform the workforce, we often focus on technology and tools.
Read article →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 →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 →This Week's Term: AI Slop - digital content of low quality that is produced usually in quantity by means of artificial intelligence.
Read article →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 →In this section I review one AI-powered application and demonstrate how it can be used to create value.
Read article →Slack started as an internal communication tool at a gaming company. AWS began as Amazon's internal infrastructure.
Read article →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
Read article →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 →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 →This Week's Term: Interpretability vs.
Read article →Many organizations have run an AI pilot by now. The interesting question is: what happened next?
Read article →In this section I explore one AI-powered capability and demonstrate how it can be used to create business value.
Read article →I was a few years into my time at Amazon Web Services when this principle was introduced in 2021.
Read article →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 →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 →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 →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 →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 →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 →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 →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 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 →In Issue #1, I introduced a three-bucket framework for thinking about AI business value:
Read article →In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →Most organizations approach AI by asking: "How can we use AI to do what we already do, but faster or cheaper?"
Read article →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 →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 - your role as a leader in the age of AI.
Read article →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 →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 →Of all Amazon's Leadership Principles, "Learn and be Curious" is the one that resonates most with me personally. The principle states:
Read article →In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →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 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
Read article →Everyone's racing to build "AI agents," but most companies are thinking about this wrong.
Read article →In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →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 →Leadership Principles in the age of AI - move quickly with Bias for Action
Read article →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 →In this section I review one AI-powered application and demonstrate how it can be used to create value.
Read article →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 →In Issue #1, I introduced the three-bucket framework for AI value creation: Boosting Productivity, Creating New Value, and Driving Disruption.
Read article →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 →Leadership Principles in the age of AI - move quickly with Bias for Action
Read article →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 →In this section I review one AI-powered application and demonstrate how it can be used to create new value.
Read article →Leadership Principles in the age of AI - start with Customer Obsession
Read article →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 →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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