AI Agents
AI agents are software systems that can perceive their environment, make decisions, and take actions autonomously. They range from simple chatbots to fully autonomous systems. Understanding the spectrum of agent capabilities — and their limitations — is essential for leaders evaluating agentic AI for their organizations.
Ownership: build one AI frontier team before you scale
I think now is the time to build one team that experiments with AI. Three or four people, real freedom to fail, an outcome they own, and AI agents as part of how the team works. Start with one, and let it teach you how to scale.
Running AI work wide, not just long
Most of the conversation about capable models is about jobs that run longer. There is a second direction nobody talks about: the same job run many times over, at once. It works, and it breaks in a place you would not expect.
Think bigger: what long-horizon AI models ask of leaders
The newest models stay on a single job for hours, sometimes days. The capability is obvious once you use them. Working out what to hand over turns out to be the harder problem, and it is a leadership problem more than a technical one.
What is recursive self-improvement (RSI)?
Recursive self-improvement is the point at which AI systems can design and build their own successors with little human involvement. In the past few weeks it moved to the centre of the industry's agenda.
AI as Aliens: what Project Hail Mary teaches us about working with other intelligences
In Project Hail Mary, the human and the alien start off without a shared language. They build one out of math, physics, and patience. The collaboration only starts to work when each understands what the other is built to do. That posture, sustained curiosity about a partner who genuinely does not see what you see, is the posture that might make AI work actually pay off in 2026.
AI for deep research: what the Stanford Virtual Lab still teaches us in 2026
In November 2024 a Stanford group spun up a Virtual Lab of AI agents using GPT-4o and ended up with experimentally validated nanobodies that bind a new SARS-CoV-2 variant. Eighteen months later the model looks weak and the design choices look stronger than ever. Four moves are worth pulling out: the AI picked its own team, five parallel meetings replaced individual judgement, the agents had hands, and compute time replaced calendar time.
SciSpace: AI-powered literature research for the rest of us
The Stanford Virtual Lab sits at the ambitious end of AI in science. Most working researchers and most executives trying to understand their R&D function will meet AI through something much more modest first. SciSpace is a good example: 280M papers, chat with your library, ~550 prebuilt task agents, inline citations as you write. The leverage is in pointing it at your own corpus first.
What is a self-driving lab?
A self-driving lab is a research operating model in which AI proposes the next experiment, robotic instruments run it, ML models read the result, and the loop runs again with light human supervision. The term has been in scientific use since 2018. What changed by 2026 is that the lab-in-a-box version has moved from research-paper claim to routine operating mode, and now interlocks with multi-agent systems in a way that was not possible five years ago.
What is a skills-based organization (SBO)?
A skills-based organization (SBO) is the structure of work, mobility, and decisions organized around discrete skills rather than jobs and ladders. In 2026 the concept matters twice over: skills are the foundation for AI agents as much as for humans. Skills work pays twice.
Company as intelligence: from AI overlay to AI-native
Jack Dorsey's Block laid off 40% of its workforce and the stock went up 26%. His manifesto argues that AI breaks a 2,000-year-old hierarchy problem. Three structural layers, three surviving roles, and one diagnostic question your leadership team should be asking.
Google Veo 3.1: the jagged edge of AI video
Released by Google DeepMind in January 2026, Veo 3.1 is a text-to-video and image-to-video model integrated across Gemini, Flow, YouTube Shorts, and Vertex AI. The creative iteration speed, not the rendering quality, is the actual product.
Six thinking hats for hybrid teams
Edward de Bono's 1985 framework for separating thinking modes turns out to be the most practical guide for leading teams where some members are human and some are AI. Parallel thinking is what agentic AI has been quietly implementing all along.
Writing skills: teaching AI how you think, write, and create
Skills are no longer just a coding trick. With 740,000+ skills across 30+ AI agents, they're the open standard for encoding expertise. Three open-source skill projects show what's possible for writers, thinkers, and creators.
The Jazz Model: Leading Hybrid Human-AI Teams
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.
AI Disruption: Two Lenses for Seeing What's Coming
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.
Base44 Superagents: Always-On AI Agents Without Code
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.
Team Tenets: From Leadership Principles to Practical Mechanisms
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.
What Is an Agent Harness?
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.
Bias for Action Revisited: When Experimentation Cost Approaches Zero
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?
Comet Browser: AI-Native Browsing from Perplexity
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.
Rethinking Engineering Organizations: The Block-Coinbase Contrast
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?
What Is Computer Use?
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.
Leadership Principles in the Age of AI Agents
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.
Intent Engineering: The Missing Layer in Enterprise AI
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.
Building AI Agents That Work: 10 Design Principles for Business Leaders
Ten practical principles for leaders building or evaluating AI agent systems - whether for customer experience, internal operations, or any business function.
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.
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?
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.
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.
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.
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.
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 ...