Human-AI Collaboration - The Thinking Lens

Weekend Reflections #6 | The Daughter Test

[Views are my own]. She was eight and loved to sing. I had just bought her a vocal processor and asked her to help me connect the gear. She looked at the cables. Then at the processor. Then at me. "Which one goes where?" I paused. Because I&

Human-AI Collaboration

Weekend Reflections #5 | The Speed of Doubt: When AI Outruns Trust

[Views are my own] Last week I ran a competitive analysis that would normally have taken me half a day. With AI, the first version took ten minutes. That was not the strange part. The strange part was that it was good. I did not discard it. I did not

Human-AI Collaboration

Weekend Reflections #4 | The Molting

For centuries, automation stripped roles of their execution layer. The roles that survived were the ones with judgment underneath.

Human-AI Collaboration

Weekend Reflections #3 | The Fluency Tax

[Views are my own] This week, I noticed something in my own habits. As an Italian living in Berlin and working mostly in English, I now default to English with AI even when it is not the language that feels most natural to me. That felt worth paying attention to.

Human-AI Collaboration

Weekend Reflections #2 | The Mirror Test

I tested whether I could catch myself anthropomorphizing AI. Forty-five minutes later, I had shared more than intended. The trap is not ignorance; it is fluency.

Human-AI Collaboration

Weekend Reflections #1 | The Momentum Wave

Most ideas don't die because they are bad; they die when momentum breaks before testing. AI shrinks the gap between thought and test, creating a Momentum Wave where natural language lets anyone prototype. But beware: speed without customer validation is just fast failure.

Knowledge Management & Curation

The Judgment Economy (Part 4/4): Connections vs. Collections

[Views are my own] In the first three parts of this series, we built the case for a new strategic mandate. We moved from filtering Signal vs. Noise, to creating Information vs. Insight, to building an enterprise-grade framework for Credibility vs. Plausibility. In this final part, we move to the

Human-AI Collaboration

Vibe-Coding Is a Filter, Not a Threat: How to Use It Without Wasting Your Team’s Time.

AI is changing the world fast. Stop focusing on who is using what tool. Focus on why, and double down on the human skills that AI can't replicate: your judgment, your creativity, and your scars. That is the only moat that lasts.

Human-AI Collaboration

We’ve Reached the Point Where Good Writing Looks Suspicious

A Personal Perspective on AI, "Polished Emptiness," and the Primacy of Thought.

Human-AI Collaboration

The ChatGPT Report and The Enterprise Blind Spot

OpenAI’s ChatGPT usage report is consumer-only, so enterprise signal is skewed. Still clear: AI is a copilot. Writing dominates, most of it editing. Younger users drive volume; older pros drive work. B2B: prioritize decision support, co-creation, embedded copilots, governance.

Human-AI Collaboration

PAIR: A Simple Model for AI-Accelerated Apprenticeship

AI should speed work, not erase the training ground. A Seniors-only + AI model boosts short-term output but drains your pipeline and increases risk. Try Senior + Junior + AI: juniors draft with AI, seniors inspect thinking. Treat mentorship as first-class work and measure it. Build great teams. Now.

Human-AI Collaboration

Beyond the Dashboard | Principle 11: Turn AI into a Judgment Multiplier

AI is not your strategist; it multiplies your judgment. Automate discovery, keep humans in the decision loop, and treat judgment as the API. Clean hypotheses and consequence paths in, clarity out. Use AI to amplify decisions, not outsource them. Automate discovery, own decisions. Judgment is moat.

Human-AI Collaboration

From “Content Is King” to “Judgment Is the Crown”: Rethinking Authority in the AI Era

Content isn't king anymore. AI makes endless "good" content; trust and judgment are scarce. Your lived experience, context, and perspective are the differentiator. Use AI as leverage, not a crutch. Earn attention by solving sharp problems for real people and building credibility. Own your voice. Go.

Prompt Engineering & AI Instructions

The “One Prompt” Fallacy: Why Voice, Not Prompts, Wins

Stop chasing magic prompts. The fix is not a template. Define your problem, then train AI on your own writing to build a voice profile. Feed real samples, extract patterns, and revise in your style. Protect your data. Do not copy tone. Engineer sharper thinking, not generic outputs. Your voice wins.

Data-Driven Decision Making

Stop Doing Discovery Karaoke

Match discovery to risk, not habit. Most teams default to interviews, tests, and betas, which miss blind spots. Treat Compliance & Ethics as a first-class risk. Build a simple map: risk → stage → methods. Use AI to speed clustering, summarization, and signal detection. Focus on uncertainty reduction

Prompt Engineering & AI Instructions

"Ahahaha! Busted! You used an em dash—must be ChatGPT!"

Ahahaha! Busted. You used an em dash, must be ChatGPT. I learned about hyphen, en dash, and em dash only recently. I asked ChatGPT, checked Treccani and Merriam Webster. I use AI a lot, but the voice is mine. Tools help me write clearer. The thoughts and the words are still mine. Fully human. True.

Human-AI Collaboration

The Hidden Cost of Framework Thinking

We live in a world of playbooks and quick frameworks. They help, but when they replace thinking, contribution dies. Stop blind execution. Ask: Is this valid for my context? Original thought is the value. Don't run someone else's logic. Slow down, think, and make it yours. Choose thinking over hacks.

Prompt Engineering & AI Instructions

The Hidden Skill That Unlocks Generative AI

Generative AI’s power is tied to our ability to communicate with clarity; its output reflects the input. I saw this with my 8-year-old daughter: her vague prompt for a unicorn yielded generic results, but a detailed one created what she imagined. AI is a mirror.