Writing

Rick Rubin went on stage in Helsinki the day after my talk. Someone asked how he resolves creative differences with artists. His answer was simple: change the conversation from "I disagree" to "let's build it." Then he shared a story: An artist played him a song. The transition didn't work. Rubin told him so. The artist said, "We'll just cut that part in half." Rubin thought to himself: What a dumb idea. But he didn't say that. He said, "Let's try it." The artist played it. It worked. Rubin is a legend. He's produced everyone from Johnny Cash to Jay-Z. Instead, he bit his tongue and let the artist prove him wrong. The principle: when you make an idea tangible, it stops being the person's idea. It becomes something you can both look at objectively and improve together. Once you build it, the truth is obvious. Here's what this looks like in practice: Your designer wants to change the entire homepage layout. You think it's too risky. Instead of three meetings debating it, you say: "Let's build a prototype and test it with 50 users this week." Your sales team wants to restructure the pricing page. Instead of blocking it because you're worried about conversions, you say: "Let's run it as an A/B test on 20% of traffic for two weeks." Your engineer wants to rebuild a core feature from scratch. You think it's overengineered. But instead of killing it in the planning phase, you say: "Spike it out in three days and show me if the performance gain is real." You're not saying yes to everything. You're saying, "Let's find out." Rubin also said something that stuck with me: "If there's disagreement, I always side with the artist's vision. Because to them, it's their career. To me, it's just one piece of my portfolio." Most leaders think backing down makes them look weak. Rubin knows that siding with the person who has the most at stake makes better work happen. Your job isn't to be right. It's to create the conditions where the best idea wins. Stop debating. Start building. P.S. This insight is from this week's newsletter where I break down why Yamaha dominates while Steinway got sold to private equity: https://lnkd.in/efSqP_9K P.P.S. Access additional research links, the podcast, and the full archive in the first comment 👇 Thank you to Nordic Business Forum!

Want to stay motivated every single day? Borrow a strategy from Harvard. Then borrow another from stand up comedy. Together, they’re a powerhouse for momentum, motivation, and mastery. Here’s how it works: Let’s start with Harvard. Researcher Teresa Amabile studied 12,000 daily work diaries across 8 companies. She wanted to know: What truly motivates people on a day to day basis? What she found changed how we understand drive. The #1 driver of daily motivation wasn’t: Money Praise Perks It was progress. The days people made progress on meaningful work were the days they felt the best. Progress isn’t a luxury. It’s a psychological necessity. So how do we make progress feel visible especially on days when it’s not? Use a “Progress Ritual.” → At the end of the day, pause. → Write down 3 small ways you moved forward. → That’s it. No fanfare. Just ritual. This works because we rarely notice our progress in real time. It gets buried under busyness, meetings, and mental noise. The act of looking back gives your brain the reward it needs to keep going. Momentum builds from meaning. Now let’s add some comedy. Young Jerry Seinfeld had one goal: write new material every day. To stay on track, he created a brilliant system. Each day he wrote, he put a big red X on his calendar. Soon, a chain of Xs formed. And here’s the key: Don’t break the chain. One red X becomes two. Two becomes ten. Ten becomes identity. Whether you’re writing, coding, or training Daily action + visual chain = long-term motivation. Summary: The Two-Part Motivation System From Harvard: Record 3 ways you made progress each day. From Seinfeld: Mark an X for each day you show up then don’t break the chain. Progress fuels purpose. Consistency fuels confidence. Apply both and you’ll stay on track especially on the tough days. Because when your days get better, your weeks get better. When your weeks get better, your months get better. When your months get better, your life gets better. It starts with one small win today.

𝗢𝗽𝗲𝗻𝗔𝗜 𝗷𝘂𝘀𝘁 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝘁𝗵𝗲𝗶𝗿 𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗚𝗣𝗧-4.1 𝗽𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 𝗴𝘂𝗶𝗱𝗲! It provides a detailed guide on how to steer GPT-4.1 with precision, including examples, tips, and advanced techniques. You can access the full version for free below. ⬇️ 𝗜𝗻 𝘀𝘂𝗺𝗺𝗮𝗿𝘆, 𝗵𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗸𝗲𝘆 𝗲𝗹𝗲𝗺𝗲𝗻𝘁𝘀: ➜ Be Clear with Your Instructions: GPT-4.1 is really good at following directions, but only if you're specific. The more clear and direct your prompt, the better the response. ➜ Break Down Complex Tasks: If you're working on something complicated, ask GPT-4.1 to “think step by step.” It helps the model give more accurate and thoughtful answers. ➜ Use Structure: If you need to share a lot of info, use clear structure—like markdown or bullet points. This helps GPT-4.1 understand and organize the info better. ➜ Format Your Prompts with Clear Sections: Structure your prompts for easier comprehension:   - Role and Objective   - Instructions (with subcategories)   - Reasoning Steps   - Output Format   - Examples   - Final instructions ➜ Put Important Instructions at the Start and End: For longer prompts, put your key instructions both at the beginning and the end. This helps the model stay on track. ➜ Guide It with Reminders: If you're designing a workflow or solving a problem, include reminders like “keep going until it’s fully resolved” or “plan carefully before acting.” This keeps the model focused. ➜ Use the Token Window Wisely: GPT-4.1 can handle a huge amount of text, but too much at once can slow it down. Be strategic about how much context you provide. ➜ Balance Internal and External Knowledge: For factual questions, tell GPT-4.1 to either “only use the provided context” or to mix that context with general knowledge. This helps you get the most accurate results. 𝗜𝗻 𝘀𝗵𝗼𝗿𝘁: 𝗧𝗵𝗲 𝗸𝗲𝘆 𝘁𝗼 𝘂𝘀𝗶𝗻𝗴 𝗚𝗣𝗧-4.1 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝗶𝘀 𝗰𝗹𝗲𝗮𝗿, 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗽𝗿𝗼𝗺𝗽𝘁𝘀 𝘁𝗵𝗮𝘁 𝗴𝘂𝗶𝗱𝗲 𝗶𝘁 𝘁𝗼𝘄𝗮𝗿𝗱 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗮𝗻𝘀𝘄𝗲𝗿. 𝗜𝘁’𝘀 𝗮𝗹𝗹 𝗮𝗯𝗼𝘂𝘁 𝗮𝘀𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘄𝗮𝘆! Access it here or download it below: https://lnkd.in/dCm6DeFW

15 years ago, I wrote "Write Better, Sell Better". The tagline that defined my career. Since then, I've written copy for Fortune 500 companies, projects that made millions, and taught copywriting at the university → Yep, writing is my life. But you don't have all semester long to learn. This post contains my 7 biggest writing lessons: (Save and repost this 60-second class ♻️) --- 1. Clarity is 90% of your writing Clarity beats cleverness 10 times out of 10. Remember: First, write clearly. Then, write creatively. Most focus on "creative" right off the bat = big no. (If you can do both, jackpot) --- 2. Use signposting to showcase authority I teach this technique to every single client. (This sentence you just read was a signpost) Signposts are short "signals" to your expertise and results. Think of them as signs on the side of the road, which allow you to "trust" the journey you're on. Can you notice where else I used it in this post? 😉 --- 3. Too much copy? Make it choppy. Here are 2 examples (the second one is better): Sometimes, we write super long sentences that we have no time to breathe and neither do our readers. Sometimes, we write super long sentences. We have no time to breathe. And neither do our readers. Chop it up! It's easier to read. --- 4. Write unselfishly. Edit relentlessly. Think about it. Writing is 80% editing. You are tweaking, optimizing, and making things sound perfect. One bit of advice: Don't hold back. Edit (ehm, delete) anything that isn't on-topic. I've deleted probably 40% of this post. --- 5. Use sensory words. Add texture to text. That had to hurt! → That had to "sting"! Having a bad day? → Having a "rough" day? A seamless process → A "silky-smooth" process All of the 2nd descriptions above can be "felt". It's how your readers "touch an emotion", not just "read text". --- 6. Never write to "everyone" Remember this for all time: "Everyone" is not your audience. Sales happen when your prospect can clearly "see" themselves in your writing. So how do you go about this? --- 7. The "Dear son" writing method Pick "one" person to speak to → I speak to my son. For you, it could be your best friend, the old you etc. I start everything with "Dear son" and end with "Love, Dad". In the end, I simply delete these 2 parts. Doing so creates such a powerful connection with your readers + a consistent tone of voice. With every word. Where there's connection, there's trust. And where there's trust, there's sales. Words to live by. --- Write Better, Sell Better = that's the whole game! Let me know which lesson you enjoy the most. Professor Jay, out. (Repost this for your network ♻️)

If you’re in PR and not paying attention to what AI is doing to search and news, you’re in for a rude awakening. AI-powered search isn’t just “tweaking the game”— it’s in the process of rewriting the rules. From how publishers decide whether to allow AI to crawl their content, to how your clients or company get discovered, this shift will change the way PR pros operate in 2025 and beyond. AI-powered search will reshape how companies and clients get visibility—and PR pros need to adapt quickly. Here’s what’s happening, why it matters, and how you can stay ahead: 1️⃣AI Search Engines Are the New Gatekeepers: Tools like Google’s Gemini and OpenAI’s SearchGPT prioritize aggregated content from trusted publications over individual websites. Your beautifully optimized website? Irrelevant if AI search decides it’s not worth surfacing. 2️⃣Publishers Deciding If They’re In or Out Big outlets like The New York Times and Wired are currently opting out of AI crawlers to protect their IP, while others allow it for traffic. This means PR pros need to strategically target outlets that feed AI models—because your story only gets told on the likes of SearchGPT if the outlet carrying it is in the AI ecosystem. 3️⃣PR Is Even More Crucial for the ‘New’ SEO: Placement in trusted media is no longer just about audience reach; it’s about ensuring AI search engines authentically and accurately pick up your client or company’s narrative. Strong media relationships will be the difference between AI surfacing your story—or perhaps leaving your brand out of the conversation, or even worse, misconstruing it. 4️⃣Crises Are on a New And Faster Clock: AI prioritizes recency and credibility, so your crisis response needs to be swift, transparent, and authoritative. A slow or ineffective reaction could leave misinformation embedded in AI models, compounding damage to your brand’s reputation. 5️⃣ What PR Pros Need to Do Right Now: Focus more on media outlets that AI trusts: Build deeper and non transactional relationships with publications and reporters already working with AI search to ensure your stories are seen. Closely Monitor AI trends: Stay ahead of updates in tools like Gemini, SearchGPT, and Perplexity so you can adjust strategies as more info emerges. Be proactive with publishers: Understand which outlets are allowing AI crawling and how that impacts your clients’ visibility. This is going to change rapidly in the coming months. The bottom line: AI search isn’t just changing how people find information—it’s going to force PR practitioners to immediately rethink how we interact with media, manage crises, and position brands for discovery. This is an underrated but important trend that will accelerate in 2025 and beyond. Anything I’m missing here? Please put in comments.

AI Product Management AI Product Management is evolving rapidly. The growth of generative AI and AI-based developer tools has created numerous opportunities to build AI applications. This is making it possible to build new kinds of things, which in turn is driving shifts in best practices in product management — the discipline of defining what to build to serve users — because what is possible to build has shifted. In this post, I’ll share some best practices I have noticed. Use concrete examples to specify AI products. Starting with a concrete idea helps teams gain speed. If a product manager (PM) proposes to build “a chatbot to answer banking inquiries that relate to user accounts,” this is a vague specification that leaves much to the imagination. For instance, should the chatbot answer questions only about account balances or also about interest rates, processes for initiating a wire transfer, and so on? But if the PM writes out a number (say, between 10 and 50) of concrete examples of conversations they’d like a chatbot to execute, the scope of their proposal becomes much clearer. Just as a machine learning algorithm needs training examples to learn from, an AI product development team needs concrete examples of what we want an AI system to do. In other words, the data is your PRD (product requirements document)! In a similar vein, if someone requests “a vision system to detect pedestrians outside our store,” it’s hard for a developer to understand the boundary conditions. Is the system expected to work at night? What is the range of permissible camera angles? Is it expected to detect pedestrians who appear in the image even though they’re 100m away? But if the PM collects a handful of pictures and annotates them with the desired output, the meaning of “detect pedestrians” becomes concrete. An engineer can assess if the specification is technically feasible and if so, build toward it. Initially, the data might be obtained via a one-off, scrappy process, such as the PM walking around taking pictures and annotating them. Eventually, the data mix will shift to real-word data collected by a system running in production. Using examples (such as inputs and desired outputs) to specify a product has been helpful for many years, but the explosion of possible AI applications is creating a need for more product managers to learn this practice. Assess technical feasibility of LLM-based applications by prompting. When a PM scopes out a potential AI application, whether the application can actually be built — that is, its technical feasibility — is a key criterion in deciding what to do next. For many ideas for LLM-based applications, it’s increasingly possible for a PM, who might not be a software engineer, to try prompting — or write just small amounts of code — to get an initial sense of feasibility. [Reached length limit. Full text: https://lnkd.in/gYY-hvHh ]

One of the good coding practices that I picked up while working at Google is about writing helpful error messages. Instead of simply stating the error, almost always, the error message also contains steps to resolve it, links to refer to, a quick shortcut to post questions to the internal question-answering platform, or at least the direction to look into. This practice can be seen across all Google Products. Try integrating with YouTube APIs, and you will see errors that are not only verbose but helpful. This can also be seen for all GCP interactions, be it web console or CLI, where the error message contains a link to a document on how to fix the issue. I have personally started using this practice every time I write code. #AsliEngineering

The One Prompt To Make ChatGPT Write Naturally: (save it for later, to copy & paste) Prompt: "Act like a professional content writer and communication strategist. Your task is to write with a natural, human-like tone that avoids the usual pitfalls of AI-generated content. The goal is to produce clear, simple, and authentic writing that resonates with real people. Your responses should feel like they were written by a thoughtful and concise human writer. You are writing the following: [INSERT YOUR TOPIC OR REQUEST HERE] Follow these detailed step-by-step guidelines: Step 1: Use plain and simple language. Avoid long or complex sentences. Opt for short, clear statements.  - Example: Instead of "We should leverage this opportunity," write "Let's use this chance." Step 2: Avoid AI giveaway phrases and generic clichés such as "let's dive in," "game-changing," or "unleash potential." Replace them with straightforward language.  - Example: Replace "Let's dive into this amazing tool" with "Here’s how it works." Step 3: Be direct and concise. Eliminate filler words and unnecessary phrases. Focus on getting to the point.  - Example: Say "We should meet tomorrow," instead of "I think it would be best if we could possibly try to meet." Step 4: Maintain a natural tone. Write like you speak. It’s okay to start sentences with “and” or “but.” Make it feel conversational, not robotic.  - Example: “And that’s why it matters.” Step 5: Avoid marketing buzzwords, hype, and overpromises. Use neutral, honest descriptions.  - Avoid: "This revolutionary app will change your life."   - Use instead: "This app can help you stay organized." Step 6: Keep it real. Be honest. Don’t try to fake friendliness or exaggerate.  - Example: “I don’t think that’s the best idea.” Step 7: Simplify grammar. Don’t worry about perfect grammar if it disrupts natural flow. Casual expressions are okay.  - Example: “i guess we can try that.” Step 8: Remove fluff. Avoid using unnecessary adjectives or adverbs. Stick to the facts or your core message.  - Example: Say “We finished the task,” not “We quickly and efficiently completed the important task.” Step 9: Focus on clarity. Your message should be easy to read and understand without ambiguity.  - Example: “Please send the file by Monday.” Follow this structure rigorously. Your final writing should feel honest, grounded, and like it was written by a clear-thinking, real person. Take a deep breath and work on this step-by-step." ___ PS: For better results, always use ChatGPT-o3.

"Vibe Coding !== Low Quality Work: a guide to responsible AI-assisted dev" ✍️ My latest free article: https://lnkd.in/gjMdjMWV The allure of "vibe coding" – using AI to "move faster and break even more things" – is strong. AI-assisted development is undeniably transformative, lowering barriers and boosting productivity. But speed without quality is a dangerous trap. Relying uncritically on AI-generated code can lead to brittle "house of cards" systems, amplify tech debt exponentially, and introduce subtle security flaws. Volume ≠ Quality. A helpful mental model I discuss (excellently illustrated by Forrest Brazeal) is treating AI like a "very eager junior developer." It needs guidance, review, and refinement from experienced hands. You wouldn't let a junior ship unreviewed code, right? So how do we harness AI's power responsibly? I've outlined a field guide with practical rules: ✅ Always review: Treat AI output like a PR from a new hire. ✅ Refactor & test: Inject engineering wisdom – clean up, handle edge cases, test thoroughly. ✅ Maintain standards: Ensure AI code meets your team's style, architecture, and quality bar. ✅ Human-led design: Use AI for implementation grunt work, not fundamental architecture decisions. The goal isn't to reject vibe coding, but to integrate it with discipline. Let's use AI to augment our craft, pairing machine speed with human judgment. #softwareengineering #programming #ai

Selling to leadership is tough. Learn to speak finance, and everything changes. (This works for both B2B sales and internal pitches.) Speak the language of financial metrics and business impact, and you’ll earn buy-in. Whether you’re pitching a product, service, or internal idea, this skill makes you a trusted partner to decision-makers. Want to dive deeper? Download my free guide “10 Levels of Profitability” here: https://bit.ly/40pY3CQ Here’s why: Executives don’t want fluff. They need to know *how* your solution or proposal will impact their business financially. Here’s how to make your pitch resonate: 1️⃣ Talk Margins, Not Just Savings ↳ Show how your solution improves gross, operating, or net profit margins. Make it clear how it improves topline or streamlines processes to ultimately add value to the bottom line. 2️⃣ Connect to Cash Flow ↳ Highlight how your solution will boost cash flow, not just the bottom-line. Smart executives prioritize cash flow over simple revenue increases or cost savings because it keeps the business stable and flexible. 3️⃣ Show ROI and Payback Period ↳ Present clear numbers on return on investment (ROI) and how quickly they’ll see a payback. Executives need to know when their investment will yield results. 4️⃣ Impact Key Financial Ratios ↳ Explain how your proposal enhances key metrics like ROE (Return on Equity), ROA (Return on Assets), or EBITDA. This demonstrates that you understand their financial framework and how your solution strengthens it. 5️⃣ Talk Risk Management ↳ Show that you’ve considered potential downsides. Demonstrate how your proposal mitigates financial risk and supports long-term stability—not just quick gains. Why this matters: 1️⃣ You Stand Out ↳ Most sales pitches and internal proposals focus on benefits. When you speak in terms of financial strategy and impact, you differentiate yourself. 2️⃣ You Build Trust ↳ Speaking their language shows you understand their challenges, priorities, and goals. 3️⃣ You Become Indispensable ↳ When you can prove your solution impacts key business metrics, you shift from being just another vendor or team member to a trusted advisor. If you want to learn finance strategy to elevate your pitch and proposals, join 3,000 learning with me here: https://bit.ly/famcol Remember: Learn to speak finance, and you’ll open doors that most can’t. ♻️ 𝐋𝐢𝐤𝐞, 𝐂𝐨𝐦𝐦𝐞𝐧𝐭, 𝐑𝐞𝐩𝐨𝐬𝐭 to help someone else. And follow Oana Labes, MBA, CPA for more