The Hidden Advantage of Being Over 50 in the Age of AI

I’ve been through a few technology revolutions. I built my first website in 1995, back when the internet made that screeching dial-up sound and nobody really knew what we were building, just that something big was happening. I watched the dot‑com bubble inflate and implode, watched social media go from novelty to addiction, and saw smartphones quietly rewire how humans behave. And now, here we are again: AI. Everywhere you look, someone is launching an AI startup, automating departments, or building agents that promise to replace entire job functions. If you’re an experienced founder or executive—especially north of 50—it’s easy to feel like you showed up late to the party. I’ve felt it myself. A few months ago, I was sitting in front of my computer watching younger founders crank out AI apps in days, shipping products before I’d even finished reading about the tools they were using. I remember thinking, “Am I becoming the guy who missed it?” That thought lasted about a week. Once I stopped comparing velocity and started actually using AI in my own work, something clicked. This might be the first tech wave where experience is the real unfair advantage. AI isn’t about being technical. It’s about thinking clearly Previous tech revolutions rewarded people who could code, manipulate algorithms, or master new platforms faster than everyone else, but AI is different. You don’t need to learn a programming language; you need to ask better questions. And asking better questions isn’t a technical skill—it’s a judgment skill. The leverage in AI doesn’t come from typing prompts quickly; it comes from knowing what matters, what doesn’t, and what consequences might follow. That’s pattern recognition, and pattern recognition is built over decades. It’s something AI is really good at, and it turns out those with experience are as well. Speed is overrated. Judgment isn’t Younger founders are moving fast right now, and I respect that. It’s exciting to watch. But speed without context creates a whole lot of noise, while experience creates context. When I use AI, I’m not asking it to build me a novelty app; I’m asking it to stress‑test a business idea, identify blind spots in a launch plan, challenge my assumptions, and help me flesh out existing models. I don’t accept what it gives me—I argue with it, refine it, and push it. That’s not something you learn from YouTube tutorials. That’s something you learn from making expensive mistakes. The real danger isn’t falling behind—it’s outsourcing your thinking There’s a subtle shift happening where leaders are starting to treat AI like a strategy generator instead of a thought partner, and that’s dangerous. AI predicts patterns. It doesn’t carry fiduciary responsibility, understand internal politics, feel reputational damage, or know which risks are existential versus cosmetic. It produces possibilities. You decide. If you’ve been in business long enough, you understand that difference instinctively—and that instinct is more valuable now than ever. The confidence gap is mostly psychological I’ve talked to more than a few executives who whisper some version of the same thing: “I’m not technical,” “I feel behind,” or “My kids understand this better than I do.” That may be true at the interface level, but understanding tools isn’t the same as understanding leverage. If you know how distribution works, AI can sharpen your messaging. If you understand customer psychology, AI can help you surface objections faster. If you understand operations, AI can reveal inefficiencies you’ve been tolerating for years. You don’t need to become an AI founder—you need to become more precise. We’ve seen this movie before, but this time you’re the advantage Every tech wave follows the same emotional arc: hype, overconfidence, correction, integration. What feels different about AI isn’t the hype—we’ve seen that—it’s the accessibility. You talk to it; it talks back. That simplicity lowers the barrier dramatically, and when the barrier lowers, judgment becomes the differentiator. Not youth. Not speed. Judgment. The leaders who win this era won’t just be 22‑year‑olds building AI‑native startups. They’ll also be experienced operators who integrate AI quietly and intelligently into systems they already understand. If you’re over 50 and feeling behind, you might actually be early. Because when the tools get easier, experience becomes more powerful—not less. And this time, that experience may finally be the competitive edge. EXPERT OPINION BY JOEL COMM, AUTHOR AND SPEAKER @JOELCOMM

How to Switch From ChatGPT to Claude With Just 1 Simple Prompt

Anthropic has had a turbulent few days, but the safety-focused AI company might be having the last laugh. Following Anthropic’s standoff with the United States Department of War, President Trump’s subsequent firing of Claude from government use, and OpenAI’s surprise deal with the Pentagon, individual users are dumping ChatGPT and flocking to Claude. On Saturday, the Claude mobile app rose to the top spot on the iOS App Store, surpassing ChatGPT for the first time. At that same time, TechCrunch has reported, uninstalls of the ChatGPT mobile app jumped 295 percent compared with the previous day. But switching AI providers isn’t always a seamless experience. The more often you use an AI platform, the more it gains an understanding of you, your work, and your personal context, which is why starting over with a new AI can feel like taking a major step back. Now, Anthropic is looking to capitalize on its newfound momentum among consumers by making it easy to transfer context about yourself from rival AI providers like ChatGPT and Google Gemini to Claude. On Monday, the company announced that its Memory feature, which enables Claude to remember key information about you across conversations, is now available for non-paying Claude users. Anthropic says on its website that this allows users to transfer their personal information with a single copy-paste, although in reality, it actually takes two copy-pastes. How to transfer your context from ChatGPT to Claude On Claude.ai, navigate to the settings page and select “Capabilities” from the sidebar menu. Then, click the button labeled “start import” under a section titled “Import memory from other AI providers.” Next, you’ll see a pop-up requesting that you copy a prewritten prompt and paste it into a new chat with the AI platform you’re looking to leave behind. For example, if you’ve been using ChatGPT and want to move on, you’d enter this prompt into ChatGPT. Here’s the full prompt, courtesy of Anthropic: Export all of my stored memories and any context you’ve learned about me from past conversations. Preserve my words verbatim where possible, especially for instructions and preferences. ## Categories (output in this order): 1. **Instructions**: Rules I’ve explicitly asked you to follow going forward — tone, format, style, “always do X”, “never do Y”, and corrections to your behavior. Only include rules from stored memories, not from conversations. 2. **Identity**: Name, age, location, education, family, relationships, languages, and personal interests. 3. **Career**: Current and past roles, companies, and general skill areas. 4. **Projects**: Projects I meaningfully built or committed to. Ideally ONE entry per project. Include what it does, current status, and any key decisions. Use the project name or a short descriptor as the first words of the entry. 5. **Preferences**: Opinions, tastes, and working-style preferences that apply broadly. ## Format: Use section headers for each category. Within each category, list one entry per line, sorted by oldest date first. Format each line as: [YYYY-MM-DD] – Entry content here. If no date is known, use [unknown] instead. ## Output: – Wrap the entire export in a single code block for easy copying. – After the code block, state whether this is the complete set or if more remain. What to do with Claude after you’ve entered this prompt If you prompt a platform like ChatGPT or Gemini with this message, you’ll receive a response that details the information the platform has about you, broken down into sections like identity, career, and projects. The response should also contain instructions detailing how you like your AI models to converse with you, such as specifications for tone of voice. Once the response is done generating, you can copy it, paste it into the textbox in the Claude settings page, and click the “add to memory” button. With that, you should see a pop-up box named “manage memory.” This box contains all the personal information that Claude knows about you, and after a minute or two it will update with the new data you just transferred from the other platform. Make sure to review this context closely and edit any data that seems inaccurate or unnecessary for what you’re planning on using Claude for. And there you have it—now you’re ready to start your new journey with Claude. What will you do first? BY BEN SHERRY @BENLUCASSHERRY

AI Adoption Has Surged to 78 Percent in This 1 Industry—but There’s a Catch

One industry has gone from barely touching AI to mass adoption in just two years. AI adoption in the legal field jumped from 23 percent to 78 percent, which is faster than in finance and healthcare. Litify’s third annual State of AI in Legal Report, which surveyed hundreds of legal professionals across law firms, corporate legal departments, and plaintiff practices, found that legal professionals are now among the fastest AI adopters anywhere. But there’s a problem hiding inside that adoption number. Only 14 percent say AI is helping them reduce costs. Just 7 percent report billing more time. Legal firms rushed to buy the sports car, then kept driving it in first gear. The gap between “we use AI” and “this changed our economics” is enormous, and it’s widening even further. “At Litify, we view this as an ‘AI maturity gap,’” notes Curtis Brewer, CEO of Litify, the legal operations platform used by 55,000+ legal professionals. “A firm that relies solely on a general-purpose tool like ChatGPT is only at the first step of its maturity journey.” The Litify data reveals exactly where firms are stuck. ChatGPT dominates usage at 66 percent, followed by Microsoft Copilot (42 percent) and Google Gemini (24 percent). These are general-purpose tools—not legal-specific platforms. And while 66 percent use AI for legal research and 39 percent for summarization, only 6 percent use it for creating invoices and 5 percent for client communication. Firms are deploying AI for tasks that feel productive but don’t directly touch revenue. Why freemium tools hit a wall General-purpose AI tools work well for research and summarization. The problem isn’t that they’re bad, but that they plateau quickly. That ceiling is exactly why legal-specific platforms like Harvey—built from the ground up on legal data and trained on case law, contracts, and regulatory frameworks—have been gaining traction at major firms. Harvey now counts PwC, A&O Shearman, and half of the 100 highest-grossing law firms in the U.S. among its clients, and has raised over $1.2 billion, with reports of another $200 million round in the works at an $11 billion valuation—partly on the argument that generic AI simply wasn’t built for legal nuance​​​​​​​​​​​​​​​. “The primary limitation of these general-purpose tools is their lack of legal and business context,” Brewer says. “Legal work is defined by nuances — solicitation rules, jurisdictional requirements, compliance standards, and practice-area-specific workflows — that general models often overlook.” Then there’s the context problem. Ask ChatGPT to summarize a case, and it only sees what you feed it — not the case history or the client’s background. And since it also can’t take action after summarizing, it’s more or less a dead-end tool. “A legal-specific tool that lives alongside your data and processes can summarize the case and suggest the next best actions or additional questions to ask,” Brewer says. “As the industry raises the bar, firms that delay are doing more than just missing out on features — they are widening a performance gap that may soon become impossible to close.” The shadow IT security risk Here’s where the adoption-without-governance problem gets dangerous: Only 41 percent of firms have an AI policy, and only 45 percent say their staff receive sufficient training. But 78 percent are using AI tools. That means roughly a third of legal professionals may be using AI in what amounts to a shadow IT environment, where there’s no oversight, guardrails, or policy. “Security, security, security!” Brewer says. “Given the highly sensitive nature of legal data, business leaders should be concerned that nearly a third of their staff may be using AI in a ‘shadow’ environment without direct IT oversight.” When employees use public AI tools, they might paste in confidential client information or HIPAA-protected medical records without thinking twice. These systems have no real safeguards. One careless prompt could mean a data breach, regulatory violation, or destroyed client relationship. “When firms fail to provide proactive guidance and purpose-built tools, staff will seek their own solutions,” Brewer explains. “If AI adoption isn’t intentional and structured from the top down, firms risk losing the very efficiency gains they sought in the first place, while exposing themselves to additional risks.” What workflow integration actually looks like The difference between AI as an assistant and AI as a business driver comes down to integration. Consider billing. Asking ChatGPT to create an invoice is like using your smartphone’s calculator instead of the accounting app. Sure, it works. But you still have to manually punch in every client detail, every payment amount, and every line item. You saved five minutes on the template and spent an hour filling it in. That’s unproductive. “When AI ‘lives’ natively alongside your billing, client, and case workflows, the impact is fundamentally different,” Brewer notes. “It transforms from an assistant to a proactive business partner.” An integrated AI tool doesn’t just generate a branded invoice template with client and matter details pre-filled. It can automatically suggest missing time entries or proactively identify billing errors. That’s the difference between saving 10 minutes and changing the economics of the entire billing process. Litify’s clients who’ve embraced this level of integration are seeing dramatic operational scaling — some firms handle twice as many matters with the same staff, and the highest performers have grown headcount by up to 400 percent as they’ve expanded regionally and nationally. The four-dimension framework Brewer says firms need to move on four fronts at once. 1. Tools: You have to stop relying on ChatGPT alone, because that’s not going to get you there. You should move to legal-specific platforms that effectively integrate with your case management, billing, and client systems. 2. Readiness: Write an AI policy. Spell out which tools are approved, how to handle sensitive data, when humans must review output, and what to do when something goes wrong. Then treat training like a safety requirement, not an HR checkbox. 3. Task scope: Research and summarization are fine starting points. But firms that stay there are leaving money on the table. The next level is workflow automation — routing requests, running conflict checks, and building chronologies. Eventually, let AI assign cases, generate invoices, and handle intake. 4. Impact: Pick metrics before you spend another dollar. Cost per matter. Turnaround time. Write-off rates. Error rates. “The try-it-and-see period is ending,” Brewer says. “Leaders will expect ROI.” Ultimately, the firms pulling ahead didn’t just buy software. They rewired how legal work gets done — from intake to invoice and research to billing — with training, governance, and measurement baked in from the start. You can keep using the sports car in first gear. But eventually, someone in your market will figure out where the other gears are. BY KOLAWOLE ADEBAYO

15 Incredibly Useful Things You Didn’t Know NotebookLM Could Do

Generative AI may be both the most useful and the most mystifying tool of our modern-tech era. The problem—aside from all the endlessly documented issues around accuracy—is that generative AI generally seems to function in a DOS-like blank prompt form. The onus is squarely on you to figure out what to ask and how to put these saucy systems to use. That black-box feeling is especially apparent when you look at NotebookLM, an “AI-first notebook” launched by Google nearly two years ago. The idea behind NotebookLM is that you upload your own source materials within carefully confined notebooks, and you can then lean on Google’s Gemini AI to interact with that material in all sorts of illuminating ways. Since each notebook is limited only to whatever source materials you supply, the prevalence of those pesky hallucinations seems to be less of an issue. And since everything within your NotebookLM notebooks is kept completely private—not even used for any manner of AI model training, according to Google—you can connect it to all sorts of subjects and use it to gain a level of deep insight that was never before so easily accessible. But again, there’s the black box challenge. When you first pull up NotebookLM, it’s tough to know where to begin and how to interact with the thing in practical, approachable ways. Even as someone who writes about technology for a living and has spent more time than most mortals thinking about this service, I realized I hadn’t entirely figured out how to use it in a way that would genuinely be helpful in my day-to-day life. So I challenged myself to dig deep, get beyond all the conceptual excitement, and come up with a series of real-world use cases for NotebookLM that any regular human could both appreciate and emulate. I’ve got 15 super-specific scenarios, all tried and tested, in which the artificial intelligence answer machine could be useful for you. Follow this road map and see which path holds the most promise from your perspective. 1. Your on-demand product answer machine Up first is a possibility that’s supremely simple yet packed with productivity potential: Create a new NotebookLM notebook called “Product Manuals.” Then, every time you purchase a new appliance or device of some sort, search the web for a PDF version of its manual and add it into the notebook. If you really want to get wild, include an image of any warranty cards, too. Then, anytime you need to know anything about those products—how some part of them works, how to fix something that’s gone awry, or if and how you’re eligible for a warranty-related repair—just fire up that same NotebookLM notebook and ask, ask, ask away. 2. Your instant car support system Next, try using NotebookLM to help wrangle the most expensive gadget you own. Do a similar web search for your current vehicle’s owner manual, then drop it into its own NotebookLM notebook with the vehicle’s name as the title. Repeat for any additional vehicles you own and any new ones you purchase down the road. After recently trading in our old minivan for a hybrid Honda CR-V, my wife and I wasted far too much time flipping through the vehicle’s paper manual to try to figure out what some random button on the dashboard did. Later, after downloading a PDF of the manual from Honda’s website and then uploading it into NotebookLM, it took me all of 10 seconds to reach the same answer—simply by asking. Lesson learned. 3. An interactive car maintenance journal While we’re thinking about cars, every time you go to the mechanic, snap a photo of the service receipt and upload it into a NotebookLM notebook created specifically for that one vehicle. You can make it even more useful by uploading the same owner’s manual you found a moment ago into that notebook, too. Doing so will give you two very practical benefits: First, anytime a question comes up about what work you’ve had done on the vehicle or when a certain repair took place, you can just pull up that notebook and ask. Second, with the manual and its instructions there alongside all of your history, you can bring the two sources of info together to ask NotebookLM targeted questions that take the manufacturer’s guidance and your past services into consideration—like, for instance, when you should rotate your tires next or what other possibilities you should be thinking about at your next oil change appointment. And on a related note . . . 4. An interactive home maintenance journal Start a NotebookLM notebook for your house, then upload every invoice and estimate you get for a home repair as well as every receipt from a new appliance purchase. Whenever you next need to know when, exactly, your roof was replaced or in what year you got your current furnace—or even what brand and model it is—you’ll have a single simple place to ask and get answers. And that’s a heck of a lot easier than having an overflowing folder of assorted old papers to sift through in every such scenario. 5. Your personal company wiki Does the company you run, or maybe just work for, have more handbook-type info than any reasonably sane human could possibly ingest and remember? If so, use a dedicated NotebookLM notebook to store all of it—guides, documents, operating procedures, even lists of contacts for different departments and purposes. From that moment forward, when a question comes up about how something is supposed to work or whom you’re supposed to contact for some particular purpose, your answer will never be more than a single quick question away. 6. Your instruction-expert wizard Why limit yourself to work, maintenance, and appliances? With anything that has an instruction manual involved, dump a digital version of the document into its own NotebookLM notebook—even for board games. The next time any kind of question comes up related to those instructions, you’ve got a fast and effective way to get answers. 7. A contract deposit box Whether you’re a freelancer juggling new contracts every month, an employee signing a new agreement each year, or an employer asking dozens of workers to sign your ever-evolving documents, creating a centralized repository for all your contracts can be a real time-saver in the future. Need to remember when you last signed something with a specific person or provider? Not sure what the terms of some agreement required—or when a particular document expires? Whatever the case may be, once the info’s all in NotebookLM, you’ve always got an easy place to ask—and let the system find the answer for you. 8. Your meeting memory Provided you’re using something to record important meetings—be it a general-purpose AI-powered note-taker, a video-call-specific summarizer, or an app designed to take notes during regular audio calls—that history will be much more useful if you bring it over to a NotebookLM notebook. With such a system in place, you can simply go to NotebookLM and ask targeted questions about any of your past meetings instead of having to dig through the transcripts individually. 9. An interview inquiry station While we’re thinking about transcripts, if you conduct any kind of interviews—with job candidates, as a journalist, or for any other purpose—take each transcript and create a NotebookLM specifically for it. (Or, if you have a group of related interviews, put them all in one notebook.) Upload either the audio or the text, depending on what’s available, and then take the opportunity to ask NotebookLM questions about your conversation—be they specific (like what the person said about some particular topic) or broad (like asking NotebookLM what interesting quotes came up during the interview that you might have missed). You’ll obviously still want to refer to the full transcript at times—and to double-check the accuracy of any quote you’re actually citing anywhere—but it can be a helpful way to find something fast when you can’t remember the exact words involved or to stumble onto something you might have otherwise glossed over. 10. An intelligent feedback interpreter If your business relies on any manner of feedback to guide its operations, do yourself a favor and create a NotebookLM notebook where you can upload those results—as spreadsheets or in whatever form they take. From reviews to survey responses, you’ll then be able to ask NotebookLM to help summarize the key themes and trends, pick out recurring positive or critical responses, and even find particularly memorable quotes for potential testimonial use. 11. Your performance review reviewer For anyone managing employee performance, NotebookLM can be a major asset. Create an individual notebook for each employee and place all their performance reviews there—then, when the time comes for the next assessment, you’ll have an easy way to revisit past highlights to identify trends and provide context for comparison. 12. A financial reality checker Provided you’re comfortable with the notion, NotebookLM can turn up some really interesting insights by analyzing things like your tax returns, bank statements, and credit card statements over the years. (For what it’s worth, Google is explicit about the fact that it doesn’t in any way access, share, or use any data uploaded into NotebookLM—even for AI model training.) With that type of info in its own dedicated notebook, you can ask NotebookLM to give you an overview of your spending habits, to identify areas where you could cut back or potentially be eligible for additional tax benefits, and to surface other such pointers that you can then investigate more thoroughly on your own or with an accounting professional. 13. An audio-video reading resource Ever find yourself running into interesting-looking videos or podcasts and just not having the time or inclination to sit through them in their entirety? Make yourself a NotebookLM notebook called “Audio-Video,” then drop a link to any YouTube video or audio clip you encounter into that area. You can then ask NotebookLM for the high points—or for any specific info you’re looking to find—from any of the clips individually or even collectively. 14. An elevated reading list NotebookLM can be a fantastic way to collect links you want to read for later revisiting. With a notebook called “Reading List,” you can see the entire text of any article whose URL you add in, right then and there and in a stripped-down and simplified format—and you can ask NotebookLM for information about, or even summaries of, any or all of your saved links, too: What was that article I saved from New York a while back? Give me the most important takeaways from that Fast Company piece I saved on privacy the other day. I’m never going to catch up with everything I saved this week. Show me a summary of all the articles I added over the past seven days. You get the idea. And finally . . . 15. Your calendar companion Get a whole new level of insight into how you’re spending your time and what’s actually gone down on your calendar by exporting your complete calendar history, and then importing it into NotebookLM—where you can create a custom notebook to interact with it. In Google Calendar, this is as easy as clicking the gear-shaped icon in the desktop website’s upper-right corner, selecting “Settings,” then clicking “Import & export” in the left-of-screen side menu and clicking the “Export” option. You’ll then need to take the resulting .ics file and convert it into plain text—which you can do in a matter of seconds with a free conversion website like this one. Finally, with the resulting .txt file in a NotebookLM note, try asking questions about anything from how many meetings you attended over a given time period to how many hours you spent at the doctor’s office last year. You can also ask for specific info such as how often, on average, you get haircuts or how long it’s been since you last had a job interview. ~ google-notebooklm-calendar.jpg You might be surprised at the types of insights you uncover with your calendar data in NotebookLM’s metaphorical hands. ~ The possibilities are practically endless—and all you’ve gotta do is ask. BY FAST COMPANY