Paul Roetzer's Recent LinkedIn Posts

Every day on the drive to school, my kids and I say one thing we're grateful for. It's an amazing daily ritual if you've never tried it. In the spirit of gratitude, today I am thankful for our incredible community of podcast listeners—especially over the last week with all the Spotify Wrapped posts people have shared showing the thousands of minutes they've spent listening through the year. We started doing The Artificial Intelligence Show weekly episodes in fall 2022, right before ChatGPT launched. The growth has been incredible to see, and experience. 2022 = 4,800 downloads 2023 = 262,000 downloads 2024 = 401,000 downloads (+53%) 2025 = ~920,000 downloads (+130%) Thanks to everyone who listens each week. We appreciate every download, every rating and review, and every recommendation to a friend or co-worker. We've got big plans for the show in 2026, so we hope you keep listening. Thank you!

The intellectual property side of AI is heating up. On the same day that Meta announced real-time content partnerships for Meta AI, news broke that Perplexity is now facing lawsuits from Chicago Tribune and New York Times for stealing their content. ***Meta "As the first step in our content expansion, we’re partnering with a variety of outlets — CNN, Fox News, Fox Sports, Le Monde Group, the People Inc. portfolio of media brands, The Daily Caller, The Washington Examiner, USA TODAY and the USA TODAY Network. We’ll continue to add new partnerships and explore new features to enhance the experience for the people who use our products. "We’re committed to making Meta AI more responsive, accurate, and balanced.  Realtime events can be challenging for current AI systems to keep up with, but by integrating more and different types of news sources, our aim is to improve Meta AI’s ability to deliver timely and relevant content and information with a wide variety of viewpoints and content types." ***The New York Times "Today, The New York Times filed a lawsuit against Perplexity AI for copying Times journalism to deliver it to Perplexity’s customers without permission or compensation. "The Times has repeatedly asked Perplexity to end its unauthorized use of our content, but Perplexity continues to unlawfully use The Times’s copyrighted material." ***Chicago Tribune "The Chicago Tribune filed a lawsuit against AI search engine Perplexity on Thursday alleging copyright infringement. The suit, seen by TechCrunch, was filed in a federal court in New York. The Tribune alleges that its lawyers contacted Perplexity in mid-October asking if the AI search engine was using its content, according to the complaint. Perplexity’s lawyers replied it did not train models with the Tribune’s work but that it “may receive non-verbatim factual summaries,” the lawsuit claims. "The Tribune’s lawyers, however, argue that Perplexity is delivering Tribune content verbatim." We'll be covering all of this on Ep. 184 of The Artificial Intelligence Show next week. Links below.

AI for health is an enormous opportunity. On the consumer side, the question becomes which AI lab/company do you trust with your data for a unified personal health advisor. We talked about this on Ep. 190 in the context of ChatGPT Health, and I shared a bit about my personal experience with a health issue last year. “The healthcare system is fragmented, while health requires looking at a full picture. I deal with this all the time.…I have one doctor for orthopedic stuff. I have a doctor for heart stuff. I have a doctor for other things. It's different health systems even. “And so I don't even have unified records when I go to my general practitioner, he doesn't even get the full visibility into what's going on in my life. “So the idea of being able to have all of that unified and then have a proactive AI assistant that's watching that stuff and having access to data. “So if something triggers again on my Apple Watch that something weird is going out with the heart again. That there's a preemptive (AI assistant could) reach out and say, ‘Hey, based on what happened last year, here's probably what's going on.’ And all of that sounds amazing. “I do think that we're entering this world where we can have this, (but) are you willing to give up the data to get the benefit becomes one of the key questions. “And then when you know everyone is gonna be racing to do this, who do you trust with that data?” I think Apple has an opportunity to dominant in consumer AI health, but Google, OpenAI, and others are going to go hard after this multi-trillion market. You can imagine this same proactive AI assistant model being highly valuable in business. If you can unify all your business data, and layer in AI agents that can monitor and react based on signals, you can build a smarter, more dynamic business.

A few weeks ago I had the random idea to start doing a simple survey at the start of each podcast episode as a way to introduce real-time research into our program. We call them AI Pulse surveys. We get ~11,000 downloads of each episode in the first 7 days, and average ~115,000 downloads per month overall. So, I figured why not start exploring what our audience thinks about key topics that we talk about each week, such as AI’s impact on jobs, society, education, the economy, and business. We had no idea how many listeners would take the time to find the link in the show notes and take the survey, but we figured we’d give it shot and see what happens. The first survey was introduced during Ep. 178 on Nov. 4, and we shared the results of that survey on Ep. 179 this week. We’ve had 115 respondents thus far to the first AI Pulse, so it’s not a significant sample size, but it definitely starts to help form a better picture of how our audience feels about timely issues. The Nov. 4 AI Pulse asked two questions: 1) Which of the following statements best describes your current personal feeling about AI's impact on job security? 2) Which statement best describes your personal, day-to-day use of AI tools in your professional work? Each week will discuss the findings at the start of the episode, and share a blog post with the results. You can see the first AI Pulse survey results at the link below. Note: We do not collect email addresses as part of this survey. You may see your email address displayed when you click on the Google Form if you are logged into a Google account, but this information is not collected, and we do not market to survey participants. This is purely research. https://lnkd.in/epUuSw8z

If your company isn’t generating significant ROI from AI adoption, then you have a people problem. AI transformation and value creation certainly requires an understanding of and access to the technology. But, more importantly, a willingness of the humans within your organization to change. Change is hard. Many people see AI as a threat to their jobs, or, more deeply, a replacement to the work they find fulfilling and meaningful. Without proper AI education and training, plus a comprehensive and empathetic approach to change management, your company will fall short of its potential and open the door to competitors who are more strategic in their AI transformation plans. I read a great post from Jack Soslow, CEO of Ciridae, that sums it up well: “This is what Silicon Valley doesn't understand about AI transformation. Technology is the easy part. Finding the problem is harder. But the hardest part, the part almost nobody wants to do, is the human work of driving change. Sitting with people. Earning trust. Refining the product until it fits their hands. Pushing until adoption actually happens. “Generating $1 of EBITDA requires three things working together: (1) business acumen to find the real problem, (2) technical skill to build a solution that works, and (3) people skills to drive behavior change. These capabilities rarely exist in one person. They barely exist in most teams. “This is why transformation is so expensive.” Most leaders won’t do the hard part. You have an opportunity to differentiate and drive enormous value in 2026 by taking a human-centered approach to AI.

Re: the AI bubble talk. Yes, there are some crazy valuations (especially for early-stage AI companies), and many of these companies will flop. But, we are on the very leading edge of an intelligence explosion. AI will be everywhere, and in everything. Demand for intelligence and compute will accelerate because society will demand greater reasoning capabilities, image generation, video generation, 3D world generation, AI agents, and robotics. Plus, the models will become more reliable at long-horizon tasks (things that take humans hours/days/weeks) across industries. All of this requires far more compute than the text-based LLMs that have largely driven the last three years of growth for AI companies like NVIDIA, Google, OpenAI, Anthropic, Microsoft, and others. Most of society is still unaware of the true multimodal capabilities of today’s AI models, and certainly have almost no concept of what’s coming in the near term. Once AI awareness, understanding, and utilization reach the masses, which may take years still, we will look back and see that Wall Street and others actually undervalued the impact of AI (much like they did for years before ChatGPT emerged). Play the long game.

Never debate with someone whose only goal is to convince you of their beliefs. They’ll never listen to logic, and you’ll never find a middle ground. Always welcome debate with someone who shares a mutual goal to explore truth. If nothing else, you’ll both learn and grow. This holds true for family, friends, coworkers, peers, and social media accounts. I think about this a lot in relation to our podcast. We do our very best at all times to present and discuss information in the most objective and unbiased way possible—even when it’s related to politics and religion. We want people to hear relevant perspectives and facts, and land on their own points of view. This will be timely when we discuss the Anthropic vs government situation next week on episode 200.

In the next 3 years, we’ll likely confirm that: 1) life—or at least the building blocks of it—exists abundantly in the universe, and 2) we’ve reached artificial general intelligence (AGI) and beyond on Earth. And yet the vast majority of humans will continue on as though nothing has changed. When, in reality, everything has changed. I find that hard to wrap my mind around.

OpenAI opened the door for its competitors when it announced plans to inject ads into ChatGPT. I thought Google would seize the opportunity, but Anthropic beat them to it with a brilliant and hilarious ad series that launched today. This is the sort of ad campaign Anthropic needed to create awareness and curiosity with a broader audience that OpenAI has owned. See the Anthropic ads playlist below. They will absolutely gain market share with this approach. Side note: I would love to know how much AI was used in the creation of these ads.

I’ve been an entrepreneur and CEO for 20 years. This is the first time one of my companies has landed on the Inc. 5000. Based on 2021-2024 growth (+1,200%), we came in at 320 on the list. This is a testament to our dedicated team, our incredible community, and the perseverance—since I launched Marketing AI Institute in 2016—to stick to our belief that AI would change the world. It certainly hasn’t been an easy road. Being primarily an AI event business in 2021, at a time when the event industry was largely shut down, was less than ideal. Plus, at that time (pre-ChatGPT), most businesses were not aware of the impending disruption that would come from Gen AI, so demand for AI events and education was still in its infancy. But, will, vision, conviction, and a funding runway saw us through. In 2022, when the event industry started to return, MAICON had 200 attendees. This year we expect 1,500+. And since that time we’ve diversified the business model, restructured the organization (SmarterX is now the parent company, with Marketing AI Institute, AI Academy by SmarterX, and The Artificial Intelligence Show as the primary brands), and focused our North Star on accelerating AI literacy and transformation for all. I wouldn’t trade the journey for anything. The highs and lows. The wins and the losses. The long nights and the early mornings. The doubts. The uncertainty. The unknowns. Every part of it is what drives the business forward, and gives me the motivation to see it through. I’m grateful to have the opportunity to work with this team, serve our customers and community, and help try and create the best possible future. Thank you to everyone who’s been a part of our story so far. Much more to come! https://lnkd.in/g8cM78GT

We're running our 2026 State of AI for Business Survey and I'd love your help. Over the past five years, we’ve surveyed thousands of marketing professionals and leaders about how they use AI. But marketing teams don't adopt AI in a vacuum. Neither do sales, ops, finance, or HR. This year, we've expanded the survey beyond marketing to capture AI adoption across the full organization — because the factors that determine whether AI takes hold (training, executive buy-in, policies, data, budget) are often company-wide. The goal is to understand where AI is gaining traction, where teams are stuck, and what professionals need next. We will publish the findings this Spring as part of the 2026 State of AI for Business Report. The more responses, the better and more useful the data will be for all of us. It takes about 7 minutes, and we're looking for perspectives across functions, industries, and company sizes. If you take the survey, I'd also appreciate you sharing it with your team or network. Plus, all respondents who provide contact information (which is optional) will receive a copy of the report and be entered into a drawing for a 12-month AI Academy Mastery Membership. Current AI Mastery Members will be eligible to receive a 12-month extension. Thanks for your help in shaping this year’s report. https://lnkd.in/eYewyccV

In March 2023—two weeks before the release of GPT-4—I published The Law of Uneven AI Distribution, which stated: “The value you gain from AI, and how quickly and consistently that value is realized, is directly proportional to your understanding of, access to and acceptance of the technology.” In the post I wrote: ***** “I’ve been thinking a lot lately about the AI adoption curve, both in our personal and professional lives, and who stands to benefit most from rapid advancements in the technology. Where I’ve landed is that the impact and benefits of AI will be unevenly distributed to individuals, companies and industries. In some cases it will be by your own choice, and in others it will be by institutional design. For example: - Financial services companies blocking employees’ ChatGPT access. - Educational systems at all grade levels struggling to adapt to generative AI capabilities in curriculum. - My own unwillingness to install some super-interesting AI apps because I don’t know or trust the companies and how they’ll use my data. This uneven distribution will create dramatic differences in people’s experiences with and perceptions about AI. It will profoundly impact how much you reap the benefits of AI in your personal and professional lives, how much value your company extracts from the technology, and the trajectory of your AI journey.” ***** Here we are, three years later, and the law continues to hold true. In the last two months alone, I’ve spent time with leaders of major financial and healthcare institutions that are still blocking access to generative AI platforms in their companies, and I’ve met with school administrators at high school and college levels who are searching for answers on how to handle AI in the classroom. And, personally, I have yet to go down the path of exploring OpenClaw—an open-source AI agent that runs locally on your computer to perform real-world tasks—because of the security unknowns and risks. For companies struggling to see an ROI from AI, you have to go back to the basics: AI understanding and access. The companies that are racing forward—and realizing the benefits of AI—are prioritizing AI literacy and empowering their employees to integrate generative AI solutions into their workflows. And AI literacy has to start with leadership. In order to get the kind of support needed to drive AI adoption and impact, your leadership team has to deeply understand AI, including the full capabilities and potential of leading AI systems, such as ChatGPT, Claude, Copilot, and Gemini. From there, leadership has to share a clear vision for the future of work and how AI will impact your people and the organization. Without those steps, your AI initiatives are destined to fall short of their full potential to drive transformation. We talk a lot more about AI adoption and the potential impact on jobs in episode 201 of The Artificial Intelligence Show.

In January 2025, I announced the AI Literacy Project, an initiative designed to prepare individuals and organizations for the future of work by making AI education accessible and personalized. The Project is anchored in the belief that AI literacy is not just a competitive advantage, but a career and business imperative. Every professional has a choice to maintain the status quo or accelerate their AI literacy and capabilities. Core Principles: * We believe AI education should be accessible to all.  * We believe AI education will be the foundation for success in every organization. * We believe in a human-centered approach to AI that empowers and augments people.  * We believe in the value of human knowledge, experience, emotion, imagination, and creativity.  * We believe in the potential of AI to have profound benefits for humanity and society. * We believe in an open approach to sharing our AI research, knowledge, ideas, experiences, and processes. * We believe in the importance of upskilling and reskilling professionals, and using AI to build more fulfilling careers and lives. * We believe in the potential to reimagine business models, reinvent industries and careers, and rethink what's possible. * We believe in the redistribution of talent to drive growth and innovation, rather than the displacement of jobs to maximize profits from AI-powered efficiency gains. * We believe in partnering with organizations and people who share our principles. Over the last 12 months, our team has brought the vision to life through: * Monthly AI Classes: Intro to AI and 5 Steps to Scaling AI are offered live each month. More than 50,000 professionals have registered for these classes since November 2021.  * The Artificial Intelligence Show Podcast: Our weekly podcast keeps listeners up-to-date on AI news and trends. We released 60+ episodes this year, reaching nearly 1M downloads. * AI Community: A Slack community of more than 10,000 AI-forward professionals. * AI Blueprints: A collection of resources that make AI approachable for workers across industries, departments, business types, and careers. * AI Summits: AI for Writers Summit and AI for B2B Marketers Summit have free virtual registration options and attracted 8,000+ attendees in 2025.   * AI Tools: SmarterX provides a series of custom GPTs—JobsGPT, CampaignsGPT, ProblemsGPT, InnovationsGPT, Co-CEO—to drive efficiency and growth, while preparing businesses for the future of work. In addition, we reimagined and launched AI Academy by SmarterX 3.0 to accelerate personal and business AI transformation. Our new AI-powered learning platform features 9 professional certificate course series, plus 20 Gen AI App Reviews, with more content and certificates being added every week. I’m so grateful for our team who makes it possible, and for our community who trusts us to be a part of their AI journey. Lots more to come in 2026!

Podcasts are one of the primary ways I stay updated on the latest in AI, specifically how AI leaders are thinking about the current and future state of industry. I get asked all the time which podcasts I listen to, so I thought I’d share the list (in no particular order): - The Cognitive Revolution - The 80,000 Hours Podcast - 20 VC - BG2 Pod - Big Technology Podcast - Dwarkesh Podcast - Lenny’s Podcast - No Priors - The OpenAI Podcast - The Mad Podcast - Hard Fork - The a16z Podcast - Google AI Release Notes - The Logan Bartlett Show - Y Combinator Startup Podcast - Lex Fridman Podcast - Google DeepMind: The Podcast - Uncapped These are all podcasts that I subscribe to. Each week I scan the latest episodes and then save the ones that are relevant. I probably listen to 5-7 episodes per week. Do you have any favorites that I’m missing?

AI as an Analyst, Advisor, and App Builder Mike and I have been making an effort on the podcast to share more stories about how we’re using AI to build and run SmarterX. Hopefully the examples we share give you some ideas and inspiration to apply AI in new ways to your business and career. Here’s a snapshot of some of the ways I used AI this week: 1) P&L Report Summary On Thursday, our COO shared a screenshot with the team of revenue by line item in the P&L (Jan. 1-15 vs same period YoY). It was meant to  give a quick look at how we’re starting off the year. I took the screenshot and dropped it into Gemini and my ChatGPT Co-CEO as an experiment. Prompt: “Analyze this and write a summary I can share with the team. Focus on insights and opportunities.” Considering how little context I provided, both Gemini and ChatGPT showed tremendous potential to produce financial reports. We’re working on tighter integration of AI into all our company reporting so that the team can more quickly turn data into intelligence, intelligence into actions, and actions into outcomes. 2) Travel Advisor I had a talk in Chicago on Friday morning. My plan was to drive there from Cleveland on Thursday after my Intro to AI webinar. On Wednesday night, the winter weather took a turn, and I started second guessing my drive-vs-fly decision. So, I went into Gemini: Prompt: “I’m heading from Cleveland to Chicago tomorrow. My plan was to drive because I like the quiet time and ability to conduct phone calls. However, the weather and roads don’t look great. Can you review the forecast and consider my options of driving versus flying.” Gemini came back with a very clear recommendation: Don’t drive! “A typical 5.5-hour drive is likely to become an 8 to 10-hour crawl. If your schedule allows the expense, flying is the significantly safer and more reliable option tomorrow.” Gemini then searched flight options and I made the switch to a direct flight later on Thursday. 3) Org Chart App This is probably the one I was most geeked about this week. I’ve been searching off-and-on for years to find software that would enable me to build and visualize dynamic organizational charts. I’ve tried a number of tools, and always been disappointed by the lack of functionality. So, I went into Lovable and started a new project with this prompt: Prompt: “I need to build an interactive org chart that enables me to envision multiple versions of potential organizational structure” Lovable took me through a series of questions about the design and functionality (using its reasoning capabilities), and within 10 minutes I had a working minimum viable product (MVP) that I am now using to plan for our staffing and structure. As someone with zero coding ability, I was able to build and refine a working app better than anything I’d ever tested. Let that sink in. With AI, you can just build things. The future of work has arrived. It’s just not evenly distributed

We held a launch event today for thousands of AI Academy by SmarterX learners to introduce a new, AI-powered learning experience. We’ve been working on designing and building the new learning management system (LMS) for the last year. It has been an enormous lift that was made possible by our incredible SmarterX team and a number of outside partners who lent their technical expertise to bring it to life. For our learners, the new LMS provides a more personalized, intelligent, and engaging experience than the legacy LMS. It features an AI learning assistant, a course recommendation engine, professional certificates, badges, skills management, custom course playlists, and learning journeys. Plus, access to all our on-demand courses and series, AI Academy Live classes, and Gen AI App reviews. For our business account team leads, the new LMS offers a massive upgrade in course and user management, personalization features, gamification, and reporting capabilities. All existing learners and business account team leaders have immediate access to the new LMS, and will continue to have access to the legacy LMS for three months to complete any active certificate course series. All new AI Academy customers will go directly into the new LMS. More details in the link below, including how to access accounts for existing customers. And you can check out a preview of the LMS in the attached PDF.

Google Workspace Studio is the AI application I've been waiting for since ChatGPT emerged in 2022. AI agents integrated directly into the productivity platform we use to run our business (Google Workspace). Google announced the rollout of Workspace Studio was starting this week. I went in to test it this morning and you can immediately see the potential impact it will have on efficiency and productivity across teams and organizations. You can easily build AI agents to assist with tasks, and, in many cases, complete activities you otherwise wouldn't have time to do (i.e. it's additive and amplifies your capabilities while creating more time). It's extremely intuitive, and easy to get started. The only problem is, it doesn't work. Every agent I tried, I got the same error message: "We are at capacity, we'll be back soon." Guess I'll have to wait a little bit longer for my dream AI app to become reality.

There was a lot of Anthropic Claude/AGI buzz during the holiday break in AI circles on X, making it the lead topic for Ep. 189 of The Artificial Intelligence Show. Here’s a sample: Igor Babuschkin (xAI founder, former DeepMind and OpenAI): “Opus 4.5 is pretty good” Andrej Karpathy (OpenAI co-founder): “It’s very good. People who aren’t keeping up even over the last 30 days already have a deprecated world view on this topic.” Jackson Kernion (Anthropic researcher): “I'm trying to figure out what to care about next. I joined Anthropic 4+ years ago, motivated by the dream of building AGI. I was convinced from studying philosophy of mind that we're approaching sufficient scale and that anything that can be learned can be learned in an RL env. And so now I feel like Opus 4.5 is as much AGI as I ever hoped for, and I'm not sure I know what I want to spend my waking hours focused on.” Jaana Dogan (Principle Engineer, Google): “I'm not joking and this isn't funny. We have been trying to build distributed agent orchestrators at Google since last year. There are various options, not everyone is aligned... I gave Claude Code a description of the problem, it generated what we built last year in an hour.” Rohan Anil (former Google engineer): “I used to be a google engineer too, leveled up all the way, and feel if I had agentic coding and particularly opus, I would have saved myself first 6 years of my work compressed into few months.” David Holz (founder, Midjourney): “ive done more personal coding projects over christmas break than i have in the last 10 years. its crazy. i can sense the limitations, but i *know* nothing is going to be the same anymore.” Igo Babuschkin: “There are decades where nothing happens, and there are weeks where decades happen” Elon Musk: “We have entered the Singularity” Don’t miss this episode. The first 30 minutes may alter your view of where we are in AI development, and how quickly knowledge work is changing. 00:00:00 — Intro 00:04:14 — AI Pulse 00:05:41 — How Close Are We to AGI? 00:31:48 — AI Change Management 00:38:18 — OpenAI Is Hiring a “Head of Preparedness” 00:41:59 — Khan Academy Creator Calls for Job Displacement Fund 00:47:30 — Jevons Paradox in AI 00:55:20 — The Rise of Vibe Revenue 00:57:57 — Salesforce Says Trust in LLMs Is Declining 01:03:25 — Nvidia Does Landmark Deal with Groq 01:06:21 — Meta Acquires Manus 01:08:34 — Yann LeCun Speaks Out 01:14:14 — OpenAI Preps for Largely Audio-Based AI Device 01:17:39— AI Predictions for 2026 01:20:35 — OpenAI Prompt Packs for ChatGPT

AI Trends to Watch in 2026 (Part 2) . . . For Ep 188 of The Artificial Intelligence Show, which drops on Dec. 23, I put together a list of some of the key trends we’re watching as we head into the new year. These aren’t meant to be predictions. They are more observations on AI topics that we think will play important roles in AI progress, adoption, and integration over the next 12 months. I focused on three areas: Technology, Business, and Society. For today’s post, I’ll share the AI Business trends. 1) Agent-to-agent communications and commerce: Businesses must solve for consumers using agents to gather information, engage with brands, and make purchases. This may alter how we design user experiences on the web and in apps, and it could rapidly evolve marketing, sales, and customer experience strategies. 2) More organizations move from the Piloting AI phase to the Scaling AI phase: An increasing number of businesses are entering the Scaling AI phase, which is characterized by AI being infused into every aspect of the organization (marketing, sales, service, operations, product, HR, finance, legal) to create competitive advantages, accelerate growth, and drive innovation. 3) Adoption of reasoning models and capabilities: Reasoning gives AI models the abilities to build plans, think logically, analyze situations, evaluate evidence, and solve problems. As more professionals understand and apply these capabilities, the future of work will begin to transform more rapidly. 4) Investments in AI literacy: Organizations are recognizing that AI tech alone does not lead to transformation. Massive investments are being made into education and training programs to drive AI literacy. We define AI literacy as, “the knowledge, skills, behaviors, and mindset needed to drive human-centered AI transformation.” 5) Shift from AI-driven optimization to AI-driven innovation: While initial AI adoption in organizations has focused on cutting costs and streamlining existing processes, the next wave is about creation of value. Optimization is using AI to do the same things better, faster, or cheaper. Innovation is using AI to do new things that create new forms of value for customers and the organization. Optimization is 10% thinking. Innovation is 10x thinking. 6) Custom evals tied to economically valuable work: Standard AI model eval benchmarks are no longer sufficient for the enterprise. Businesses will increasingly build custom evaluation frameworks that measure an AI’s performance against specific business KPIs, tasks, and workflows rather than academic IQ tests. 7) AI becomes a default layer in every software workflow: AI is shifting from a standalone tool to a capability layer embedded across the business software stack. AI models are being infused into marketing solutions, CRMs, ERPs, analytics, HR systems, and service platforms. I'll post AI Society trends on Tuesday, along with the link to the episode.

ChatGPT launched three years ago today. Even though OpenAI leaders were unsure how the public would react to it, Sam Altman foretold the impact it would have in his announcement Tweet that day. "soon you will be able to have helpful assistants that talk to you, answer questions, and give advice. later you can have something that goes off and does tasks for you. eventually you can have something that goes off and discovers new knowledge for you." Here's what I wrote on Dec. 2, 2022 when I first tested ChatGPT: "I just tested ChatGPT from OpenAI. My immediate reaction after five minutes is that the marketing profession, business world and society are not even close to ready for what is about to happen as a result of rapid advancements in artificial intelligence. "Everything we think we know about communications, creativity and strategy is going to be redefined and reimagined in the months (and years) ahead. The closest comparison I can find in my mind to understand the magnitude of the moment would be to rewind to June 2007 when the iPhone was introduced. "What is about to be built in the generative AI space is basically the equivalent of the emergence of the app ecosystem, which Apple says facilitated $643 billion in billings and sales worldwide in 2020. "With generative AI, we're talking about trillions of dollars in value and wealth creation over the next decade. And the barriers to entry (e.g. access to the tech, technical skills required to use AI, compute power, energy costs) are rapidly falling. "Comprehension of what AI is and what it is capable of doing is critical for companies to get this right. We need more industry leaders experimenting and sharing, but we also need more leaders who fully grasp the power and potential of AI to be use for good, and for evil. "This stuff is going to move very fast, and the business world is not even close to prepared for what's to come in 2023." These thoughts ring true today. Three years later, I still don't think the business world is prepared for what's to come.

In normal week, I add about 30 topics to our Artificial Intelligence Show sandbox. Mike then curates the list into 3 main topics and 7-10 rapid fire items. This week’s sandbox sits at 52 items and counting. I went through them this morning to write my weekly ExecAI Insider newsletter and I’m honestly not sure what to cut this week. Every topic feels important and worthy of discussion. Here’s a sample of what we’re tracking: - Sulaiman Ghori, a member of the technical staff at xAI, was fired after disclosing a bunch of insider information on a podcast about Elon Musk’s AI lab, including that the company has been developing AI employees that act like humans, known as “human emulators.” - Dario Amodei and Demis Hassabis took the stage together at the World Economic Forum in Davos to talk AGI timelines, self-improving AI models, AI risks, jobs, and the economy. - NeurIPS, a leading AI conferences, accepted research papers with 100+ AI-hallucinated citations, according to research from GPTZero. - Anthropic released Claude’s new Constitution. “Claude’s constitution is the foundational document that both expresses and shapes who Claude is. It contains detailed explanations of the values we would like Claude to embody and the reasons why. - Lemonade unveils autonomous car insurance, cutting rates for Tesla Full Self Driving (FSD) miles by 50% - Google partnered with The Princeton Review to bring full-length, no-cost practice SATs directly to users in the Gemini app. - Apple is rumored to be developing a wearable pin (in addition to more details about the next-gen Siri). - Google acqui-hires AI voice startup Hume AI. - Google DeepMind is hiring a Chief AI Economist. “As a Chief AGI Economist at Google DeepMind (GDM), you will be at the forefront of understanding the profound economic transformations that will accompany the arrival of Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI).” - Amazon plans thousands of job cuts next week. - Altman warns that OpenAI’s upcoming model releases are pushing the limits of risk and security. “We are going to reach the Cybersecurity High level on our preparedness framework soon.” And that’s just a sample. Going to be a full episode 193.

Ship a new Gen AI App Review every Friday. That was a key part of the vision for our reimagined AI Academy by SmarterX when it launched late last year. With AI tech moving so fast, we wanted to help our AI Mastery members cut through the noise with short (15-20 minute) on-demand courses highlighting the latest AI tools and features across four categories: Audio, Images, Productivity, and Video (plus Agents coming soon). Our goal was to give enough information (What is it? How does it work? Who is it for? What are the use cases? How is it priced?) for members to decide if it’s worth their time to explore the tech for themselves. The AI Academy team (mostly Mike and Claire) have been crushing this series, publishing 26 videos since August 2025 (including Claude Projects today): Gen AI Audio App Series - ElevenLabs (1/9/26) - Udio (11/28/25) - Suno (10/31/25) Gen AI Image App Series - Adobe Suite - Photoshop (12/26/25) - Midjourney (12/5/25) - Nano Banana Pro (11/26/25) - OpenAI 4o Image Generation (10/24/25) - Google Imagen 4 (9/26/25) - Gemini 2.5 Flash Image "Nano Banana" (9/5/25) Gen AI Productivity App Series - Claude Projects (2/6/2026) - Deep Research w/ NotebookLM (1/30/26) - ChatGPT Memory & Personalization (1/23/2026) - GPT-5.2 (12/19/25) - Wispr Flow (12/12/25) - OpenAI Custom GPTs (9/19/25) - OpenAI ChatGPT Deep Research (9/12/25) - Google NotebookLM (8/29/25) - Google Gemini Deep Research (8/22/25) Gen AI Video App Series - Higgsfield AI (1/16/26) - Adobe Suite - Premiere (1/2/26) - Runway (12/19/25) - Descript (11/14/25) - Pika (11/7/25) - Sora 2 (10/17/25) - HeyGen (10/10/25) - Google Veo 3 (10/3/25) If you’re an AI Mastery Member, be sure to take advantage of these weekly videos to stay up on the latest tech and trends. https://lnkd.in/gJNxyTbj

As AI continues to improve across all areas of creative and strategic work, the question many professionals will face is, “when should I let AI do the work, and when should I do it myself?” It’s becoming less about the technical ability of AI to assist in or perform tasks, and more about the meaning of the work. Writing is a great example. On Ep. 203 of The Artificial Intelligence Show, we talked about a controversial New York Times article—Who’s a Better Writer: A.I. or Humans?—that has readers take an AI Writing Quality quiz in which they choose between two passages. One written by AI, and one by a human. More than 86,000 people took the quiz. The punchline is that in this specific test, humans preferred AI-written passages more often: 54% of readers said they preferred the AI-written passages over the human originals. On the identification question, readers struggled to consistently tell the difference. I assume that for most people it will become increasingly difficult to tell human vs AI writing, especially when the AI is trained to write in a specific writer's style and tone. But, just because AI can write, doesn’t mean it always should. For me, writing is thinking. It’s how I process information, comprehend concepts, build competency, and pursue mastery of topics. I write for myself—to learn, understand, and grow. And I write for audiences—to educate, entertain, and inspire. So, there are absolutely use cases (like LinkedIn posts, my podcast commentary, and my personal ExecAI newsletter) when I want the writing to be 100% authentic and personal. I want to create a connection with the audience and share unique perspectives and opinions. I have no use for AI in these instances, no matter how much time it would save. The process is the purpose. Other times, the writing is more fact-based and objective. I may be trying to simplify complex topics that require more research and nuance, but the audience still expects the content to be in my voice, and have a personal touch. In these cases, AI may assist with research, brainstorming, outlining, and refining. My point is that the decision of when and how to use AI in your writing (or whatever your work is) isn’t binary. It exists on a spectrum, and it is a subjective and personal choice. Lots more discussion on Ep. 203. 00:00:00 — Intro 00:03:11 — AI Pulse Survey Results 00:07:48 — Anthropic vs. Pentagon Round 3 00:30:02 — New York Times Releases Controversial "AI Writing Quality" Quiz 00:46:18 — Atlassian Layoffs and Job Loss Dashboard 00:58:49 — Adobe CEO Stepping Down 01:07:14 — Amazon AI-Related Outages and Engineering Struggles 01:14:28 — McKinsey AI Chatbot Hacked 01:19:49 — AI Politics Update 01:24:06 — Grammarly AI "Expert Review" Controversy 01:30:51 — Andrej Karpathy's Autoresearch Agent 01:34:47 — AI Product and Funding Updates https://lnkd.in/g25zmyti

We recorded episode 200 of The Artificial Intelligence Show this morning with a live audience for the first time. The episode drops tomorrow with a huge conversation upfront about Anthropic vs the US government. Thanks to all our AI Academy Mastery Members who were able to join us today live, and thanks to all of our listeners who have made the show the highlight of our professional lives each week. And special thanks to Claire Prudhomme on our team who produces the podcast each week, and put together an incredible video with highlights over the last 3+ years. Baby AI versions of me and Mike even make an appearance. :) 200 episodes in 200 seconds video link in the comments.

We're hiring for three critical customer success roles at SmarterX. If you, or someone you know, is a potential fit, please consider applying on our Careers page. ***VP of Customer Success, AI Academy*** The Vice President of Customer Success, AI Academy is the senior leader responsible for the end-to-end customer experience for all AI Academy customers, including individual learners, Standard Business Accounts (5-99 licenses), and Premium / Enterprise Business Accounts (100+ licenses and high-growth potential). The VP of Customer Success is charged with building an industry-leading, AI-forward department that drives customer transformation and can help us scale to 250,000+ licenses in the next 3-5 years. ***Senior Customer Success Manager, Enterprise Accounts*** The Senior Customer Success Manager (SCSM), Enterprise Accounts is responsible for the success, growth, and retention of AI Academy’s premium and enterprise customers. These accounts typically include 100+ licenses or high-growth potential, and each SCSM manages a portfolio of $2–$3M in ARR. This role is far more than traditional customer success. SCSMs function as AI Transformation Consultants, acting as the primary point of contact and customer champion. You will guide organizations through onboarding, adoption, enablement, expansion, and renewal—ensuring measurable impact from their AI Academy investment. ***Customer Success Manager, Standard Accounts*** The Customer Success Manager (CSM), Standard Accounts is responsible for the success, retention, and expansion of AI Academy’s standard business accounts. These customers typically have 5–99 AI Mastery Member licenses and limited account growth potential based on company size. This is a scaled, AI-assisted customer success role. Each CSM manages a portfolio of 100–150 business accounts representing $1–2M in ARR, using AI agents, automation, and data-driven prioritization to deliver high-quality outcomes at scale. CSMs serve as the primary customer champion and trusted advisor—working in tandem with the pooled customer support team and AI agents—while functioning as AI transformation consultants for their assigned accounts. ***About SmarterX*** SmarterX is a Cleveland-based AI transformation company. We educate and empower leaders to reimagine business models, reinvent industries, and rethink what's possible. > We believe AI will rapidly transform businesses, industries, jobs, the economy, educational systems, and society.  > We believe you can build a smarter version of any business through a responsible, human-centered approach to AI. > We believe the future of all business is AI native, AI emergent, or obsolete.   >We believe AI education and training is the foundation for success in every organization. Our goal is to Accelerate AI Literacy for All through courses, content, and events. Consulting and speaking are also secondary solutions under the SmarterX brand. https://lnkd.in/gjntDUfy

I'm in awe of the volume and quality of AI courses and certificates that our AI Academy by SmarterX team is producing. In the last 45 days alone, we've released: * AI for Retail & CPG (Industries Collection) * AI-Driven Leader with Geoff Woods (AI Academy Live Series: Book Club) * How Google Forms Is Getting Smarter with AI (Gen AI App Series) * NotebookLM Audio Overviews: A New Way to Consume Documents (Gen AI App Series) * Turn Claude Desktop Into Your AI Work Partner (Gen AI App Series) * Build Autonomous AI Workflows with Claude Cowork (Gen AI App Series) * AI for Finance (Departments Collection) * AI for Financial Services (Industries Collection) * AI & IP Law: Navigating the Evolving Legal Landscape (AI Academy Live Series: Master Class) The content is powered by a growing team of internal and external instructors, including Mike Kaput, Taylor Radey, Claire Prudhomme, Katie Robbert, Jessica Miller and Christa Laser. All on-demand and live content is available as part of our AI Mastery Member program. https://lnkd.in/gtGVjSBZ

Do you have an AI story to tell? We’d love to share it with 2,500+ attendees at MAICON 2026, Oct. 13-15 in Cleveland, Ohio. We’re looking for AI experts, brand marketers, practitioners, authors, entrepreneurs, and educators who can help make AI approachable and actionable. MAICON 2026 is a multi-track event focusing primarily on: * Applied AI (i.e. use cases, case studies, technology solutions, pilot projects, etc.) * Strategic AI (i.e. talent, operations, workflows, org structures, legal/IP, ethics, etc.) * Vision, Innovation and Human Impact Sessions range from 30-45 minutes, and are a mix of solo presentations, fireside chats, and panels. The submission deadline is approaching fast, so get your ideas in now. Check out MAICON 2025 speakers, and click on "Become a MAICON Speaker." https://lnkd.in/gJv2YWiF

AI Academy by SmarterX 3.0 is finally live after 10+ months of planning and creation! We held the launch event today with nearly 2,000 registrants to introduce all the new courses, professional certificates, experiences, and resources. (Thanks to everyone who attended!) I've worked on some pretty big projects in my career, but this was probably the most ambitious and mentally consuming thing I've ever done. Plus, our incredible team worked tirelessly behind the scenes to make it all possible. The attached roadmap offers a snapshot of everything that rolled out today, and a preview of what’s coming soon. AI Academy is not just about courses. You can get incredible AI courses from lots of different companies and thought leaders. Our goal is to accelerate AI literacy and transformation through personalized learning journeys that go far beyond a single course or series. AI Academy is designed to foster deep understanding, practical application, and a transformative mindset. Every aspect of our courses, quizzes, exams, exercises, and experiences is built to help our learners drive human-centered AI transformation. At the core are our instructional design principles: - Start with the learner's “why.” - Provide flexible and adaptive pathways. - Emphasize case studies and real-world application. - Facilitate peer learning and discussion. - Focus on frameworks over prescriptions. - Consistently highlight the human-centered thread. You can learn more at the new AI Academy website.

The Cost of Intelligence in Business Software How should software companies charge for access to AI in their products? Should it be embedded in your per seat license fee (even if you pay more per license), or a separate cost based on usage, or maybe the value of the outputs? I don’t have the answers, but this is a growing issue among software companies who assume their customers will have fewer seats/employees as AI impacts jobs. And, it’s increasingly becoming an issue for business users who have to deal with unknowns around tech costs. On Ep. 193 of The Artificial Intelligence Show, I shared my personal frustration with the credit-based pricing model being used by companies such as HubSpot, Lovable, and Runway. We recently had to turn off AI features in HubSpot for a week to avoid going over some arbitrary credit limit that we weren’t even sure how we were hitting it. Now, to be clear, I love HubSpot, and have built multiple businesses with HubSpot as the core CRM. So, this is a wider industry issue that I’m illuminating through a personal experience. Here are a few of the challenges with credit-based pricing: Abstract and Variable The credits are abstract and variable, so we have no ability to forecast and manage them efficiently. For example, HubSpot’s credit pricing shows that the number of credits used varies based on the type of action being performed (e.g. customer agent interaction = 100 credits; data studio workflow with fewer than 500k rows = 25 credits; workflow automation = 10 credits). This becomes more variable in this model as the platform enables more reasoning, image generation, video generation, etc., which are more compute intensive than standard text and automation tasks. The Cost of Intelligence is Falling I know the cost of compute to serve up the intelligence in the product is plummeting (some estimates show an estimated annual cost reduction of 10x every 12 months). So if software companies are charging on a per token basis (what they pay through the API), will they continue to reduce the end user’s cost as their costs fall? That’s unlikely, which is annoying to know as a customer. Unknown Future Costs HubSpot has a section on their credit-pricing legal page showing a collection of beta AI features that they aren’t charging for yet, but will be soon. So basically every place we might use AI in HubSpot, we now have to try and consider how many tokens/credit might be used. Conclusion Again, I don’t know the answer, but generally speaking if a pricing model is causing more confusion than clarity, and makes me want to invest resources investigating alternative software solutions with more transparent pricing, it’s probably not ideal. I also feel like there is some element of the Bitter Lesson here in which software companies try to write a bunch of rules for how pricing should work (X credits for this, Y credits for that), when a more simple approach is likely the better solution for everyone.

Let’s conduct a thought experiment for a moment about the future of work. Assume that these statements are true in your business in the next 1-3 years: 1) Everyone has access to a Gen AI platform (ChatGPT, Claude, Copilot, Gemini) that can think, reason, understand, and create. 2) Everyone understands what AI is, and what it is capable of doing. Not just the basic answer engine and chat uses cases, but the deeper reasoning and multimodal capabilities that open up a world of business applications and innovations. 3) Everyone has received personalized training to help them prioritize use cases and maximize the impact of AI on their jobs (i.e. efficiency, productivity, creativity, innovation). 4) Everyone’s personal AI assistants have on-demand access to a comprehensive company knowledge base and clean, real-time data. They are able to turn data into intelligence, intelligence into insights, and insights into actions with simple prompts (or automated agents that proactively produce the outputs). 5) Everyone has on-demand access to AI subject matter experts (SMEs) across every topic inside and outside the organization. 6) Everyone has on-demand access to high-level strategic support and consultation from their AI for any business problem or goal. 7) Everyone has access to AI agents that can complete digital tasks with high-levels of reliability and autonomy. If these are true, what changes across talent, technology, processes, products and services, and business models? The answer is everything. And yet, most companies I talk to, especially large enterprises, are still stuck on number 1 (access to Gen AI). And the ones who have actually provided Gen AI access to their teams rarely have moved to 2 and 3. It is shocking how many enterprises are stuck on the most basic and accessible parts of AI adoption and transformation: tools and training. The only items above that are hard today are number 4 (data) and number 7 (reliable agents). Data can be overcome with the right approach and technical support. Agents just need more time to mature (maybe 1-2 years) in order to realize what’s possible across industries. If your organization simply does 1-3 well, everything else falls into place. But technology access, and personalized education and training, have to become urgent priorities. And it has to come from the top.

This is an interesting turn of events. The Information reports that on Monday, “OpenAI CEO Sam Altman told employees he was declaring a ‘code red’ to marshall more resources to improve ChatGPT as threats rise from Google and other artificial intelligence competitors, according to an internal memo.” This could mean delays in progress on planned advertising products, as well as existing features and capabilities such as AI agents and Pulse. The Information article highlights Imagegen, OpenAI’s image generation AI, as a tool that will get more resources in order to compete with Google’s Nana Banana Pro. Personalization is another area OpenAI will continue to invest in. “Altman said Monday in an internal Slack memo that he was directing more employees to focus on improving features of ChatGPT, such as personalizing the chatbot for the more than 800 million people who use it weekly, including letting each of those people customize the way it interacts with them.” ChatGPT is still the dominant leader in usage with 800 million weekly active users, but given the company’s massive funding needs, OpenAI can’t afford to let Google, Anthropic, DeepSeek, xAI and others slow its growth and take its customers. The AI model wars are just getting started. https://lnkd.in/gV9fcXUa

This Joe Rogan interview with Jensen Huang, CEO of Nvidia, is incredible. I’ve followed and invested in Nvidia for more than a decade, but I’d never heard Jensen’s origin story as an immigrant at age 9 (separated from his parents for two years), or the background stories of how Nvidia nearly collapsed multiple times in the early days. He tells the story of how the CEO of Sega let them out of a contract in 1995 when Nvidia had failed to deliver, and then let them keep the $5 million they had paid them as an investment in the company. Jensen said, “I told him that if you invested that $5 million in us, it is most likely to be lost. But if you didn't invest that money, we'd be out of business, and we would have no chance.” “I told him that I would understand if he decided not to, but it would mean the world to me if he did. He went off and thought about it for a couple of days, and came back and said, I will do it.” Sega later sold their stake when Nvidia had its IPO. Jensen said that investment would be worth about $1 trillion today had they held onto it! He also tells the story of Elon Musk believing in him in 2016 and buying a new AI supercomputer that Nvidia had spent billions to create. “I announced it at GTC, one of our annual events. And I described this deep learning thing, computer vision thing, and this computer called DGX1. The audience was like completely silent. They had no idea what I was talking about.” “Nobody wanted to buy it. Nobody wanted to be part of it, except for Elon. He was at the event, and we were doing a fireside chat about the future of self-driving car. And he goes, you know what? I have a company that could really use this. I said, wow, my first customer. And so I was pretty excited about it.” “And he goes, yeah, we have this company. It's a non-profit company. And all the blood drained out of my face.” That non-profit was OpenAI. If you love a great entrepreneurial success story as much as me, you’ll enjoy this episode.

AI Trends to Watch in 2026 (Part 1) . . . For Episode 188 of The Artificial Intelligence Show, which drops on Dec. 23, I put together a list of some of the key trends we’re watching as we head into the new year. These aren’t meant to be predictions. They are more observations on AI topics that we think will play important roles in AI progress, adoption, and integration over the next 12 months. I focused on three areas: Technology, Business, and Society. For today’s post, I’ll share the AI Technology trends. 1) Personalization of AI assistants: AI assistants will be increasingly personalized for individual users based on the preferences, traits, beliefs, and conversation history, and the memory capabilities and dynamic personalities of the chatbots. As an example, OpenAI just rolled out the ability to adjust “characteristics” including warmth, enthusiasm, emoji use, and style. 2) Reliability of agents on long-horizon tasks: Significant progress is being made by AI labs on agents and multi-agent systems that are capable of performing long-horizon cognitive workflows and tasks that can take human workers hours, and eventually days and weeks. 3) AI model progress across many dimensions: Leading AI labs are unlocking AI model gains across areas including: continual learning, context windows, memory, multimodality, reasoning, recursive self improvement, and world models. 4) Multi-media outputs that are indistinguishable from reality: The "uncanny valley" is rapidly closing as generative AI models for images, video, audio, and 3D environments become indistinguishable from reality. 5) Humanoid robot advancements: The convergence of advanced computer vision and specialized "world models" is accelerating the deployment of general-purpose humanoid robots. We are moving towards robots being able to navigate real-world environments and perform complex manual labor in industries such as manufacturing, retail, and healthcare. 6) Consumer hardware gets smarter: In addition to your smartphones getting smarter (please, Apple, deliver us a next-generation Siri!), we are seeing a race to build and sell wearable devices, such as glasses, that can see and understand the world as you interact with it in real-time. 7) Progress toward AGI and ASI continue: The quest for Artificial General Intelligence (AGI), and eventually Artificial Superintelligence (ASI), remains the North Star for leading labs. I'll post AI Business trends on Monday, and AI Society trends on Tuesday, along with the link to the episode. What noteworthy AI Technology trends are you seeing?

This past week, we held the SmarterX annual meeting and retreat with our full team. It was an inspiring couple days of in-person collaboration and camaraderie. Day one we talked about vision, goals, KPIs, priorities, and growth initiatives. Day two we ran AI Productivity and AI Innovation workshops designed to accelerate responsible AI adoption across our business units and teams. While I teach this stuff every day to other companies, taking time to do it for ourselves gave me a new perspective on how quickly AI is redefining what’s possible in AI-forward companies. One specific example is Rocks. We use a modified version of Rocks from the Entrepreneurial Operating System (EOS) in which departments and individuals establish 3-5 priorities per quarter. Rocks align our time, energy, and resources on what matters most, and provide transparency across the organization into what everyone is focused on. The one thing that became abundantly clear to me is that the time to complete Rocks is compressing, and that this requires a complete rethinking of our operating system. For example, during a live session in which I was demoing a new AI assessment tool we’re developing, I used Anthropic Claude Sonnet 4.6 in real time to build an interactive reporting dashboard that visualized and analyzed responses from 17 people. This was the entire prompt: “I had 17 team members take the assessment. Can you come up with an elegant way to visualize the results based on the format/model you already created? The csv is attached.” In a previous life (aka three months ago), this would have been a Rock for Q2: “Create an interactive dashboard to visualize assessment results for teams.” I would have spent 10-20 hours researching dashboards and developing a project brief. Then I would have invested time and money hiring a designer and developer to conceptualize, build, and iterate on the design and capabilities. Then we would have gone through weeks of internal testing and revisions. And maybe by the end of Q2, I would have had a minimum viable product (MVP) to demonstrate to the team and pilot with users. Instead, in a matter of about five minutes, Claude did the entire thing with one prompt. And the final product was beyond anything we would have created through the traditional process. It’s time to reimagine what’s possible in business. Everything has changed, most leaders just don’t realize it yet.

Many marketing agencies are at a crossroads. AI is threatening to disrupt traditional service and pricing models, while presenting new growth opportunities for the firms that can reimagine their business and help clients drive AI transformation. Brands—empowered by access to the same AI tools as their agency partners—are demanding more value and outputs, while expecting to pay less due to efficiency gains. We all have more questions than answers for what happens next, and that's why we're holding our 3rd annual AI for Agencies Summit presented by Screendragon on Feb. 12, 12-5 pm ET. This is a half-day, live virtual event that brings together thousands of agency professionals and leaders to consider what's possible as AI advances. We have an incredible lineup with seven speakers, and we've introduced a free registration option this year. If you work for an agency, you won't want to miss this. If you work with an agency, pass it along to your account team. Everyone benefits from building more AI-forward agencies that are helping drive responsible AI transformation across industries.

I’ve consistently found that one of the most effective ways to help people understand AI, and get immediate value from AI assistants, is to build Custom GPTs for specific tasks. Sharing sample prompts is great too, but GPTs make use cases and benefits extremely tangible. We have a collection of internal GPTs trained on proprietary data, but we also build and share public GPTs based on our AI frameworks. We use these for educational purposes in our AI Academy courses, and also teach them in AI workshops to give people tools to accelerate their learning and experiment with practical applications. If you’ve never built a Custom GPT, I highly recommend trying it. If you can give instructions to a human how to do something, then you can train and create a GPT. It requires no coding, or advanced AI knowledge. It’s simply text instructions, and ideally some knowledge base documents. Here are some of the public GPTs I’ve built and shared that anyone can explore: > JobsGPT analyzes job roles by breaking them into tasks, assessing AI's impact on each, and providing actionable insights to optimize productivity and prioritize AI-driven opportunities. This is also trained on the AI Exposure Key I devised related to anticipated AI advancements. > CampaignsGPT analyzes tasks within campaigns to identify AI's impact, prioritize use cases, and enhance productivity across business functions. > ProblemsGPT identifies and prioritizes business challenges, helping craft problem statements and initial strategic plans to accelerate AI-driven innovation and smarter decision-making. > Innovations GPT helps push beyond conventional boundaries, empowering you to reimagine your business model, revolutionize your industry, and drive growth. > Co-CEO is an experimental custom GPT that acts as a strategic advisor for executives across marketing, sales, customer service, product, operations, HR, finance, and legal. This is a public version meant as a demo. I have a private version that is trained on our data and roadmap. > Kid Safe GPT helps parents understand online risks, provides guidance on discussing safety with kids, and helps create customized safety agreements to protect children in digital spaces. I’d love to hear in the comments about the GPTs (or Google Gems) you’ve built, or the ones that you use regularly. Always looking for inspiration, and always interested in experimenting. You can access all of our public GPTs in the comments link.

AI is improving much faster than most business leaders realize. I just watched an interview from Davos featuring Demis Hassabis (co-founder and CEO of Google Deepmind) and Dario Amodei (co-founder and CEO of Anthropic). While their timelines for AGI differ slightly, it's very apparent they share high conviction that we are on a near-term path to much more powerful and generally capable AI systems. It is becoming increasingly important that organizations plan for this future, now. One of the key actions leaders can take is to establish and govern a set of responsible AI principles that guide a human-centered approach to AI. Here are 12 principles that I set forth in January 2023 as part of a Responsible AI Manifesto. The manifesto was meant to codify our responsible AI principles at SmarterX, and serve as an open template for other organizations and leaders who want to pilot and scale AI in an ethical way. 1) We believe in the responsible design, development, deployment and operation of AI technologies. 2) We believe in a human-centered approach to AI that empowers and augments professionals. AI technologies should be assistive, not autonomous. 3) We believe that humans remain accountable for all decisions and actions, even when assisted by AI. The human must remain in the loop in all AI applications. 4) We believe in the critical role of human knowledge, experience, emotion, and imagination in creativity, and we seek to explore and promote emerging career paths and opportunities for creative professionals. 5) We believe in the power of language, images and videos to educate, influence, and affect change. We commit to never knowingly use generative AI technology to deceive; to produce content for the sole benefit of financial gain; or to spread falsehoods, misinformation, disinformation, or propaganda. 6) We believe in understanding the limitations and dangers of AI, and considering those factors in all of our decisions and actions. 7) We believe that transparency in data collection and AI usage is essential in order to maintain the trust of our audiences and stakeholders. 8) We believe in personalization without invasion of privacy, including strict adherence to data privacy laws, mitigation of privacy risks for consumers, and following our moral compass when legal precedent lags behind AI innovation. 9) We believe in intelligent automation without dehumanization, and the potential of AI to have profound benefits for humanity and society. 10) We believe in an open approach to sharing our AI research, knowledge, ideas, experiences, and processes in order to advance the industry and society. 11) We believe in the importance of upskilling and reskilling professionals, and using AI to build more fulfilling careers and lives. 12) We believe in partnering with organizations and people who share our principles.

A behind-the-curtain look at how I think about building an AI-Native business at SmarterX. As I was standing in line this morning to board my flight, I saw this quote on X from Coursera’s CEO: "In 2025, AI skills are becoming essential, and demand has accelerated. We are now seeing 14 enrollments per minute in our catalog of more than 1,000 generative AI courses, up from 8 enrollments per minute last year. Generative AI is the most in-demand skill in Coursera's history," My plan for SmarterX is to scale an eLearning platform with 100s of thousands of licenses, so I’m always looking to learn from the companies that are leading the way. At first, I made a to-do to find and review the full earning call transcript. Then I had a thought. What if, instead, I built an AI agent to automate this process moving forward? So, now sitting on the plane waiting to takeoff, I created this workflow: * Pull quarterly transcripts from leading eLearning platform companies (maybe via CB Insights subscription). * Analyze based on predefined criteria and format using system prompt + template. * Extract key excerpts and summarize highlights with focus on CEO and CFO comments, as well as analyst questions related to AI education market. * Create strategic brief related to our business model using the format in your knowledge base. * Recommend strategic updates to our business model based on key insights and opportunities. Include guidance on market demand, pricing, courses, sales and customer success models, and staffing. I’m not 100% how to build it yet, but I’ll work on that when I land. I used my Co-CEO GPT to run a test with the actual transcript and the output was incredible. The above workflow would probably take me 5-10 hours per earnings call to perform manually. My guess is I can build the agent (with some technical help) in about that same amount of time, and then save myself 30+ hours per quarter (assuming 3 companies to monitor). More importantly, I likely wouldn’t have had time to complete this workflow, so this automation is additive. It’s bringing new value to the company through a small innovation. All of the above happened in about 5 minutes at the airport. It took me longer to type this post on my phone. Learn to look at problems and opportunities differently. AI makes it possible to reimagine workflows and business models.

AI Trends to Watch in 2026 (Part 3: Society) . . . For Ep 188 of The Artificial Intelligence Show, which dropped today, I put together a list of some of the key trends we’re watching as we head into the new year. These aren’t meant to be predictions. They are more observations on AI topics that we think will play important roles in AI progress, adoption, and integration over the next 12 months. I focused on three areas: Technology, Business, and Society. For today’s post, I’ll share the AI Society trends. 1) Synthetic relationships become mainstream (companions, tutors, coaches): Always-on AI companions will become commonplace for tutoring, therapy, wellness coaching, mentorship, and companionship. The upside is scalable support. The downside is dependency, manipulation risk, and blurred boundaries. Expect a growing conversation around disclosure, safeguards for minors, and standards for emotional AI. 2) AI grows as a political friction point: Expect to see AI continue to play a key role in political agendas and campaigns, both in the U.S. as a midterm election wedge related to jobs, regulations, and security, and on the international stage, specifically related to relations with China. 3) AI becomes a disruptive force on jobs: The conversation around AI and jobs is shifting from theory to reality. As AI agents become more autonomous and reliable across knowledge work professions (e.g. attorneys, consultants, customer service representatives, sales professionals, marketers, etc.), we will see significant disruption to the labor market. 4) AI investment continues to drive economic growth and GDP: The massive capital expenditures in data centers and energy infrastructure are beginning to translate into measurable productivity gains, potentially sparking a period of sustained economic expansion. But, the economy is also becoming increasingly reliant on the AI infrastructure buildout to sustain its strength. If an AI bubble emerges, the broader economy could see significant negative impact. 5) Leading AI labs go public: The "private era" of the AI boom is maturing. As early-movers demonstrate sustainable revenue and defensible moats, the public markets are preparing for a wave of high-profile IPOs from OpenAI, Anthropic, and others, providing the liquidity needed to fuel the next decade of infrastructure development. 6) Education shifts from “anti-cheating” to “AI-native assessment”: Instead of schools banning tools, they’ll move toward oral defenses, in-class creation, and real-world problem solving where process and chain-of-thought matters as much as the output. The future of work is human + AI, and educational systems must rapidly evolve to prepare students for a business world that requires high degrees of AI literacy and capabilities. See the comments for Part 1 (AI Technology Trends) and Part 2 (AI Business Trends), as well as a link to Ep. 188.

The latest edition of the AI Answers podcast series covers some timely topics, including the potential for marketing agent swarms in 2026, entry-level job disruption, AI’s environmental impact, and AI privacy. These questions come from the audiences of our AI for Departments Week webinars (Marketing, Sales, and Customer Success) in late February that were all presented by Google Cloud. 00:00:00 — Intro 00:05:18 — How should a CMO get started with AI? 00:09:57 — What is the difference between an AI agent and a regular prompt? 00:12:47 — Will AI labs fix their environmental impact? 00:17:04 — How to convince skeptics that AI can help improve performance? 00:19:55 — How to deal with AI sycophancy when using it as a thought partner 00:22:06 — What efficiency gains are people seeing from generative AI in marketing? 00:25:42 — How to track and measure time saved by AI 00:27:47 — How to manage information and prompts across multiple AI platforms 00:33:59 — How to balance AI adoption with data privacy and security 00:36:17 — Which roles will be most disrupted by AI? 00:43:51 — Will AI sales calls just feel like spam robocalls? 00:46:29 — How to reinvest time saved by AI into growth and innovation 00:49:33 — When to buy software versus build it yourself with AI 00:54:35 — How to protect yourself from others using AI agents irresponsibly 00:55:58 — Why IT shouldn’t be driving AI adoption What is AI Answers? Since 2021, our free Intro to AI and Scaling AI classes have welcomed more than 50,000 professionals, sparking thousands of questions. AI Answers presented by Google Cloud is a biweekly bonus podcast series that curates and answers questions from attendees of these live events. Each episode focuses on the key concerns, challenges, and curiosities facing professionals and teams trying to understand and apply AI in their organizations. I answer each question in real time—unscripted and unfiltered—just like we do live. https://lnkd.in/g4Pgih7c

On the latest edition of AI Answers, Cathy and I cover 15 audience questions related to AI’s impact on talent and jobs, the rise of the generalist in business, and realistic timelines for AI agents. We also get into signals that tell you an AI pilot project is failing due to human resistance rather than tech limitations, and the critical importance of maintaining human authenticity in an era of AI-generated content. You can listen to the full episode, or bounce around to the timestamps most relevant to you: 00:00:00 — Intro 00:06:11 — Q1: Who owns AI learning in an organization: L&D or departments? 00:09:52 — Q2: Hiring dedicated AI change management consultants.  00:11:54 — Q3: Middle management’s role in normalizing adoption. 00:14:27 — Q4: Signals a pilot is failing due to culture, not tech.  00:16:12 — Q5: Balancing learning pace vs. rapid experimentation.  00:20:11 — Q6: Hiring for critical thinking and AI skills. 00:23:31 — Q7: Experience vs. adaptability in talent acquisition.  00:25:35 — Q8: Protecting and compensating AI leaders. 00:27:56 — Q9: Using AI with confidential data restrictions. 00:30:35 — Q10: Realistic timelines for AI agent advancement.  00:33:21 — Q11: Managing model selection and "agent chaos." 00:37:24 — Q12: The rise of the Generalist vs. Specialist.  00:41:14 — Q13: Proving AI skills beyond certificates.  00:44:25 — Q14: Trust and authenticity in AI content. 00:48:35 — Q15: AI SDRs: Vendor questions vs. building in-house. What is AI Answers? Since 2021, our free Intro to AI and Scaling AI classes have welcomed more than 50,000 professionals, sparking thousands of questions. AI Answers presented by Google Cloud is a biweekly bonus podcast series that curates and answers questions from attendees of these live events. Each episode focuses on the key concerns, challenges, and curiosities facing professionals and teams trying to understand and apply AI in their organizations. I answer each question in real time—unscripted and unfiltered—just like we do live. https://lnkd.in/gxBPkY5h

Our 3rd annual AI for Agencies Summit presented by Screendragon kicks off today at noon ET. This is a half-day, live virtual event that brings together 3,000+ agency professionals and leaders to consider what's possible as AI advances. We have an incredible lineup with seven speakers, and we've introduced a free registration option this year. There's still time to join us! www.aiforagencies.com

Is there an AI bubble? This is a conversation that keeps coming up, and it’s relevant to your personal investing decisions, and your career choices. This was a main topic on ep 183 of The Artificial Intelligence Show. Here are the highlights of what I shared: You have to consider your own position from a personal investing perspective, but also from a career and business perspective. What is your long-term thesis on AI? What is your level of conviction? What is your appetite for risk? For me, I bet everything personally and professionally starting in 2016 that AI would change the world. That every business in every industry would be AI Native, AI Emergent or obsolete. I bet on the companies that I thought were best positioned to grow when demand for intelligence scaled, and I built my own companies to help professionals and businesses accelerate their AI understanding and transformation. I believe we are still on the leading edge of an intelligence explosion. That does not mean that every AI company survives. There will be winners and losers. There will be ups and downs. There will be variables that are out of our control that will impact the markets, and AI progress, in the months and years ahead. What Accelerates AI Progress: - Algorithmic breakthroughs - Clean energy abundance (i.e. wind, solar, nuclear fission) - Compute-efficiency breakthroughs (e.g. smaller models, targeted search and retrieval in models like our brains, faster inference) - Cost of intelligence declines at a rapid rate - Energy breakthroughs (e.g. nuclear fusion) - Greater network and data security to reduce threats and risks - Infrastructure investments (e.g. upgraded and expanded electrical grids, more data centers) - Large-scale government funding (e.g. Apollo-type programs) - More compute capacity (i.e. more chips and fabs, plus diversity in the chip supply chain) - New scaling laws - Other scientific breakthroughs (e.g. metacognition, quantum computing, new physics) What Slows AI Progress? - Breakdown in the AI compute supply chain through natural (e.g. earthquakes, hurricanes) or human (e.g. physical or cyber sabotage) forces - Catastrophic events blamed on AI - Lack of value created in enterprises - Landmark IP lawsuits that impact access to training data and legality of existing models - Restrictive laws and regulations (e.g. heavy regulation of open source models) - Societal revolt against AI due to job loss, politics, perceptions, fears, etc. - Unexpected collapse in scaling laws - Voluntary or involuntary halt on model advancements due to catastrophic risk I think there is far greater risk in sitting back and assuming this is all a bubble, than positioning yourself and your company to thrive in the age of AI. https://lnkd.in/gg5Vmtk9

If you think AI filmmaking is easy (or not creative), check out this video (which is 100% AI, BTW), and see his process. The future of filmmaking has arrived, and it’s going to transform how shows, movies, ads, and social videos are produced. There will be pros and cons to this, but it’s a reality we have to start adapting to. “We want to tell stories, we want to create films that matter, ads that stay in your head. We believe that now is the time to create amazing content with AI, but first and foremost: with people who understand their craft! Making films with AI is NOT just pressing a button. It's teamwork, it's artists, it's producers and sound designers, people who understand lighting and composition, people with taste.” - Simon Meyer

In addition to announcing the long-awaited restructuring to a public benefit corporation, which paves the path for a likely IPO in 2026-2027, OpenAI shared updated plans to build an autonomous AI researcher. On a livestream last week, company leaders stated their internal goals to create an AI research intern by September 2026, and a fully autonomous AI researcher by March 2028. Altman said OpenAI chose to reveal these internal timelines because, “given the extraordinary potential impacts, it’s in the public interest to be transparent about this.” Altman added on X, “In 2026 we expect that our AI systems may be able to make small new discoveries; in 2028 we could be looking at big ones. This is a really big deal; we think that science, and the institutions that let us widely distribute the fruits of science, are the most important ways that quality of life improves over time.” We’ve known for months that OpenAI was heading in this direction. In April 2025, The Information reported: “By the end of the decade, the company has told some potential and current investors it expects combined sales from agents and other new products to exceed its popular chatbot, lifting total sales to $125 billion in 2029 and $174 billion the next year.” “They even project that by 2029, agents alone could bring in $29 billion a year, selling high-end AI workers ranging from $2,000-a-month knowledge agents to $20,000-a-month research agents.” AI researchers are scientists who study and invent new ways to build increasingly intelligent AI systems that can think, understand, reason, create, take action, and automate work across industries. Human researchers are constantly moving between AI labs, and the top researchers can earn millions of dollars per year. But, the breakthroughs they create can be worth billions—or trillions—of dollars. For example, eight researchers are listed on the 2017 Attention Is All You Need paper from Google Brain that invented the transformer. The transformer became the architecture that enabled the building of ChatGPT, and the catalyst for the generative AI age. Building an automomous AI researcher is a bit of a canary in the coal mine. All major AI labs are pursuing autonomous AI researchers because they have an enormous compounding value. Projects that currently take human researchers months or years might be done in hours or days. New insights could emerge in fields like medicine, materials science, physics, etc., because these autonomous systems might explore spaces humans haven’t yet fully charted, or don’t have the time to explore. The same approach will happen in other industries and across professions. We talk a lot more about these concepts and their impacts on Ep. 178 of The Artificial Intelligence Show. https://lnkd.in/grTQQb53

What is something that 100% of humans would agree on? That is the random thought experiment I had last week that led to a main topic on Ep. 180 of The Artificial Intelligence Show. As more influencers and politicians take interest in AI and its impact on society (good and bad), I think it’s critical that we have foundational conversations around beliefs and truths. As I said on the podcast, I hesitated to even have the discussion because it came from a very personal place for me, and I am not a philosopher who has studied these concepts. So, I presented the ideas from my own personal perspectives and experiences, and connected them to why I think it is important to consider these ideas in relation to where AI is, and where it’s going. A belief is something we think is true. People can disagree about it. It can be true or false, strongly or weakly held, justified or not. People can have conviction about something and be wrong. People who have strongly held beliefs usually don’t want to be told that their beliefs aren’t truths, which leads to conflict in business and life. A fundamental truth is true whether or not anyone believes it. For example: > Time always moves forward. > If you drop a rock, it will fall down, not up.  > Humans need air, water, food, and sleep to live. > 2+2 = 4 Science takes beliefs, questions, observations, and ideas and tests them to form models and laws (e.g. the AI Scaling Laws). Science is, “our best tested explanation right now.” Built by evidence, experiments, and predictions; always open to revision if stronger evidence appears. There are an increasing number of politicians, influencers, and AI leaders voicing beliefs with great conviction. They present information as though it is a fundamental truth or a scientific law. When, in reality, it is just a subjective opinion, oftentimes intended to advance their own agendas. As more of the general public becomes aware of AI, they will form their own beliefs. Whether true or not, those beliefs will begin to affect how AI is regulated, how it is taught in schools, and how it is applied in business. We all need to do our part to be open-minded, to listen to other people's opinions and beliefs, to form our own educated positions, and to do our best to push for balanced and logic-based conversations in our companies and communities. Lots more to the conversation in the episode. See 00:22:09. 00:00:00 — Intro 00:03:59 — AI Pulse 00:06:41 —GPT-5.1 00:14:51 —Controversial New AI Product Brings Back the Dead 00:22:09 — Beliefs vs. Fundamental Truths 00:39:39 — Increasingly Negative Public Moods Towards AI 00:46:36 — First Reported AI-Orchestrated Cyberattack 00:51:33 — AI-Generated Country Song Tops Billboard Charts 00:58:43 — Cursor Raises $2.3 Billion, Valued at $29.3 Billion 01:01:13 — Parallel Raises $100 Million to Build Web for Agents 01:03:34 — Yann LeCun Leaving Meta 01:07:47 — NotebookLM Adds Deep Research 01:10:24 — McKinsey State of AI Report

We cover a lot of ground on the latest edition of the AI Answers podcast series, including job displacement, why AI literacy is the most overlooked foundation of any AI strategy, and what the future of knowledge work might actually look like when senior leaders can do the work of entire teams. 1) We’ve been talking about Amazon slowing parts of its AI rollout due to quality issues. My gut says that might actually be a sign of maturity, but how do you see it? 2) Do you think large enterprises are structurally disadvantaged in the AI era, or do they have assets that will ultimately let them win? 3) If we say the bottleneck is something like adoption or data readiness, who actually owns that problem inside an enterprise, and why hasn’t it been solved yet? 4) I keep thinking about this idea of an “AI divide” inside companies between power users and everyone else. Are you seeing that too? What actually happens to the people who don’t keep up? 5) What’s an AI take you have right now that most people would disagree with? 6) Is there a world where companies look back and feel like they automated too much, too fast? Has that already happened? 7) We’ve talked before about augmentation versus automation. Do you still think we land somewhere in the middle, or does automation eventually take over? 8) If we fast forward three years, what does the average knowledge worker’s job actually look like because of AI? 9) What are companies still getting fundamentally wrong about AI strategy right now? 10) One of the biggest challenges I hear is just keeping up, since everything seems to change weekly. How should leaders decide what actually matters versus what’s just noise? 11) We hear a lot about AI councils, but I’ve also seen them slow things down. What separates the ones that drive progress from the ones that don’t? 12) Where do you think governance is necessary right now, and where is it actually getting in the way? 13) When you’re showing AI to leadership, is it more important to show the system itself or real outputs and results? (Paul, what do you as a CEO want to see?) 14) What’s one AI use case that feels like a no-brainer at this point, but most companies still haven’t implemented? 15) I still see people waiting to be told how to use AI instead of just experimenting. Why do you think that is, and what actually works to change that behavior? What is AI Answers? Since 2021, our free Intro to AI and Scaling AI classes have welcomed more than 60,000 professionals, sparking thousands of questions. AI Answers is a biweekly bonus podcast series that curates and answers questions from attendees of these live events. Each episode focuses on the key concerns, challenges, and curiosities facing professionals and teams trying to understand and apply AI in their organizations. I answer each question in real time—unscripted and unfiltered—just like we do live. https://lnkd.in/gTWXxx_R

The latest edition of our AI Answers podcast series dropped today. AI Answers is a biweekly bonus series from The Artificial Intelligence Show that curates and answers real questions from attendees of our live events. Each episode focuses on the key concerns, challenges, and curiosities facing professionals and teams trying to understand and apply AI in their organizations. 00:00:00 — Intro 00:03:55 — Q1: What AI Positions are in demand for professionals who are not coders? How can skill sets be presented to hiring managers? 00:08:49 — Q2: What are the top AI concepts that organizational communicators need to know? 00:10:56 — Q3: What should I focus on in AI? 00:13:21 — Q4: What do you think would be a good area to focus on as someone trying to break into the AI industry? 00:16:15 — Q5: Would you recommend prioritizing 'Generative' use cases or 'Predictive' use cases to achieve the quickest win? 00:18:45 — Q6: What’s the most innovative way to get started? Do we need a certain level of data hygiene first, or can AI help clean and organize the data as we go? 00:23:55 — Q7: Can you talk about what to be aware of and best practices for sourcing use cases? 00:28:25 — Q8: What is the best way to introduce AI tools to a technical/industrial workforce without causing 'replacement fear'? 00:30:47 — Q9: What would you say to people who are trying to move beyond the mechanical use of AI and actually trust the technology enough to use it in meaningful ways? 00:34:20 — Q10: How do you see AI-driven search tools impacting traditional search engines? 00:36:43 — Q11: As generative AI matures, what’s the next significant shift? 00:41:04 — Q12: Do companies understand AI well enough before reducing their human workforce? 00:45:51 — Q13: What are the main factors that could slow down the advancements of AI? 00:49:11 — Q14: As AI systems move toward recursive self-improvement, what guardrails are needed to ensure they aren’t learning from a distorted or incomplete view of the world? 00:52:27 — Q15: What are you most excited about for AI in 2026? https://lnkd.in/gq5NhWYB

Reports today have both SpaceX and Anthropic considering IPOs in 2026. OpenAI has been rumored to be targeting an IPO in 2026-2027. Let’s say all three IPO next year. You can only buy stock in one. Which are you buying? And why? I think one of them is a $10 trillion company by 2035. I won’t say which one yet.

We’ve teamed up with Google Cloud to produce an AI for Departments series of webinars and Blueprints that launch next week (Feb. 24-26). The webinars will take place live at noon ET each day, and we’ll release the corresponding (ungated) Blueprints at the same times. * Feb. 24: AI for Marketing presented by Google Cloud - Learn how to scale campaigns, optimize content workflows, and generate demand with less manual effort. * Feb. 25: AI for Sales presented by Google Cloud - Discover how to empower your sales teams with AI-enhanced prospecting, personalization, and pipeline management. * Feb. 26: AI for Customer Success presented by Google Cloud - Explore how to use AI to improve customer retention, streamline support, and proactively identify churn risks. These resources are an ideal way to get started with AI, or expand your understanding and use. They are also a great way to introduce AI to your department peers who may not be as far along their AI journeys. Hope you can join us. https://lnkd.in/gysNiVfa

Every Friday we drop a new Gen AI App Series review in AI Academy by SmarterX. This week's course features an incredible breakdown of Claude Cowork by Katie Robbert, one of our newest featured instructors. Katie gives us a hands-on look at how Cowork transforms AI from a simple chat interface into a structured work environment for multi-step projects. In this 20-minute course you'll see how Cowork allows you to organize folders, configure capabilities, and build workflows where Claude can independently complete tasks across multiple files. Instead of prompting step by step, you’ll learn how to create a setup where Claude can access the information it needs, process it, and deliver results while you focus on other work. The course is available now to AI Mastery Members, and for one-off course purchases.

In what’s being called, “SaaSpocalypse,” software stocks got pummeled last week. According to The Wall Street Journal, “Investors’ fears that new developments in artificial intelligence will supplant software reverberated through the stock market…dragging down the shares of companies that develop, license and even invest in code and systems. Traders have questioned whether AI will chip away at the competitive moat built by software makers.” Mike and I tackled this topic on Ep. 196 of The Artificial Intelligence Show. For some context, here are the stock price drops of some leading software companies YTD (since Jan. 1, 2026): * Adobe (ADBE) -20% * Asana (ASAN) -34% * HubSpot (HUBS) -38% * Intuit (INTU) -29% * Salesforce (CRM) - 22% * ServiceNow (NOW) -27% * Workday (WDAY) - 24% As you can see, it’s not good. This despite strong earnings reports and near-term strength in revenue forecasts from many of them. Is it an overreaction from the market? Most likely. But, there is new uncertainty around the stability of SaaS multiples and whether the traditional SaaS players will be the ones to capture the value moving forward. The question is in part about the $300 billion SaaS market, but it's really more about the total addressable market of human labor, and which technology companies will capture the largest shares there. a16Z State of Markets pegs annual software spend in the U.S. at $300-$350 billion, while, according to the same a16z report, the Bureau of Labor Statistics has U.S. white collar payroll at $6 trillion annually. The software spend isn’t going away. It will likely increase significantly. But, it also may shift away from the legacy software players. It’s a nuanced conversation that comes down to uncertainty around future growth and cash flows. The vast majority of companies are not going to vibe-code an alternative to HubSpot, Salesforce, ServiceNow, Workday, etc. But, as AI systems like Claude and ChatGPT become capable of doing the work (e.g., drafting, analyzing, routing, negotiating, summarizing, completing workflows), buyers will feel less need to pay for lots of separate SaaS tools + per-seat licenses. If agents do more work, companies may buy fewer seats, or demand pricing tied to outcomes/usage instead. Lots more thoughts in the episode. 00:00:00 — Intro 00:04:14 — AI Pulse Results 00:06:24 —SaaS Apocalypse 00:23:53 — Anthropic Super Bowl Ad 00:33:56 — The Move 37 Moment for Everyone 00:47:39 — SpaceX Acquires xAI 00:50:55 — Claude Opus 4.6 00:56:00 — GPT-5.3 Codex 00:59:10 — OpenAI Frontier 01:04:48 — The AI Capex Wars 01:11:01 — Latest on AI Impact on Jobs 01:14:52 — Agentic CRMs 01:17:41 — AI Product and Funding Updates https://lnkd.in/dcQa36d4