Mark Law

Is tech losing its way? Many 'innovation'-focused product roles that I've seen this year seem to more reflect AI-reactive panic than coherent strategy. Companies seem eager to skim who they can off the top of what's becoming an incredibly deep talent pool without first putting a modicum of thought into how to set these folks up for success. It seems almost inevitable that we'll see another wave of turnover in 1-3 years amongst the top talent that was hired into these hand-wavy roles. Despite the growing quantity of tech job seekers, it's almost refreshing to see some companies hitting pause on hiring until they figure out what they truly need.

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I’m happy to share that I’ve been involved as an advisory board member with Humane AI. It's a great organization - please comment below or message me if you want to learn more or get involved. https://www.humane-ai.ai/ Humane AI #AI #Ethics

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Brad Romney from Verdi was on fire last week. We discussed his insights on integrating AI into product development workflows. He shared fantastic advice and a fascinating graphic on where AI impacts Product Managers' work—partially, fully, and not at all. Catch the full event in the comments. Thanks again, Brad, for sharing your wisdom! #ai #productmanagement #productleadership

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Interesting - do we want AI to write our TV shows? If creativity is parametrized to certain metrics and the goal is to maximize attention of the audience, we know what will be the results. It will be a gross regurgitation of every sensational show that has done already done that in the past. We risk going into a time loop of consuming the same content over and over, again and again, in different forms. I hope we will get AI technologies to solve other pressing problems for us in #cleanenergy #medicine #spacetech etc. Please let human creativity be! I thought the whole point of automating everything we do is to allow us become more creative. Am I wrong #siliconvalley? #innovation #purpose #society

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I've been wanting to build a personal website and landing page to video call with my Tavus digital twin for a while, and I finally did it. I used Replit and Cursor to do it, and man, was I blown away. This had been on my bucket list for a while- but a lack of time and my general displeasure in writing front-end had been blocking me. Using Replit was magic, letting me express my dreams and ideas and turning them into a reality. I was so impressed at its ability to plan things out, be verbose with its execution, and just rip through file by file—a complete step-change compared to copying and pasting code from Claude. Unfortunately, I hit my usage limit rather quickly (Amjad Masad, please increase the limits, friend), so then I exported the code and moved to Cursor. I’ve been using Copilot for a while and used Cursor to work on existing code, but I hadn’t used it or tested it for something from the ground up. Holy crap, I was incredibly impressed with it as well. I found that combining Anthropic Claude 3.5 Sonnet and OpenAI o1-preview worked well. It took a good degree of prompting to get it to do the right things at times, but o1-preview as an architect and Claude 3.5 sonner as the developer worked quite well. Highly recommend this setup. Also, throwing in o1-preview for harder problems or just to have an alternative take on something – was a game changer. Then, came actually integrating my Tavus digital twin into the site. I hooked up the Tavus docs and Cursor just ripped through and easily wrote code to create a conversation. While I may not have written much of the code for this personal blog, I did write all of the content because that’s the part that is truly me. AI cannot understand or replicate it. The best part of using tools like Replit and Cursor is that it allowed me to focus on writing the content and design rather than the intricacies of the front end. Before this, I didn’t think SWEs could be replaced, but now I think junior devs absolutely can be. I still do think it takes experience and software engineering knowledge to truly get great outputs. While creating anything may be easy, making something good will still take a sense of design and product think. That’s the human part that will not be replaced. Understanding system architecture and having an eye for design will be the differentiators. The point of this exercise was also to force me to put down my thoughts in a place for my digital twin persona to consume. This website will serve as the knowledge base for my digital twin. Creating my digital twin was super easy using Tavus. That will be the next post—how to create a digital twin of yourself easily using Tavus. For now, check out the website and talk to digital me. www.hassaanraza.com

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I'm still leery of calling today's AI "intelligent" or "reasoning", but I like how Perplexity is starting to experiment with how best to communicate the trade-off between quality vs. speed in the design of its in-product tooltips....

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The Future of Money, Robots, and AI—Key Insights from Peter H. Diamandis's Blog and my queries on top of that. In a recent blog by visionary Peter Diamandis, he explores groundbreaking shifts that are set to reshape economies globally. Here are three key takeaways: 1️⃣ Will Money Become Irrelevant? AI, robotics, and nanotechnology are driving production costs to near-zero, potentially diminishing the role of money as we know it. But does this mean money will become irrelevant? Not entirely. As production costs drop, powered by advancements in fusion energy, open-source IP, and automated manufacturing, we’re headed towards a world of abundance, where the focus may shift from earning to managing resources differently. 2️⃣ China’s Bet on Humanoid Robots 🤖 Facing a rising labor cost and aging population, China is banking on humanoid robots to retain its manufacturing edge. Companies like AGIBOT and Unitree are leading the way, while Tesla and Boston Dynamics push globally. Robots will transform industries, freeing humans from labor-intensive tasks. 3️⃣ India’s Big Bet on AI 🇮🇳 With a youthful population but significant economic challenges, India MUST invest in AI. AI-driven education and healthcare, powered by networks like Jio’s 5G, can democratize access and enable the country to achieve its ambitious economic goals. These shifts are no longer distant possibilities—they’re happening now. 💡 🚀 As exciting as this sounds, it raises some critical questions about our future: 1️⃣ What will humans do when knowledge work and even arts (think video generation) are automated? Will there still be room for human creativity in a world where machines can produce at scale? 2️⃣ China's reliance on humanoid robots makes sense given labor shortages, but wouldn't fostering global citizenship, where people work across borders, reduce the dependency on robots while keeping humans engaged in meaningful work? 3️⃣ AI in education is critical, but how should education evolve in a future that might not prioritize jobs but rather a gig economy or entrepreneurship? How do we prepare the next generation for this transformation? Would love to hear your thoughts on these. If you’re curious to explore more, subscribe to Peter’s blog for deep dives into the future of technology: Peter Diamandis Blog - https://lnkd.in/gTZyC_a6 And if you find this post interesting, follow me (Vellanki Sriharsha) for more such interesting posts. #AI #Automation #Robotics #India #China #FutureOfWork #Innovation #PeterDiamandis

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Check out my writing on Substack.com. Perspectives Omnibus: An eclectic collection of insights, analyses, and viewpoints spanning a diverse range of topics. From deep dives into complex issues to reflections on the everyday, offering thoughtful and engaging writings about anything that captures the imagination. Substack #writing #substack

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Whether to include LLM-based GenAI features in your data product is not a simple, binary question. Strong leadership is needed, and context really matters—particularly when we have this risk of reacting to incorrect information that looks plausible and believable because of how many LLMs tend to respond to prompts with a positive sheen much of the time. Learn more below. ⬆️ Join 2k readers: tap “Visit my website” to get my latest thinking in your inbox 🚫 Don’t like LinkedIn’s algo deciding what you see? Tap the bell under my profile banner to get all my posts ♻️ Please repost if this was useful 🎧: https://bit.ly/3W5IddY #LLMs #genAI #ai #ux #design

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Evolving CDP Landscape: A Reminder of How CMSes Evolved We’ve seen a familiar story repeat itself in the tech world. The last decade was about headless CMSes, which emerged with claims to revolutionize CMS architectures and challenge traditional CMSes. In response, traditional CMSes began building headless capabilities, and headless CMSes started adding frontend (heads) capabilities. After all, a site needs both backend and frontend functionalities. Fast forward to the present with Customer Data Platforms (CDPs). Composable or DWH-native CDPs have made bold claims about being superior to so-called packaged CDPs. In turn, packaged CDPs have evolved their own data warehousing stories, building similar capabilities. Meanwhile, composable CDPs have started expanding their functionalities beyond just reverse ETL. Key Lessons: Nuance Matters: While broad capabilities are important, the nuanced differences between solution types—whether CMS or CDP—are crucial. These subtleties can significantly impact how well a solution fits your specific needs. More Options, Better Choices: For buyers, this convergence means more options. The differentiation that initially seems stark can blur, providing a richer array of choices to tailor solutions more precisely to business requirements. Beware the Hype: Buzzwords and initial hype around new technologies can be misleading. It's essential to look beyond the surface and consider the specific nuances and requirements of your own organization. In the end, flexibility and attention to detail are key. You should look closely at the nuances to make the best choice for your organization. #MarTech #CDP #CMS #DigitalTransformation #TechTrends #CustomerExperience #DataManagement

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Book a free meeting with one of our consultants to explore fascinating AI use cases that can help you decide how to best leverage AI at your organization.

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I think LLMs are amazing—they’ve blown me away from day one, which is why I jumped in as soon as ChatGPT launched. But as incredible as they are, I don’t think they’re enough on their own to get us to ASI or AGI. Sam Altman is hopeful, but anyone who has spent time using LLMs knows they make mistakes. Reaching true AGI will demand new models that go further—ones with memory, that can learn on their own, adapt, and do all this quickly and affordably. They’ll also need a real sense of what’s accurate or inaccurate, not just patterns to follow. On top of that, there’s a major hardware, cost and energy consumption bottleneck: we’re hitting the limits of Moore’s Law with GPUs and CPUs, which can only be shrunk and optimized so far. This hardware plateau is a serious hurdle for the growth AI needs to truly evolve. Without these breakthroughs in both hardware and intelligence, LLMs are likely to hit a ceiling before they can take us much further. All of that said, here's a great interview with Sam Altman. Let's see if I end up being wrong on this. What do you think?

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Tired of AI recommendations pushing you to the vendors offering the advice? Here's an independent, tech platform agnostic guide to populating your AI roadmap with some meaningful detail: 1. Take Credera's vendor-neutral assessment and get a view in five minutes 2. Pinpoint where you need to increase your focus 3. Read the content recommended to get you to the next level Get started by taking the assessment now:

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Join me and Pete Pacent on a webinar next month where we'll unpack an AI operating model to help you move past prototype and into production!

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Had a great conversation with radio host Gary Scott Thomas on all things emotion AI, digital transformation, cross-cultural communication, and AI ethics. Tune in below to learn more about Valence's journey!

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We read 100+ enterprise generative AI RFPs so you don't have to. And seriously: the best enterprise orgs have their act together — they don't need a government telling thing how or when to do AI responsibly. We recommend organizing your thinking around responsible AI in a matrix with four areas of obligation: data models systems operations ✅ Guardrails within the “data” category include data integrity, provenance, privacy, storage, and legal and regulatory compliance; and include ALL types of data the system will touch, not just training or data for RAG (other post on this in comments) ✅ In “models,” they’re training data transparency, accuracy, bias, toxicity, and misuse. ✅ In “system,” they’re security, reliability, customization, traceability, auditability, and configuration. ✅ And in “operations,” they’re the software development lifecycle, testing and validation, access + other policies (human and machine), and ethics. In your internal guidelines, each category should include key questions your leaders need to ask to clarify the stakes and articulate what "good” looks like. These will help you articulate risks, define success, and establish measurement. Security, transparency, and accountability in AI is everyone’s responsibility. This month in Fortune, I share the approach above in detail — to help every organization establish its own policies and ethical standards. And yes, to write your own RFP against your policies, including what questions to ask. Unpaywalled article in comments (thank you Fortune). http://bit.ly/4cflqlm Let me know if you'd add anything.

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https://lnkd.in/gdzFKhb6 New AI unicorns skew young: 30% are “early-stage” companies, compared to just 11% of their non-AI counterparts.

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The essence of leadership lies in harmonizing vision with action. Exceptional leaders go beyond setting high-reaching objectives; they cultivate an environment where their teams can proficiently bring these goals to fruition. Balancing a strategic vision with a hands-on approach is pivotal. It ensures that the implementation is in sync with the overarching strategy, nurturing a supportive and empowered team culture. How do you navigate the delicate equilibrium between strategy and execution in your leadership voyage? #Leadership #TeamSuccess #StrategicVision #Execution Read more: https://lnkd.in/ezWNAc5K

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