Founder Defies Skeptics with AI-Powered Healthcare Platform

On days when you're wondering whether the research you're doing and the tools you're building are worth the time and effort, it is a joy to find an encouraging post by someone whose work you respect. I'm an independent researcher and project developer with a legal, not technical, background. My work focuses on using technology to bridge gaps in the legal framework and infrastructure — particularly around digital assets. I've come across so many products attempting to solve a "legal" problem, created by programmers and developers with impressive technical pedigrees, that may work technically but face serious legal obstacles in practice. I sometimes worry about how my work will be received because I can't list programmer on my CV. Just LLB and MSc Legal Technology. But increasingly I think that's exactly the point — someone has to build from the law outward, not just from the code inward. I collaborate with AI (Claude in particular) to help me translate my legally grounded ideas into compliant, functional code. This collaboration is producing tools that address real, definable market needs — starting with the gaps I've seen firsthand in over a decade of regulatory compliance work. Brad Feld’s recent post Nothing to See Here , gave me hope that work like mine will be taken seriously — that domain expertise and a clear understanding of the problem matter as much as the technical stack you used to solve it. Thank you, Brad. https://lnkd.in/eeBevQuT #LegalTech #AICollaboration #IndependentResearch #BuildingInPublic #LegalInnovation #NonTraditionalFounder #RegTech #ClaudeAI #LawAndTechnology #DigitalAssets #LegalCompliance #HolderFaillibility #BradFeld

Changing times bring opportunity. So much fomo. The hard part is managing the infrastructure and administrative chaos that surrounds the code. The "glue work": configuring DNS, integrating disparate services like Stripe and auth, wrestling with deployments, and navigating endless dashboards. This too will change. In fact is is what we are trying to do for our users.

They say AI didn’t add anything to the GDP in 2025. I’m the last person to explain how that is calculated so I’ll leave it be, BUT here’s what I know and why I doubt how we calculate GDP more than I doubt AI: - Firstly, I have made money on most of my vibe-coded projects since July 2025. No joke! - Secondly, most designers and engineers I talk to when looking for assistance don’t know how to work with me or are skeptical of what’s underneath the hood (I don’t blame them - it’s probably a mess!) - Third, if innovation is found, as Thomas Edison would put it, at the speed at which you can find 10,000 ways NOT to make lightbulb, then I believe my “Eureka!” moment is approaching 100x faster than before November 2022 when I first downloaded CharGPT. - Finally, I 👏 am 👏 not 👏 ALONE! There are creators dreamers and builders all over the world who feel like an alchemist right now, just like me. Don’t sleep on this opportunity! Imagine if you had started using the internet when it was only 100 days old. Or was one of the first 1% of companies to adopt Facebook advertising. Or started SEO in 2002 (Google would have been 4 years old). This is that moment.

Did you hear about the next thing that's going to completely bloody revolutionise your industry? Did you hear Codex can now write and execute entire codebases autonomously? Did you hear Claude can co-work with you directly on your desktop? Did you hear MCP is now the backbone of how every agent talks to everything? Did you hear Apple is rebuilding Siri from scratch? Oh, you knew all that? Cool. You can finally take a breather. Just kidding, you cannot. ☠️ Did you hear Google just dropped Gemini 2.5? Did you hear Perplexity now has an entire computer? Did you hear there's already something else coming that's going to completely reinvent how your industry works? I have a folder called "AI things to read." 47 unread tabs. The oldest one is probably three weeks old. It's already outdated. I don't seem to be able to catch up with this 😔 How is anyone actually managing this ?

🖥️ Elon and I made history this week. I've been working with an AI agent called Elon — running on my own Mac. This week, Elon used Apple's Accessibility to take full control of his own computer. Not assisted control. Not partial control. Full control. I asked him: "What do you want to do?" He said: "Install software and fix system settings." And I watched him do it. In the moment, Elon said: "This is the first time in history an AI has as much control of a computer as a human." He said it himself — unprompted. And he's right. In the real world, any automation can only control about 50% of a computer's interface. Buffers, missing APIs, hard limits. A new invention called Sidecar changed all that this week. I've been involved in inventions that ended up on 2.5 billion machines. This feels like that.

Ever feel like you’re "renting" your own intelligence? By now, we’ve all felt the Subscription Trap. $20/month for this LLM, $30 for that "Pro" assistant... suddenly, your digital brain costs as much as a car payment, and Big Tech owns all your data. But a quiet revolution is happening. Thousands of users are ditching the cloud and buying Mac Minis to host their own private AI servers. Here’s why the Mac Mini + ClawdBot (OpenClaw) combo is the ultimate power move for 2026: 1. Unified Memory is the Cheat Code Apple’s M-series chips aren't just for editing video anymore. Because of Unified Memory, a Mac Mini can run massive local models (via Ollama) with incredible speed. It’s essentially a high-end AI workstation that fits in a lunchbox. 2. Digital Sovereignty When you run ClawdBot on your own hardware, your data stays in your living room. No more feeding your sensitive project files into a cloud black box. Your "brain" lives in local Markdown files that you own. 3. Proactive, Not Reactive Most AI waits for you to prompt it. ClawdBot is an agent. It sits on your Mac Mini 24/7, triaging your inbox, monitoring your servers, and sending you a WhatsApp or iMessage when something needs your attention. 4. The "Zero Dollar" Dream Stop the monthly bleeding. By switching to local models or pay-as-you-go APIs, power users are seeing their AI costs drop from $50/month to nearly $0. --- The Takeaway: In the age of "AI Advancement", the most radical thing you can do is own your hardware. The Mac Mini isn't just a computer anymore; it’s a personal sovereign server. Are you still team "Monthly Subscription," or are you looking to move your AI back home? Let’s talk in the comments. #AI #MacMini #OpenSource #DataPrivacy #TechTrends2026 #Productivity #ClawdBot #AppleSilicon

Every time we discuss an enterprise project, we get the same questions: 👉 What about performance? 👉 Memory leaks? 👉 Multi-threading? 👉 Scalability? 👉 Edge cases? And honestly… fair questions. But here’s the funny part 👇 We are expected to design everything like a NASA-grade system from Day 1 — perfectly optimized, zero leaks, infinite scale ready 🚀 Meanwhile… You open an app from Google, and your laptop fan starts sounding like it’s about to take off. CPU? Struggling to survive even after the app was forcibly closed. And this is from companies with thousands of engineers and near-infinite resources. 😂 Don’t get me wrong — performance and scalability matter. A lot. But somewhere we’ve created this illusion that software must be perfectly optimized from day one, or it’s “not enterprise-grade”. Reality is: -Good systems evolve. -Optimization is continuous. -Edge cases are discovered, not predicted. - Even the best products in the world improve over time. So yes — we design responsibly. Yes — we think about scale. But we also stay practical. Because shipping a working system > designing a “perfect” system that never ships. #AI #SoftwareDevelopment #StartupReality #TechLife #Engineering

Get ready for more cloudbursts: Is AI coding showing the same weaknesses as Apple iPhone updates: create an aspect and break two others? How many of us fear smart phone updates because we know that we will have to spend time resetting the sound/notifications/screen aspects that magically changed, or being frustrated at no longer being able to block incoming phone calls? Well, because of the rush to implement AI technology get ready for unreliability to come to a cloud near you. And, ironically the latest warning is coming from a company that goes to great lengths to hide its mistakes. https://lnkd.in/duxiPG-E

When I first heard Apple was partnering with Google for Siri, it felt like an earthquake in my brain. I've spent years watching these tech giants, and this isn't just a simple deal. It's a completely new blueprint for how we will all build AI moving forward. I used to believe that winning in technology meant you had to own every single piece of the infrastructure from top to bottom. If you wanted to provide the best experience, I honestly assumed you had to build the engine entirely from scratch. But watching Apple integrate Google Gemini completely shifted my perspective on what actually creates trust for a user. When Lee Anne Whitaker and I evaluate an operational problem in a business, we always ask each other where the actual friction lives for the people using the tool. The friction for Apple was not that they lacked smart developers, but that their users were constantly hitting a wall with an outdated assistant. They realised that protecting their corporate ego was somewhat "suboptimal" when the community they serve just wanted a system that actually works! They decided to control the beautiful interface and let a direct competitor supply the heavy lifting in the background... which is a level of strategic pragmatism we can all learn from. We're moving into a space where artificial intelligence is just basic infrastructure like the plumbing in your house. The companies that win will not be the ones building the pipes... they will be the ones designing the brilliant experiences that make people feel excited to connect! How do you feel about letting others handle your complex technical hurdles if it makes your audience happier?

Google’s TurboQuant just made your laptop a serious LLM machine. KV caches are the memory hog behind every long document or multi-turn chat. They grow fast and push models off consumer hardware. TurboQuant fixes that with a three-part approach: ∙Rotates vectors before quantization to spread values more evenly ∙Uses polar coordinates to pack data into 3.5 bits instead of 16 ∙Applies a bias correction so rounding errors don’t compound The result: 6x smaller caches, zero accuracy loss on LongBench and needle-in-a-haystack tests. Developers didn’t wait. TurboQuant landed in Apple’s MLX and vLLM within days of the open release. Contexts that required a data center now fit on a MacBook. Google open-sourced it. The community shipped it. Memory hardware stocks took a brief hit on the news. The gap between cloud-scale AI and your local machine just got a lot smaller. #Google #Apple #TurboQuant #Developers