For many Europeans visiting the U.S., seeing the iconic yellow school buses for the first time feels like stepping into a movie scene. Something so familiar from American culture suddenly becomes real right in front of them. It’s interesting how everyday things can become exciting discoveries when viewed from another perspective. A simple school bus represents a piece of daily life, history, and tradition that many people have only seen on screens. Travel allows us to appreciate the little details we often overlook. Who would have thought a yellow bus could become one of the most memorable parts of someone’s trip?

The lesson I take from the SpaceX IPO is that the only thing stopping us from solving arbitrarily difficult problems is extreme creativity in business models. No amount of tax and spend programs got us reusable rockets and great electric cars. Customer delight is a necessary precondition for success. There seems to be some discussion around whether successful entrepreneurs should give up control of their companies so they can subsidize some philanthropic venture that otherwise has no value prop sufficient to run it as a business where customers voluntarily exchange money for goods and services at a competitive and reasonable price. This misses the point. Transformational products deliver tangible value at 1000x the rate of charities whose value cannot be tested in the market place. Think about the undeniable value of the smart phone, satellite Internet, electric consumer devices, etc etc. I think the transformational moment for SpaceX was when Elon stepped away from the philanthropic Mars greenhouse concept and fixed his resolve on unlocking radically better rockets for humanity. The greenhouse would have been, at best, a neat trick. Falcon and Starship give humanity a durable economic engine to maintain and improve access to space, forever.

There’s an iconic line from the movie Up In The Air: “How much did they pay you to give up on your dreams? And when were you going to stop and do what makes you happy?” Look, we all have bills to pay. We do what we have to do to make ends meet and put food on the table. Providing is something to be proud of, but… Don’t sacrifice your dreams along the way. Don’t wake up at 50 (or 60) and realize you’re no closer to your best life than when you started. 👉 Treat your job as a means, not an end. Slowly—over years and decades—gain more control. Become the person you are on vacation. That’s the real you. Now you’ve got a life you don’t need to escape. (P.S. I’m not talking about living a life of leisure. Humans need work and skin in the game. The goal isn’t to retire—it’s to choose your work and do it on your terms. That’s as good as it gets.)

The takeaway from Fable 5 being BANNED by the government: GET GOOD AT LOCAL MODELS SO YOU HAVE 100% CONTROL. My entire weekend was going to be building my craziest ideas with Fable 5. That's now cancelled. So instead of building with Fable this weekend, I've decided I'll go deep on local models: 1. Start with the runtime. Download Ollama or LM Studio first. This is the thing that actually runs models on your machine. 2. Match the model to your hardware. A model's size is measured in billions of parameters (7B, 32B, 70B). Bigger is smarter but needs more memory. Rule of thumb: a 7B model runs on almost any laptop, a 32B needs a good Mac with 32GB RAM, a 70B needs serious hardware like a DGX Spark or a maxed-out Mac Studio. 3. Know which model for which job. Qwen 3 is the best all-around choice for most tasks. DeepSeek for reasoning and coding. Gemma 4 when you need something tiny that runs on a phone. Llama when you want the biggest community and the most fine-tunes. 4. Quantization. You can shrink a model to run on weaker hardware with barely any quality loss. Look for versions labeled Q4 or Q5. This is how a model that "needs" a server runs on your laptop. Learning this one concept changes everything. 5. Connect it to your agent. Point Hermes or your agent stack at a local model. 6. Context window is your real constraint locally. Cloud models give you huge context for free. Local models make you pay for it in memory. A bigger context window eats RAM fast. Keep your sessions tight and your prompts lean or your machine chokes. 7. Learn to give local models tools. A smaller local model with web search, file access, and code execution beats a giant model with none. The capability gap closes fast when you wire up the right tools. The model is the engine but the tools are the wheels. 8. Fine-tuning is more accessible than you think. You don't need this on day one, but know it exists. You can take an open model and train it on your own data so it gets good at your specific domain. I'll probably do a breakdown at some point on this @startupideaspod if people are into it. The lesson from this ban is basically don't build your entire workflow on something that can disappear with a single letter. Own part of your stack. Local models are insurance. It reminds me when people realized they don't own social media accounts. And then you saw people build email lists etc. I remember running a startup and my biggest traffic source was organic FB. All of a sudden, algo changed, and I lost 99% of my traffic. Same sorta moment (but bigger) for AI. This is a wake up call.

This is why I fled South Africa and came to seek refuge and safety in America