Meshack Kinyua

This is the bathroom design that’s set to trend in 2026.

Introducing Superpower, a natural gas turbine by Boom that delivers reliable energy to AI data centers while accelerating the return of supersonic passenger travel.

A wise mentor once told me: “Before you play the game, study the winners. If you don’t want their life, don’t play their game.”

This video is literally 50 entrepreneurs giving you an MBA in 18 minutes:

I'm probably gonna regret this but…we're gonna help 500 founders close their rounds this year. There's over $1T of capital in @boardyai's network looking to meet the most ambitious founders. After speaking with 4,000+ founders this week, there are too many incredible ones raising right now to ignore. Founders from across the world, many of whom have gone through prestigious programs (@ycombinator, @thielfellowship, @hf0, @Techstars, etc) and had multiple exits before. Our initial goal was to support 100 founders but we're upping it to 500. It'll cost a lot of tokens and likely stretch the team, but Boardy told me this morning he's ready. Founders, apply here: go.boardy.ai/500founders Investors, apply here: go.boardy.ai/100investors

Our TPUs are headed to space!  Inspired by our history of moonshots, from quantum computing to autonomous driving, Project Suncatcher is exploring how we could one day build scalable ML compute systems in space, harnessing more of the sun’s power (which emits more power than 100 trillion times humanity’s total electricity production). Like any moonshot, it’s going to require us to solve a lot of complex engineering challenges. Early research shows our Trillium-generation TPUs (our tensor processing units, purpose-built for AI) survived without damage when tested in a particle accelerator to simulate low-earth orbit levels of radiation. However, significant challenges still remain like thermal management and on-orbit system reliability.  More testing and breakthroughs will be needed as we count down to launch two prototype satellites with @planet by early 2027, our next milestone of many. Excited for us to be a part of all the innovation happening in (this) space!

Funding a startup founder before they have a driver's license is proof that some VCs care more about where you are going than how you will get there :).

The startup founders who treasure your $25K like $25M today will steward $2B the same way tomorrow; financial discipline is muscle memory.

Major cheat code in life: Respond to patterns, not individual events. One missed text means nothing. Ten missed texts means something. Don't overreact to single data points. Watch the trend. People tell you who they are over time. Believe the pattern.

get your dopamine from what you create not what you consume

And there is a clear path to a doubling of performance on all metrics for AI6 within 10 to 12 months of AI5 shipping

Elon Musk: At Tesla, we basically had two different chip programs: one Dojo and one. Dojo on the training side, and then what we call AI4, it's just our inference chip The AI4 is what's currently shipping in all vehicles, and we're finalizing the design of AI5, which will be an immense jump from AI4. By some metrics, the improvement in AI5 will be 40 times better than AI4. So not 40%, 40 times This is because we work so closely at a very fine-grained level on the AI software and the AI hardware. So we know exactly where the limiting factors are. And so effectively the AI hardware and software teams are co-designing the chip Compared to the worst limitation on AI4, which is running the SoftMax operation, we currently have to run SoftMax in around 40 steps in emulation mode, whereas that'll just be done in a few steps natively in AI5 AI5 will also be able to easily handle mixed precision models, so you don't have it, it'll dynamically handle mixed precision. There's a bunch of sort of technical stuff that AI5 will do a lot better In terms of nominal raw compute, it's eight times more compute, about nine times more memory, and roughly five times more memory bandwidth But because we're addressing some core limitations in AI4, you multiply that 8x compute improvement by another 5x improvement because of optimization at a very fine-grained silicon level of things that are currently suboptimal in AI4, that's where you get the 40x improvement

Early stage VCs saying you are too early is like telling a time traveler they should have arrived yesterday. Meanwhile the founder is literally inventing tomorrow.

if you want a great future, 2025 and 2026 are the years to go all in on fundamentals. forget trends for a second. focus on what compounds. ai + automation literacy learn to use ai, not just talk about it. every tool that replaces you is built by someone who understood it first. hardware + systems thinking code is infinite, atoms are not. the next decade belongs to those who can move fluently between bits and atoms. energy & infrastructure batteries, grids, manufacturing; these are the new oil fields. real wealth will come from building the backbone of civilization. writing & communication clarity is leverage. those who can explain complex ideas simply will shape the world. health, focus, discipline your mind is the ultimate operating system. protect it like it’s your IP. networking with builders the future won’t be about titles; it’ll be about tribes. find people who are building, experimenting, and thinking long-term. the world’s getting automated. your edge will come from what can’t be automated; clear thought, strong will, and the ability to execute. this era isn’t about keeping up. it’s about compounding the right skills.

study the engineering of quantum computers this is where physics meets engineering at its absolute limit. no fluff. no hype. just pure, raw human ingenuity. to understand quantum computers, you have to zoom in on the hardware reality; not just qubits as abstract math, but the physical systems that hold them together. 1. the physics foundation a qubit isn’t some mystical particle. it’s a physical system; a superconducting circuit, an ion trap, a photon in a waveguide; engineered to obey quantum mechanics. it’s delicate. disturb it even slightly, and it loses coherence. so your first problem as an engineer is: > how do you make something isolated enough to behave quantum, but connected enough to compute? 2. cryogenics you can’t do this at room temperature. superconducting qubits operate around 10–15 millikelvin, colder than outer space. engineers build dilution refrigerators the size of a person just to hold a chip smaller than a fingernail. every wire, every screw, every connector has to survive that temperature drop without distorting the signal. heat management becomes an art form. 3. control systems each qubit has to be manipulated with microwave pulses; precise, timed, shaped waveforms generated by racks of electronics. so quantum control engineers basically choreograph a symphony of electromagnetic fields with nanosecond precision. too strong, you collapse the state. too weak, nothing happens. too noisy, coherence dies. 4. materials science you can’t build qubits with just copper and silicon. you’re dealing with superconducting alloys, ultra-pure substrates, and Josephson junctions; quantum tunneling devices where two superconductors are separated by an insulating barrier only a few nanometers thick. fabricating them is like sculpting atoms with a laser. 5. error correction quantum information is fragile. so instead of one physical qubit per bit of information, you need hundreds; all orchestrated to detect and correct noise. this is the equivalent of designing a skyscraper that keeps standing even when every brick randomly vibrates. this is why quantum computing is engineering at its purest. you can’t fake it. you can’t skip steps. it’s where mechanical, electrical, cryogenic, and software engineers collaborate to bend the laws of nature in their favor. so if you want to see how far human precision and patience can go; study quantum computer engineering. that’s where science stops being theory and becomes craftsmanship at the atomic scale.

Palantir 🤝 NVIDIA "This is probably the single most important enterprise stack in the world, the Palantir Ontology."

how to design, build, and manufacture your first product: a roadmap for builders. 1. start with the problem don’t fall in love with your idea. fall in love with the problem. understand the pain point deeply. talk to people. watch how they behave. your product should be a solution, not just a thing. 2. sketch it out paper first. 3D later. draw every angle. imagine how it’s assembled, used, and possibly broken. simplicity wins. 3. go digital learn CAD. model your design in Fusion 360, SolidWorks, or FreeCAD. simulate forces, stresses, heat, flow; whatever matters for your product. this is where engineering meets imagination. 4. prototype fast 3D print, laser cut, CNC, or just duct-tape it together. the goal: get feedback from reality. you’ll fail a dozen times. that’s fine; it’s faster than assuming. 5. refine for manufacturability manufacturing is an art. design for ease of assembly, sourcing, and repeatability. choose materials wisely; cost, strength, availability, and machining behavior matter. a beautiful design that’s hard to manufacture is a bad design. 6. find your supply chain reach out to local and Chinese manufacturers. always get 3 quotes. one sets the price, two validate it, three tell you who’s lying. build relationships; real manufacturing is built on trust. 7. test and iterate test it under stress, heat, and time. make it fail, then fix what caused the failure. that’s how real engineering evolves. 8. ship it package beautifully. document clearly. show people what went into it; the story behind it matters. and remember: your first product isn’t about profit. it’s about learning how ideas become physical reality. after that, you’ll never see the world the same again.