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“Red Friday” marked the largest liquidation event in crypto history, nearly $19 billion erased in a single day amid renewed U.S., China trade tensions. Yet what makes this episode remarkable is not the size of the sell-off but its limited effect: Bitcoin fell only about 8%, a far cry from the 58% crash of March 2020 or the 19% slide after FTX collapsed in 2022. For the first time, the market absorbed massive leverage unwinding without imploding. The combination of deeper liquidity, institutional participation, and new instruments such as ETFs has begun to tame the asset’s once-violent swings. ...

Over the last year the workflows vs. agents debate has turned from a niche engineering question into something every product team seems to argue about. New tooling lowers the barrier to spin up an AI agent that can call tools in a loop, so leaders start asking whether they should rebuild processes around these agents, or stick with the safer structure of step-by-step workflows. The conversation heats up because both sides have real wins and real failure modes: agents feel magical when they solve fuzzy, open-ended tasks, but they can be slow, costly, and unpredictable at scale; workflows are efficient and auditable, but can feel rigid when the job needs exploration. That tension between flexibility and control is why this topic is hot and why teams keep getting stuck. ...

Bloomberg just published this fascinating map of the AI power network, showing how companies like NVIDIA, OpenAI, Microsoft, AMD, Oracle, and Intel are now intertwined through billions in deals, compute, and equity. It’s not just a supply chain anymore. It’s a feedback loop — where hardware, software, and capital keep feeding each other. NVIDIA sits at the center with a $4.5 trillion market cap, investing up to $100 billion in OpenAI, while selling GPUs to Oracle, AMD, xAI, and everyone else. OpenAI, in turn, signs a $300 billion cloud deal with Oracle, deploys 6 gigawatts of AMD GPUs, and gives AMD an option to buy 160 million OpenAI shares. Microsoft is still the connective tissue, part investor, part service provider, part enabler.

I came across a video by Dr. John Padfield, a former engineer and state representative, talking about something that stuck with me. He recalls being told, “never get in a fight with people who buy ink by the barrel.” It was a warning for politicians — don’t mess with newspapers. Then he updates it for our time: “Never get in a fight with people who buy network servers by the acre.” ...

Visual Capitalist just released this updated chart of the 50 largest companies in the world (July 2025) — and it’s another reminder that software really did eat the world. The top 5 companies are all in tech: NVIDIA, Microsoft, Apple, Amazon, and Alphabet. Together, they’re worth more than most countries’ GDPs. NVIDIA alone — the company powering the AI boom — now sits at $4.2 trillion, ahead of everyone else. ...

We live in a world that’s more connected than we often realize. Roads, flight paths, shipping routes — these invisible networks shape how we travel, trade, and share ideas across the globe. Peter Atwood created a series of satellite maps that strip away everything but those connections. The result is a striking view of how humanity has built, expanded, and reshaped its presence on Earth over the past 150 years. ...

Time Between Disengagements is a concept I came across in a recent article from Gitpod, and it offered an interesting new way to think about AI’s role in software development. It compares the evolution of AI in engineering to the progression of self-driving cars—where the key metric is how long an autonomous system can operate before a human needs to step in. That simple but powerful analogy really clicked with me. It reframes how we should think about the future of AI-assisted development—not just in terms of raw capability, but in how independently and safely these systems can work. ...

Why do we glorify complexity and look down on simplicity — especially in tech? I wanted to share this because it resonates with so much of what I’ve experienced and observed in tech myself. In Joan Westenberg’s thought-provoking piece, “Why Simplicity Offends Tech Elites”, she explores the curious tendency within tech circles to glorify complexity and dismiss simplicity as somehow less valuable. Reading this, I was struck by how deeply embedded this mindset is in startup and developer culture — where convoluted solutions, obscure tools, and overly engineered systems are often seen as badges of honor. Westenberg challenges this mentality, arguing that simplicity should not be mistaken for laziness or lack of depth. In fact, true simplicity is hard-earned — it requires clarity, discipline, and empathy for users. ...

In Industrial IoT (IIoT) environments, devices often operate in remote, resource-scarce locations with intermittent connectivity and minimal hardware—conditions that demand lightweight, resilient software solutions. These edge deployments typically involve devices with less than 1GB of RAM, limited CPU power, and basic storage like SD cards, yet they must run reliably and autonomously. KubeSolo was designed precisely to meet these challenges. As a single-binary Kubernetes distribution, it’s carefully optimized to function efficiently in such constrained conditions, typically requiring only around 200MB of RAM. This makes KubeSolo an ideal solution for IIoT scenarios, delivering the power of Kubernetes at the edge without overwhelming the hardware. ...

Startups are often drawn to microservices with the promise of scalability and flexibility, but adopting them too early can backfire. Microservices introduce overhead—more infrastructure to manage, more complexity in deployments, and more effort in monitoring and debugging. For small teams moving quickly, these challenges can slow progress rather than support it. Early on, simplicity is a major advantage. Keeping your architecture lean—whether that’s a monolith or a tightly scoped service—allows you to move faster, iterate quickly, and focus on building the product. The key is not to avoid microservices altogether, but to recognize when the benefits truly outweigh the costs. Premature optimization can lead to a fragile setup that’s hard to maintain without delivering real value. ...