- Artificial Intelligence (LLMs, AI agents, and the future of human expertise)
- Blockchain (Decentralized infrastructure, networks, and ecosystem evolution)
- Data Engineering (Building data infrastructure that actually scales)
- DevOps (Infrastructure, automation, and operational philosophy)
- General (Culture, science, and the miscellaneous)
- Retro Computing (The machines and culture that shaped computing)
- Music Production (Gear, sound design, and creative workflow)
- Personal Development (Expertise, craft, and the engineering mindset)
- Space (Infrastructure and vision for human expansion beyond Earth)
From Awakening to Action: Building the Life You've Discovered
The Space Between Knowing and Becoming There is a particular moment in the journey of personal transformation that nobody quite prepares you for. It comes after the awakening - after you have seen clearly what matters, remembered who you are, and felt the profound sense that something fundamental has shifted inside you. And then reality arrives. The bills still need to be paid. The old habits are still there, waiting at 3am. The people around you haven’t changed, even though you have. The clarity you felt so vividly in that moment of insight begins to blur against the texture of ordinary Tuesday afternoons. ...
Career-Ops: Flipping the Script on AI-Powered Job Search
The job search has long been a one-way mirror - companies deploy AI to filter applications while candidates manually juggle spreadsheets, tailor cover letters, and hope their resume gets past the automated screener. Career-Ops flips that script entirely. Built on Claude Code, it’s an open-source system that gives job seekers their own AI advantage: intelligent evaluation of opportunities, automated customized applications, and systematic candidate strategy. The Problem It Solves The traditional job search is a grind of low-signal noise. You find 30 job postings. You read them. You customize a resume. You write a cover letter. You track applications in a spreadsheet. You wait. You compare offers using gut feel and spotty spreadsheet columns. The process burns time and attention - exactly when you need both to think clearly about your career. ...
AWS S3 Files - Bridging File Systems and Object Storage
Amazon Web Services recently introduced AWS S3 Files, a service that addresses a persistent challenge in cloud computing - how to give file-based applications direct access to object storage without duplicating data or building custom connectors. The Problem S3 Files Solves Traditionally, applications designed around file systems faced a difficult choice when working with Amazon S3: Use object APIs - Build custom integration code and refactor applications Duplicate data - Copy data between S3 and separate file systems, creating sync challenges and increased costs Accept performance trade-offs - Work with slower, network-dependent access patterns S3 Files eliminates these constraints by providing a native file system interface directly over S3 data. ...
Cline + Kanban: Autonomous Development Meets Project Management
In the evolution of agentic software engineering, one critical gap remains: the disconnect between project management and code execution. Your Kanban board tracks what needs doing, but your AI assistant lives in your IDE. Cline + Kanban closes that gap. The Problem: Two Separate Systems Most teams operate with a frustrating split: Kanban board (Linear, GitHub Projects, Jira, Trello): “Build the user authentication flow” IDE with Cline: “Let me write code” Manual sync: You paste the task, manually update the board status, context-switch constantly This handoff is where developers lose hours to context-switching and where tasks fall through the cracks. ...
Structured Outputs: When Your AI Needs to Follow a Schema
For years, extracting structured data from LLMs meant post-processing their text output: parse JSON, handle edge cases where the model forgot to close a bracket, write validation code to check if the output matched your schema, implement fallback logic when parsing failed. Then came structured outputs - a way to constrain LLM responses to match a JSON schema before they’re returned to you. Structured outputs sound simple but represent a fundamental shift in how to build production LLM systems. And yet, most teams are still extracting data the old way - waiting for the post-processing disasters that guaranteed outputs prevent. ...
The LLM Context Window Arms Race: Does It Actually Matter?
Every week brings a new headline: “Model X reaches 1M token context!” “Model Y supports 2M tokens!” The LLM industry seems locked in an arms race where the stated goal is always “bigger context window,” as if this single metric determines whether a model is useful. It doesn’t. The context window arms race reveals a gap between what engineers think matters and what actually works in production systems. And if you’re building with LLMs, understanding that gap will save you from infrastructure that doesn’t solve your problems. ...
What Comes After Artemis: The Road to a Lunar Gateway
The Gateway Concept When most people think of returning to the Moon, they imagine Artemis astronauts landing, collecting samples, and returning home - just like Apollo. That’s the goal for Artemis III and IV. But NASA is building something different for what comes after: the Lunar Gateway. It’s not a destination in itself. It’s infrastructure - a way station in lunar orbit that changes how humans explore the Moon forever. ...
Token Economics: Why the Cost of AI Isn't Going Down
There’s a persistent myth in tech: AI will get cheaper. The argument is straightforward - Moore’s Law, scale effects, competition, and raw compute efficiency improvements mean costs should plummet. Yet in April 2026, Claude costs roughly what it did in 2024. GPT-4 Turbo pricing hasn’t moved in eighteen months. Gemini’s cost structure remains sticky. Why? The answer isn’t that progress hasn’t happened. It’s that the economics of modern AI are fundamentally different from hardware commoditization. Once you understand the actual constraints, the stability of pricing becomes logical. ...
How BASIC Shaped a Generation of Programmers
How BASIC Shaped a Generation of Programmers When you powered on a Commodore 64 in 1983, the first thing you saw was: READY. Blinking cursor. No graphical interface. No visual metaphors. Just BASIC - a programming language that wasn’t supposed to be the foundation of computing education, but became exactly that. BASIC shaped how an entire generation thought about programming. Not because it was the best language, but because it was the only language available on personal computers. If you wanted to write anything on your C64, your Spectrum, your BBC Micro, or your Apple II, you were writing BASIC. And when constraints force a population into a single tool, that tool becomes the culture. ...
The Most Valuable Skill Is Knowing What Not To Build
Every builder knows the feeling. You have an idea. It’s clever. It could be useful. You start sketching it out, planning the architecture, imagining how it would work. Then you stop. Not because it’s impossible. Not because you lack the skill to build it. But because something inside you says: This is not worth building. That instinct - that ability to say no - is rarer and more valuable than knowing how to build something well. ...