Nate Ebel

If there’s any low level coders in my network please check out Troy’s GitHub and his project to build a new, faster shell! Some details on Troy: ### Windows Accessibility and TTS Contributions (Red Eagle Team) - Description: As part of the Red Eagle Team (a Georgia-backed initiative with Microsoft support in the mid-2000s), Mallory developed foundational code for universal Text-to-Speech (TTS) systems and cross-platform handicap accessibility features. This included compatibility layers for screen readers, app navigation, and voice input (e.g., influencing tools like Dragon NaturallySpeaking). - Impact on Windows: Microsoft adopted and evolved his logic starting with Windows Vista, integrating it into core OS features for impaired users. If you've used modern Windows TTS, clipboard integrations, or basic accessibility navigation, elements trace back to this work. - Modern Extensions: He's currently exploring IoT/smart home integrations for disabled veterans, building on this foundation. Troy’s Post “Okay guys think tank. I maybe over complicating this or may habe to do a bit of tweaking with some C code. Rubian has been going smoothly. The new boot and dynamic system discovery deamons work great. As standalone. The new stack needs tweaking for efficiency but works and is stable. Here's the stack im working on with the prototype test. /etc/rc.local ->calls boot.rb as bg process. ->boot.rb bootstraps rubian's system discovery and array logic. User login -> rubian3.rb (repl) -> chsh -s ./rubian3.rb USER Rubian boot.rb logic. ->starts C ruby and Jruby C ruby starts the bootstrap process while jruby warms up. -> Cruby passes workload to jruby when its ready to finish boot system. The deamon system is the server-side, where shells and env are the client. (See my UNIX socket prototype here) https://lnkd.in/gf6rWs46 C and j ruby can now natively talk to each other. I know that works. The issue im having is the new login shell isnt hooking into the deamon when it loads. https://lnkd.in/g5_2ZuPH A further explanation: “Yes. I've been building from the Shell working down to the kernel. The Shell side of things mimic Bash but in ruby expression. On the logic side of things, ruby treats everything as an object. What im doing is taking all the system information and building Arrays. Each directory and file then has an index that we can iterate through with .each_with_index, .each_with_object, etc. So instead of a static file tree, i have arrays of nested file paths and directories being pattern matched. Any ruby app will be ran and communicate to it. This allows for dynamic file utils systems and more. Each array index points to a file, directory, process, thread, interpreter, shell, hardware, everything that is a defined method object.”

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This was a good discussion about the Principal Engineer role at Amazon! I often say that the Principal Engineer role as it exists at Amazon simply doesn't make sense at smaller companies. To many, the title just means the next highest level of engineering skills. At Amazon, it requires dealing with high levels of ambiguity, business strategy, and organizational influence. If you're at a company with <50 people, the person with that level of influence should be leading the whole technical organization - it requires a significant amount of scale before it makes sense to have an IC role for it. I also personally appreciated Steve's points on internal level progression - or as Gergeley says, "Why being promoted from Senior to Principal at Amazon is one of the hardest jumps in tech." Steve: "Basically, to get from senior to principal, you have to do like two and a half level jump, from L6 to L7. Technically, it sounds like one level, but at some other companies, this might be like, you know, L8, L9 or L8 and a half. [...] I noticed that some of the best engineers that I'd ever worked with were having such problems getting to principal engineer that they ended up moving to Facebook or to Meta or to all these other places where the progression was sane. Now they're senior staff and, you know, principal and distinguished engineer at other companies. And so because we had high standards, we actually had this brain drain." In addition to the level itself being a big jump the promotion process is notoriously arduous and arbitrary. While I was L6, I had multiple managers over several years acknowledge that I was doing L7 work, and even agree that if I was being hired in from outside I would be hired at L7, and it was the internal promotion process that was the barrier. This was not the *only* reason I left Amazon, but it certainly made it very easy to do. Amazon has lost a lot of skilled engineers this way, but it's a difficult problem to fix, since the incentives are fundamentally badly aligned. If an L6 engineer is already doing the work that's needed, it's very hard for a manager to justify spending the 100+ hours of work it takes to advocate for their promotion. And while there have been attempts to make the process less arduous, no one wants to be seen as "lowering standards." I highly encourage engineers in that position to make it clear they will not be continuing to do work that way indefinitely. And I encourage leaders at other companies to learn from the example! https://lnkd.in/guC35n2B

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This is absolutely true. I would also add that just because AI decreases cycle time does not mean you should operate without a plan. To use an analogy, pretend you are going on a trip from New York to Los Angeles and fuel/electricity are free (or only cost pennies). Now imagine that you don't have a map but are just driving based on instinct. Because you are moving and the cost is low or zero, you feel you are getting somewhere even when you are not. You need a map (app or paper), or at least need to stop for directions occasionally. Movement, no matter the speed, is not progress unless it's toward where you want to go.

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Big news for Meta Neural Band owners! 🎉 Starting this week, we're rolling out a groundbreaking new way to message: writing with your finger on any surface (https://lnkd.in/g6t_9sPC). Imagine messaging as simply as you wrote in elementary school—no keyboards, no accessories, just you and the neural band. This isn't just a new feature; it's a fundamental step in the evolution of human-computer interaction. The neural band natively understands written text using human biology (EMG at the wrist), eliminating the need for users to learn a new interface (physical/virtual keyboards, touch screen UIs or mice). This is a new step in the paradigm shift from humans adapting to computers to computers communicating like humans. While much of the recent AI focus has been on language models and reasoning, the same underlying techniques have been taking perceptive AI to quite a mature level over the last 10 years. First it revolutionized computer vision (https://lnkd.in/gejhZ9Vu) and speech recognition (ASR, TTS). Beyond human senses, it enabled the processing of complex sensor suites that made applications like self driving cars possible (https://lnkd.in/ghxE2hvR). When we launched the Neural Band last fall (https://lnkd.in/gyuzRVeD), we proved for the first time that a consumer-grade device could accurately capture and process neural activations. Initial gestures were innovative, but handwriting is different. While finger differentiated taps and swipes could have arguably been implemented using other modalities, the richness and accuracy of the signal required for handwriting requires the high-information-entropy bandwidth unique to an EMG-based device. I can't wait for many of you to experience the "waouh, this is new!" feeling for yourself. While this is the culmination of 10 years of research (https://lnkd.in/gxm_gc3z), we're just getting started! Stay tuned for the even more exciting, next-level capabilities we are working on. #MetaNeuralBand #HumanComputerInteraction #PerceptiveAI #Innovation #EMG

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There are a lot of different levels of AI agent autonomy, but only one blanket term for what we’re calling these tools. That’s creating some confusion about where the space is headed next. Clear up the confusion with Sean Falconer’s new guide in VentureBeat! https://lnkd.in/eNYcveXg

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New to GitHub Copilot CLI or agentic tools? I built a 5‑minute, learn‑by‑doing Copilot CLI quickstart that runs inside your terminal. It’s beginner‑friendly for developers and non‑developers! 👉 https://lnkd.in/gmk8caXm No docs. No videos. Just an interactive Copilot skill that teaches you how to use the CLI and understand agent workflows step by step. If you’re curious about where Copilot CLI and agents are heading, this is a great place to start!

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In case you missed it - a little mini bio on myself: I’m a farmer and developer born in the MidWest, thrived in the Pacific Northwest and now developing/testing in Texas. I built FFT Nano to help independent farms compete and thrive. FFT Nano: Your farm's AI coworker. Three years in the making. Gatekeeper-free. Transforming agriculture from the ground up

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Continued thoughts on Per Aspera 001: The Return to the Guild As I’ve had more time to reflect on Dan Goldin’s Per Aspera 001 and this article from GitHub’s Branching Out_ channel—https://lnkd.in/gkp3u3TU “Why Developer Expertise Matters More Than Ever in the Age of AI”—I’ve been meditating deeply on the future of education, the ancient patterns of apprenticeship, and the soul of software engineering itself. We are, I believe, living through a strange paradox. On one hand, AI promises to accelerate development, automate boilerplate, and optimize workflows. On the other hand, the core of what makes a developer excellent—clarity of thought, principled design, architectural foresight—cannot be automated. These are not just skills. They are virtues. And virtues must be cultivated. The article rightly points out that developer expertise is becoming more valuable, not less, in this new age. I agree—but I’d go even further. Expertise is not just about efficiency or productivity. It is about craft. And that’s where our current institutions have failed us. The industrial education system, with its pre-packaged curricula and endless credentialism, has little to say about mentorship. About learning by osmosis. About failing nobly under the watchful eye of a master builder. The great developer is not born from YouTube tutorials or bootcamp sprints. They are born, like the blacksmith or stonemason of old, through the sacred rhythm of apprenticeship. I believe it is time to return to the guild. A place where elder technomancers teach the next generation not just how to code, but how to think. A place where principles like SOLID, Clean Code, and the Twelve-Factor App are passed down not as checklists, but as living traditions. A place where engineers are trained not only to build, but to bear the moral weight of what they build. Alternative education models—similar to the technology academy mentorship program I’ve experimented with in the past—point toward this future. A future that’s slower, deeper, and more relational. A future that values wisdom over trend-chasing, and character over hustle. In the end, this is the invitation of Per Aspera: to take the harder path. The path of craft. Of community. Of the sacred return to form. Because while AI may change how we build software, it cannot change who we are while building it. #PerAspera #SoftwareEngineering #DeveloperLife #TechLeadership #AlternativeEducation #MentorshipMatters #Apprenticeship #EngineeringExcellence #AIandDev #DevCommunity #FutureOfWork #SOLIDPrinciples #CleanCode #MoralTech #HumanCenteredAI #IndieDev #EngineeringWisdom #CodeAsArt

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Interested in learning more about Foundry Local https://foundrylocal.ai and how to build RAG-style systems that run locally? I’ve been exploring patterns for local-first retrieval, generation, and agent workflows, focusing on privacy, performance, and developer control. If you’re experimenting with RAG beyond cloud-only setups, these samples might be useful: • Local RAG – a simple, practical starting point for retrieval‑augmented generation running locally https://lnkd.in/e8DaV8ae • Local CAG – moving beyond classic RAG into contextual and agent‑driven generation patterns https://lnkd.in/eb5u_QXc • Local Hybrid Retrieval (ONNX) – combining lexical + vector search with optimized local inference https://lnkd.in/eh4mMwSi These projects are all about understanding the building blocks: local models, embeddings, hybrid retrieval, and how they fit into modern agent architectures with Foundry Local. If you’re curious about edge AI, local-first agents, or privacy-aware RAG, feel free to explore, fork, or share feedback. #AI #RAG #FoundryLocal #AgenticAI #LocalAI #EdgeAI #Developers

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After 5 years of development at Airbnb, we’re open-sourcing Viaduct. On the surface, Viaduct is an easy-to-use, production-ready GraphQL server. Under the hood—and this is what gets me passionate—it’s a new software architecture for cloud applications, blending the best of monoliths and microservices. Whether you’re looking for a GraphQL solution or want to explore new ways of building in the cloud, we’d love for you to try Viaduct. With a new developer API under active development, now’s the perfect time to join our community and help shape its direction. 👉 Read more about Viaduct and why we’re so excited about it: http://bit.ly/4gyd0cf

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