It is currently in its early development phase. However, the core implementations are ready for testing and ready for feedback but it's not yet feature complete yet.<p>If this fits your workflow, feel free to use it and stress-test it. Questions, suggestions, and contributions are welcome to help make LockFS better.
Many posts claim that "development is becoming obsolete" but they rarely discuss what software evolution actually looks like.Yes, a growing portion of development, especially frontend boilerplate, is becoming automated. But automation doesn’t eliminate development; It changes its shape. The real question isn’t whether coding disappears. It’s: What does development become when repetitive UI work is largely automated?Here’s one direction I see emerging: the rise of variable frontends.Tod
Anders Ericsson argued that high-touch mastery - elite human capabilities - takes on the order of 10k hours of focused development.I personally started adopting LLMs into my workflow with Sonnet 3.5, which was released June of 2024. Sonnet 3.6 was released in October of the same yearTry as I might, I couldn't plug 625 hours per week of deliberate practice in that window. I never achieved Sonnet 3.5 mastery.---There has a steady stream of blog content on the "How I program with LLMs (in
I've been using Claude Code ever since it came out, and I've seen good success with it. However, Matt Shumer's recent article [1] included a piece I'm curious about:When describing his workflow now, he says "Then, and this is the part that would have been unthinkable a year ago, it opens the app itself. It clicks through the buttons. It tests the features. It uses the app the way a person would."Unless I missed a major development, do these coding agents have the ab
We had a call with a large accountancy firm and they gave us some really good feedback. However, we couldn’t convert them into a development partner because of IT security and compliance constraints. Right now, we are testing and getting traction with mid-sized and smaller accountancy firms, but their processes are not as complex, so automation does not feel like a major value add for them. Bigger firms are where the real complexity and value are, but they are much harder to work with early on.
My wife and I built and shipped a simple iOS app without writing a single line of code in the traditional sense.She hates when I bring my laptop on trips. I love building things. This was our compromise.I had been wanting to experiment with building an iOS app using Claude Code. I had never built for iOS before, and the idea of exploring it through AI-assisted development felt like a new frontier for me. But bringing a laptop to Japan again would not go unnoticed, and not in a good way.So I made
I realized something uncomfortable while running agents in production:APIs authenticate the process making a request.But with LLM agents, the process no longer decides the request — the model does.So when an agent is prompt-injected or misaligned, authentication still succeeds. The system verifies who executed the call, not who chose it.Rotating keys or adding revocation checks doesn’t fix this. You’re still trusting the wrapper while the decision lives inside the model.The missing primitive isn
It's political satire about American gun culture, toxic masculinity, and radicalisation pipelines, built by a distributed async dev team across multiple continents. The project started as a 7-day game jam entry and spiralled into 14 months of development. Whoops.It hit #2 on Steam's Upcoming Releases page before launch with 6,400+ wishlists.Some things that might interest this community:The scope creep from 7 days to 14 months is a case study in how small projects grow Unity, yarn We l
Most AI tools generate text. Very few generate finished artifacts you can ship.I expected the hard part to be prompt engineering. It wasn't. The hard part is what happens after generation: enforcing structural invariants so the output is actually usable -- every section present, no "coming soon" placeholders, no layout that falls apart at export time.I ended up treating LLM output the way a compiler treats source code: intent goes in, validated artifacts come out, deterministic ru
When building AI experiences, choosing between WebSockets and HTTP isn't always straightforward. Which protocol is better for streaming LLM responses? How do you maintain continuity when users switch devices mid-conversation? Should you use both?The answer depends on the type of AI experience you're building. Modern AI applications often require both protocols, each serving different purposes. The key question is: how do you decide which communication pattern fits each scenario in your AI stack?
After spending weeks analyzing the Moltbook leaks and the systemic failures of unaccountable AI agents (as warned in I Am Your AIB), I thought we were headed straight for a black-box catastrophe.I was wrong. I just stumbled upon something that changes everything.There is an open initiative that isn't just talking about "AI safety" in abstract terms. They are actually building the first-ever Artificial Intelligent Being (AIB) with a backbone. This is the "Genesis Moment"
I’ve spent the last couple of years deploying LLM agents in production environments, and I’ve consistently hit the same wall: the 'Cognitive Monolith' (or what I call the Big Ball of Mud AI).We are currently seeing a lot of hype around 'autonomous agents' that are essentially 3,000-word prompts with access to 20 tools. In my experience, this doesn't scale. It’s impossible to unit test, observability is a nightmare, and the 'vibe-based' engineering makes it a li
tl;dr looking for any links, resources or tips around best practices for data security, privacy, and agent guardrails when using Claude (or others).My journey over the past few years has been one of borderline AI skeptic for its use in coding to having tried Claude Code a month ago and being unlikely to ever go back to coding big changes without it. Most queries I would have used search for in the past are now done in AI models as a first step.However, one thing that concerns me is whether I am
I’m an electromechanical engineer who usually tinkers with RPis and Arduinos more than software, but a few weeks ago I went down the rabbit hole of randomness. I read about Cloudflare’s lava lamp wall and thought: if they’re ultimately using cameras, why not use the image sensor noise directly?Modern CMOS sensors produce a lot of grainy, unstable pixels—even when pointed at a static scene. You can film the same white wall at 30 fps and never get an identical frame. That felt like a decent physic
I've been steadfastly trying my best to incorporate the latest-and-greatest models into my workflow. I've been primarily using Codex recently. But I'm still having difficulties.For example: no matter what I do, I can't prevent Codex from introducing linter errors.I use tabs instead of spaces for indentation. It seems like the model is massively weighted on code written using spaces (duh). Despite having a very well articulated styleguide (that Codex helped me write after exam
I kept collecting software design bookmarks for years — repos, articles, books — but never organized them. Most "awesome" lists for architecture cover the "monolith vs microservices" debate. I wanted something focused on the code-level side: how to actually structure modules, enforce design rules in CI, and document decisions. I went through ~300 resources and kept 106 across 9 categories. A few sections I haven't seen elsewhere:Architecture Decision Records — 14 real-wo
Editing or removing a message after it’s been published sounds simple. In realtime systems, it usually isn’t.Once a message has been delivered to multiple clients, cached locally, and written into history, changing it safely becomes a coordination problem. Clients need to agree on what’s current. History needs to stay consistent. Reconnects and refreshes can’t bring back stale content.That’s why many systems treat messages as immutable by default.Today, Ably Pub/Sub adds support for editing and
This article is the sixth in a series of articles about authentication and authorization in a microservice architecture.The complete series is: Overview of authentication and authorization in a microservice architecture Implementing authentication Implementing JWT-based authorization Implementing authorization using fetch and replicate Implementing complex authorization using Oso Cloud Implementing complex authorization using Oso Cloud local authorization
Hi HN,I’m Vincent from Aden. We spent 4 years building ERP automation for construction (PO/invoice reconciliation). We had real enterprise customers but hit a technical wall: Chatbots aren't for real work. Accountants don't want to chat; they want the ledger reconciled while they sleep. They want services, not tools.Existing agent frameworks (LangChain, AutoGPT) failed in production - brittle, looping, and unable to handle messy data. General Computer Use (GCU) frameworks were eve
I was sick of recreating the wheel every time I wanted to built some distributed application, so I built this<p>https://github.com/octopii-rs/octopii