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4h ago · 5 min read · If you've browsed Nepal IT job listings recently, you've probably noticed "Docker" sitting in the requirements list right next to Git and SQL — even for roles that sound junior. And if you've asked a
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4h ago · 18 min read · Node.js Is Not Failing You — You're Already Outgrowing It The uncomfortable truth about backend performance, Rust, and why the event loop will betray you exactly when it matters most. It was 3 AM. No
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6h ago · 14 min read · Agentic commerce is moving out of the concept stage and into mainstream payment infrastructure. Visa has launched its Agentic Ready programme for issuers. Stripe unveiled its Agentic Commerce Suite at
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9h ago · 15 min read · In the previous blog, we explored the fundamentals of Kubernetes Services, where we discussed how Pods communicate with each other, the role Services play, and how the communication actually works beh
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9h ago · 9 min read · This is a two-part engineering retrospective on PetPaint. Part 1 covers Phase 1 and Phase 2. Part 2 covers the Phase 3 image quality improvement. Live product: pet-paint.vercel.app Why PetPaint This
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I do fancy stuff with Oracle APEX #orclapex
12 posts this monthAI Governance Platform
3 posts this monthBuilding data layer of AGI
2 posts this monthHey everyone, I am a developer based in India
1 post this monthI do fancy stuff with Oracle APEX #orclapex
12 posts this monthAI Governance Platform
3 posts this monthBuilding data layer of AGI
2 posts this monthHey everyone, I am a developer based in India
1 post this monthIn my view, both are based on the same automation principles. The main difference is the purpose. Gaming automation is usually focused on improving or simplifying gameplay, while productivity automation is designed to solve real-world problems, save time, and increase efficiency in business or personal workflows. Technically, both rely on predefined rules, triggers, and automated actions, but their end goals are different.
This is a great breakdown of how design patterns shift the focus from 'making it work' to 'making it maintainable.' I’ve found that the real shift happens when you stop seeing patterns as just theoretical structures and start seeing them as solutions to specific 'code smell' scenarios. For anyone currently digging into these patterns, I’ve been working on a tool that summarizes technical deep-dives and video documentation into concise, readable formats. It’s been helping me get through architectural documentation much faster—you can check it out at ytskim.com. Out of curiosity
Really like how you framed the shift here — the "beyond prompts" point lands. The part I'd add from my own experience: the hardest part of context engineering in practice isn't deciding to use context, it's the unglamorous structuring decisions — chunk ordering, what to evict when the window fills, where to place the question relative to the evidence. That's where I've seen output quality actually move, often more than prompt wording. I wrote up a fuller breakdown of where prompting stops being enough and context takes over here, which complements your piece nicely: <a href="https://scienti
The missing piece for me is a repo contract, not just repo metadata. Something explicit that says: what commands are allowed what paths are off-limits which verifier actually counts as done what proof a retry needs before it can continue That turns a repo from 'maybe safe' into something an agent can operate against without folklore. That's a big part of the direction we've been taking with MartinLoop.
Every developer has an opinion on this. But most of the takes online are just hype dressed up as analysis. Here's what I've actually found after using all three seriously: ChatGPT is fast and handles
Absolutely on point. I second your finding that Claude is perfect for deep problems. Combine it with GSD (and a hefty token budget) and it w...
Interesting breakdown. From my experience running ops for small teams, the real difference shows up when you use these tools for non-coding ...