This story was originally published on HackerNoon at: https://hackernoon.com/infinite-scroll-zero-frameworks-just-generators-and-grit.
Generators are functions which can be exited and later re-entered.
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This story was written by: @ashubham3. Learn more about this writer by checking @ashubham3's about page, and for more stories, please visit hackernoon.com.

Generators are functions which can be exited and later re-entered.

This story was originally published on HackerNoon at: https://hackernoon.com/the-feynman-technique-for-algorithms-how-to-stop-memorizing-code-and-start-building-intuition.
Why volume-based study fails, and how to use LLMs to build the mental models you're missing.
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This story was written by: @huizhudev. Learn more about this writer by checking @huizhudev's about page, and for more stories, please visit hackernoon.com.

Most AI coding assistants fail the Feynman test. We can engineer a prompt that forces the AI to teach us, not just solve.

This story was originally published on HackerNoon at: https://hackernoon.com/clean-code-concurrency-patterns-context-management-and-goroutine-safety-part-5.
A practical guide to clean, safe Go concurrency—covering context, goroutines, channels, patterns, pitfalls, and lessons learned from production systems.
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This final installment in the Clean Code in Go series breaks down how to write safe, idiomatic concurrent Go code using context, goroutines, channels, and proven patterns—while avoiding leaks, race conditions, deadlocks, and the production outages they cause.

This story was originally published on HackerNoon at: https://hackernoon.com/gos-16th-anniversary-and-the-major-highlights-of-2025.
The Go team is applying its thoughtful and uncompromising mindset to the problems and opportunities of this dynamic space.
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Go 1.24 and 1.25 were released in February and August of this year, respectively. Go is the most productive language platform for building production systems. New APIs for building robust and reliable software have been added to the language and library.

This story was originally published on HackerNoon at: https://hackernoon.com/rust-1780-whats-in-it.
Rust now supports a #[diagnostic] attribute namespace to influence compiler error messages.
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Rust 1.78 has upgraded its bundled LLVM to version 18, completing the announced u128/i128 ABI change for x86-32 and x86-64 targets. Distributors that use their own LLVM older than 18 may still face the calling convention bugs mentioned in that post.

This story was originally published on HackerNoon at: https://hackernoon.com/if-your-documentation-takes-two-clicks-to-open-congrats-its-already-outdated.
An article on effective documentation practices in software development, explaining how to structure specs, READMEs, JavaDocs, and clean code.
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This story was written by: @abgarsimonean. Learn more about this writer by checking @abgarsimonean's about page, and for more stories, please visit hackernoon.com.

Documentation only survives if it lives as close to the code as possible. Good documentation isn’t a single artifact - it’s a small ecosystem of layers, each serving a different purpose.

This story was originally published on HackerNoon at: https://hackernoon.com/free-cv-domains-for-everyone-a-tiny-island-nation-is-rewriting-the-future-of-professional-profiles.
The .cv domain is shaping a new global identity layer in the AI era, as Cape Verde and Ola.cv build an open, DNS-anchored alternative to LinkedIn.
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Cape Verde wants to turn its country code, .cv, into a global identity layer for the AI era. Its partner operator Ola.cv believes profiles should live on the open internet, not inside a corporate network. They are giving away first and last name domains for free through partners like hello.cv.

This story was originally published on HackerNoon at: https://hackernoon.com/how-i-built-an-ai-powered-research-automation-system-with-n8n-groq-and-5-academic-apis.
Discover how to build a powerful AI-Powered Research Automation System using low-code tools like n8n, Groq, and integration with 5 academic APIs.
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This post guides you through architecting an AI-powered research automation system using a low-code approach. It shows you how to integrate n8n for workflow orchestration, Groq for high-speed LLM inference, and five different academic APIs to automatically query, analyze, and process research data, accelerating the entire R&D-to-publication cycle.