coding

How I Would Learn To Code (If I Could Start Over)

Egor Howell shares his coding journey and offers advice for learning programming. He emphasizes the value of coding, starting with a single language relevant to one's career goals, and warns against “tutorial hell.” Encouraging practical projects right after basic courses, he stresses the importance of mastering fundamentals without chasing trends. Documentation and sharing learning experiences online can enhance visibility to potential employers. Despite fears over AI impacting programming jobs, Howell reassures that coding skills remain essential and unlikely to be replaced by AI.

https://towardsdatascience.com/how-i-would-learn-to-code-if-i-could-start-over/

Augment Code

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Augment Code is a top verified open-source AI agent for software engineers, featuring advanced integration with codebases, memory enhancements, and collaboration tools. It excels in code quality, outperforming competitors on the SWE-Bench leaderboard at 65.4%, and offers features like real-time context analysis, debugging tools, and seamless integration with various development environments. The platform includes efficient workflows for issue tracking, pull requests, and coding, emphasizing reliability and developer efficiency.

https://www.augmentcode.com/

Why I Stopped Using AI Code Editors

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Stop using AI code editors due to loss of competence and over-reliance; manual engagement recommended. Started using AI in 2022, felt fast but grew dependent. Dropped AI in late 2024 to regain skills. Maintaining in-depth knowledge is crucial, as AI fails in complex contexts. Use AI wisely, but don't rely fully on it—stay engaged and curious to avoid becoming obsolete in programming. Enjoy coding for its own sake and keep practicing basics to remain capable.

https://lucianonooijen.com/blog/why-i-stopped-using-ai-code-editors/

E.W.Dijkstra Archive: On the Foolishness of “natural Language Programming”. (EWD 667)

Dijkstra criticizes “natural language programming,” asserting it complicates the man-machine interface rather than simplifying it. He highlights that formal programming languages, despite being perceived as burdensome, help eliminate nonsensical errors that natural language cannot. Historical examples show that reliance on verbal communication has hindered mathematical advancement. He suggests that formal symbols facilitate learning and precision. Dijkstra warns that the decline in language mastery (“The New Illiteracy”) undermines the feasibility of programming in natural languages. Ultimately, he believes creating and using such languages would be incredibly challenging.

https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667.html

Devin, the Viral Coding AI Agent, Gets a New Pay-as-you-go Plan

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Cognition has launched a low-cost pay-as-you-go plan for its viral AI coding tool, Devin, previously priced at $500/month. The new plan starts at $20 for about 9 computing credits, with usage potentially increasing costs. Although Devin 2.0 claims improved functionality, its effectiveness in complex coding remains questionable, with earlier evaluations showing it completed only 3 of 20 tasks successfully.

https://techcrunch.com/2025/04/03/devin-the-viral-coding-ai-agent-gets-a-new-pay-as-you-go-plan/

Zencoder’s ‘Coffee Mode’ Is the Future of Coding: Hit a Button and Let AI Write Your Unit Tests

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Zencoder introduces ‘Coffee Mode,' allowing developers to use AI for unit tests and coding tasks while taking breaks. The AI, integrated into popular IDEs like Visual Studio Code and JetBrains, claims superior performance on industry benchmarks by analyzing entire codebases. Its unique “Repo Grokking” technology offers contextual insights, mitigating common AI coding tool issues. Zencoder positions itself against competitors like GitHub Copilot while enabling developers to maintain familiar workflows. The company aims for production-ready AI code with security checks, projecting transformative changes in software development by 2025.

https://venturebeat.com/ai/zencoders-coffee-mode-is-the-future-of-coding-hit-a-button-and-let-ai-write-your-unit-tests/

There Is No Vibe Engineering

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Vibe Coding, coined by Andrej Karpathy, emphasizes coding without direct code interaction, relying on AI outputs. While AI changes coding, it doesn't replace the essential role of software engineering, which involves system design over time. Vibe coding focuses only on immediate coding tasks, neglecting vital long-term considerations. Thus, there's no unique “Vibe Engineering”; it's still traditional engineering, albeit with less coding. The future may integrate AI-generated components, but the need for careful system design remains unchanged. Vibe Coding is effective for prototypes but not suitable for robust production software.

https://serce.me/posts/2025-31-03-there-is-no-vibe-engineering

What Is Vibe Coding? And Why Should You Care?

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Vibe Coding Overview:
Vibe Coding emphasizes the “vibe” or essence of software rather than focusing solely on the code itself. It leverages AI to create software by using natural language inputs to guide the development process, allowing AI to iteratively refine and enhance code behavior based on human conceptual directions. This shift raises new challenges for businesses, such as reliance on code that may not be fully understood by humans, the acceleration of prototype development, and implications for software testing, security, and team structure. As AI-generated code becomes more prevalent, it's vital for businesses to adapt and stay competitive in this evolving landscape.

https://www.forbes.com/sites/nishatalagala/2025/03/30/what-is-vibe-coding-and-why-should-you-care/

Why I’m Breaking Up With Vibe Coding

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Breaking up with vibe coding: once enjoyable, now inefficient. Over-reliance on AI leads to time sink, high costs, lack of understanding. AI aids mockups, but structured planning needed for complex tasks. Exploring balanced alternatives like Gemini Code Assist and Open WebUI for better control and reduced expenses. Creativity valuable, but unsustainable without structure, especially under deadlines.

https://www.lucasaguiar.xyz/posts/vibe-coding-pitfalls/

What Is Vibe Coding, Should You Be Using AI to Do It, and Does It Matter?

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Vibe coding uses AI (like ChatGPT) to generate complete software code for non-programmers. Coined by Andrej Karpathy, it enables users to create apps without programming knowledge, but results can be buggy and unreliable. While some claim it may replace developers, experts assert it won't, as software engineering involves more than just writing code.

https://www.newscientist.com/article/2473993-what-is-vibe-coding-should-you-be-doing-it-and-does-it-matter/

10 Professional Developers on Vibe Coding’s True Promise and Peril

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Vibe Coding Insights: Developers debate “vibe coding,” blending AI and software development. While AI speeds up coding, concerns rise over security risks and potential pitfalls for inexperienced users. Experts warn that without solid programming knowledge, users might create flawed or insecure software. Effective use requires understanding user needs and proper oversight, ensuring AI doesn't compromise software quality. Balancing creativity with caution is vital in this evolving landscape.

https://www.zdnet.com/article/10-professional-developers-on-vibe-codings-true-promise-and-peril/

Does Vibe Coding Really Work? We Built a Game With Claude—Here’s How It Turned Out

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Vibe coding, a method of building software by conversing with AI, was tested by creating a simple typing game using Claude AI. The process involved iterating and refining the game's code through natural language communication, resulting in a playable game that demonstrated rapid prototyping capabilities. Key lessons learned include the importance of iteration, not rushing the development process, and recognizing that while vibe coding can yield functional software, it may lack professional polish. Overall, vibe coding shows promise for both novices and experienced developers as a creative coding tool.

https://decrypt.co/311183/we-built-game-vibe-coding-ai-claude

Tools

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CodeWithLLM Tools Overview

  • IDEs: Diverse integrated development environments provide AI-powered coding, debugging, and collaboration (e.g., Cursor, GitHub Copilot, and Trae).
  • Extensions: AI coding extensions for IDEs enhance code generation, debugging, and quality (e.g., Cline, Zencoder, and Tabnine).
  • CLI Tools: Tools for coding assistance through command-line interfaces (e.g., Aider Chat, MyCoder.ai).
  • Web Generators: Platforms facilitate software development with minimal coding (e.g., Base44, Pythagora).
  • Development Tools: AI-enhanced tools support collaborative coding, testing, and deployment (e.g., Devin, Databutton).
  • Cost-Effective APIs: OpenRouter unifies various APIs, and local LLM deployments offer privacy and control options.

https://aicode.danvoronov.com/tools/

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