coding

Vibe Coding: How AI Is Changing Software Development Forever

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Vibe coding revolutionizes software development by using AI to generate code from natural language prompts, allowing both experienced developers and beginners to describe desired functionalities instead of writing syntax. OpenAI's Andrej Karpathy coined the term, highlighting how AI alleviates coding burdens and enhances creativity. Popular tools include Replit, Cursor, Lovable, and Windsurf, which streamline development, improve productivity, and democratize coding for non-developers. However, challenges include concerns about code quality, ethical implications, reliance on AI, and potential erosion of programming expertise. Despite these issues, vibe coding is ushering in a new era of software creation, emphasizing oversight and collaboration rather than traditional coding.

https://www.unite.ai/vibe-coding-how-ai-is-changing-software-development-forever/

Should Managers Still Code?

Managers should be “in the code” but not necessarily writing it. They need to understand the codebase, review it, and engage with the technical aspects of their team while focusing on strategic, leadership, and mentorship roles. Their coding involvement can vary based on individual roles and organizational needs, emphasizing the importance of being technically aware without being the primary coder.

https://theengineeringmanager.substack.com/p/should-managers-still-code

Hallucinations in Code Are the Least Dangerous Form of LLM Mistakes

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LLM hallucinations in code, like inventing methods, are less harmful than errors not caught by compilers. Running code reveals issues immediately, allowing for quick fixes. Unlike prose, where critical review is needed to avoid sharing false information, code provides built-in fact-checking. Manual testing is key; never trust code without seeing it work. Users should improve skills in reviewing LLM-generated code. To reduce hallucinations, experiment with different models, use context effectively, and pick well-known libraries. Relying solely on LLMs without running the code indicates a lack of experience.

https://simonwillison.net/2025/Mar/2/hallucinations-in-code/

Functional Options Pattern

Functional Options Pattern: A strategy for cleanly passing configuration options in functions, enhancing flexibility and usability. Popular in Go, it mitigates issues like parameter bloat and mandatory options. Instead of cumbersome parameters, it uses a struct for options, allowing default values and encapsulation. Implementing via variadic parameters and functions as options enhances customization without breaking changes. Applicable in various languages, it’s particularly suited for Go's constraints. Examples include Docker and Uber’s Zap logging. Overall, it's a valuable tool for developers for managing function configurations.

https://andrerfcsantos.dev/posts/functional-options-pattern/

Leaderboard

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WebDev Arena Leaderboard Summary: Real-time AI coding competition by LMArena. Top models at the moment:

  1. Claude 3.7 Sonnet (Anthropic)
  2. Claude 3.5 Sonnet (Anthropic)
  3. DeepSeek-R1 (DeepSeek)
  4. early-grok-3 (xAI)
  5. mini-high (OpenAI)
  6. Claude 3.5 Haiku (Anthropic)

Various models from Google, OpenAI, and others ranked below.

https://web.lmarena.ai/leaderboard

Cline

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Cline is an autonomous coding agent for VSCode designed to enhance developer productivity through collaboration and versatility. With 842.8k installations and 32.5k stars, it streamlines workflows, automates coding tasks, and integrates seamlessly with various AI models and external databases. Cline is open-source, secure, and offers features such as error monitoring, customizable checkpoints, and a supportive community, allowing developers to work more efficiently and innovatively.

https://cline.bot/

How to Turn ChatGPT Into Your AI Coding Power Tool

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Extreme TLDR: Utilize ChatGPT as a coding tool to enhance programming output by: giving small tasks, using iterative prompts, testing code, and rewording prompts if needed. Avoid proprietary coding requests, and leverage AI for general coding knowledge, patterns, CSS selectors, and regular expressions. Check legal issues and generate useful variable names for better code clarity.

https://www.zdnet.com/article/how-to-turn-chatgpt-into-your-ai-coding-power-tool-and-double-your-output/

Home

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Aider is an AI pair programming tool for terminal, supporting code editing in local git repositories, compatible with various LLMs. It simplifies project setup, allows requests for code changes, automatically commits edits, and integrates with popular IDEs, enhancing productivity across multiple programming languages.

https://aider.chat/

Claude 3.7 Sonnet and Claude Code Anthropic

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Claude 3.7 Sonnet, Anthropic's latest AI model, introduces integrated reasoning capabilities for improved coding and web development. It features instant or extended thinking modes, allowing user control over response time. Claude Code, a new tool for coding tasks, enhances collaboration and efficiency. Available across all pricing tiers, it retains previous models' pricing structure. Testing shows it excels in real-world coding tasks and reduces development time. The model prioritizes responsible use, with improved safety measures and user feedback integration to refine capabilities.

https://www.anthropic.com/news/claude-3-7-sonnet

AI Coding: New Research Shows Even the Best Models Struggle With Real-World Software Engineering

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AI coding research reveals top models struggle with real-world software tasks, as highlighted by OpenAI’s SWE-Lancer benchmark. The study shows even leading AI, Claude 3.5 Sonnet, only solves 26.2% of coding tasks and 44.9% of management tasks, translating to about $400,000 in potential earnings from $1 million, indicating they lag behind human capabilities in practical scenarios.

https://devops.com/ai-coding-new-research-shows-even-the-best-models-struggle-with-real-world-software-engineering/

XOR

XOR (Exclusive OR) is a boolean logic operator defined by its truth table. It outputs 1 when inputs differ and 0 when they are the same. XOR has several interpretations: it can mean “exclusive or,” “not equals,” or can be seen as conditional inversion or parity operations. It possesses properties like commutativity, associativity, and identity with 0. Bitwise XOR extends these properties to integers, offering applications in cryptography, graphics, and error-correcting codes. In cryptography, XOR combines plaintext with a keystream for encryption. In pixel graphics, it allows for reversible drawing operations that are efficient in memory use. Overall, XOR is crucial to computer science for its simplicity and utility in various operations.

https://www.chiark.greenend.org.uk/~sgtatham/quasiblog/xor/

My LLM Codegen Workflow Atm

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TL;DR: Harper Reed shares a code generation workflow using LLMs, focusing on brainstorming, planning, and execution. He details two approaches: greenfield (new projects) and incremental (existing codebases). His steps involve honing ideas with a conversational LLM, creating detailed specs, and employing tools like Claude and Aider for execution. Despite the efficiency, he highlights limitations, such as solo work and potential environmental impacts of AI. He encourages skeptics to explore AI's benefits through resources like Ethan Mollick's book, aiming for a collaborative coding experience.

https://harper.blog/2025/02/16/my-llm-codegen-workflow-atm/

A Catalog of Ways to Generate SSA

Catalog of Static Single Assignment (SSA) generation methods, detailing historical papers and approaches. SSA assigns variables once, improving compiler efficiency. Important papers cover various methods from 1980s to 2023, addressing phi functions, dominance frontiers, single-pass generation, and incremental SSA. Highlights include Cytron's minimal phi instructions, Brandis & Mössenböck's parsing approach, and recent works using reaching definitions. The author plans to add more resources and encourage contributions on SSA-related topics.

https://bernsteinbear.com/blog/ssa/

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