Explores the challenges of using AI coding assistants, comparing them to the movie '50 First Dates' and emphasizing the need for persistent documentation.
December's major AI model releases focused on open licensing, long-context efficiency, and multimodal capabilities from companies like Mistral, Amazon, and OpenAI.
Author begins a blog series on learning Azure AI for certification, covering services like OpenAI, RAG, and Generative AI with practical .NET examples.
Explains how to use the KAITO RAG Engine on Azure Kubernetes Service to build a Retrieval-Augmented Generation (RAG) system for querying private documents with LLMs.
A developer shares their structured workflow for effectively using AI coding assistants like Claude Code, emphasizing planning, clear specs, and critical oversight.
A quote about Claude Code's potential impact on tech and a predicted industry split between outcome-driven and process-driven developers.
A review of key trends and developments in Large Language Models (LLMs) throughout 2025, focusing on reasoning models, agents, and industry shifts.
A developer's personal journey through a difficult year leads to insights on how AI is transforming software development and enabling the rise of the micro-entrepreneur.
A blog post quoting Armin Ronacher on how AI-assisted programming removes the frustrating labor of coding, leaving the core thinking intact.
A 2025 year-in-review analysis of large language models (LLMs), covering key developments in reasoning, architecture, costs, and predictions for 2026.
A 2025 year-in-review of Large Language Models, covering major developments in reasoning, architecture, costs, and predictions for 2026.
A curated list of notable LLM research papers from the second half of 2025, categorized by topics like reasoning, training, and multimodal models.
A curated list of notable LLM (Large Language Model) research papers published from July to December 2025, categorized by topic.
Boris Cherny shares his experience using Claude Code + Opus 4.5 to write all code for 259 PRs in a month, highlighting AI's coding progress.
A developer reflects on the anxiety and impact of using Large Language Models (LLMs) in programming, balancing skepticism with practical utility.
A software engineer shares practical strategies for effectively using AI coding agents like Claude Code, emphasizing setup and feedback loops.
An introduction to mutation testing, a technique for evaluating the quality and trustworthiness of automated test suites by deliberately injecting faults.
Testing GPU performance on a Raspberry Pi 5 versus a desktop PC for transcoding, AI, and multi-GPU tasks, showing surprising efficiency.
A visual essay explaining LLM internals like tokenization, embeddings, and transformer architecture in an accessible way.
![[notes] Some of Us Actually Like Coding](https://crawljobs-blogs-media.s3.us-east-1.amazonaws.com/alldevblogs/thumbs/article-2d50f68bf2fa-full-8b7d93d2.webp)
A software engineer's perspective on enjoying coding amidst the rise of AI coding agents, arguing for the value of hands-on programming.
