A software developer argues that formal computer science education and algorithmic problem-solving skills are essential for using AI to program, comparing unqualified AI users to untrained scalpel han…
A UK enterprise guide details the migration of COBOL systems to Python, citing readability, procedural compatibility, AI integration readiness, developer availability, and library ecosystem as key dri…
An engineer built EdgeGuard, an open-source VS Code extension that uses AI to find security vulnerabilities in code, and discovered that LLMs tend to make optimistic assumptions about unknown function…
A B.Tech Computer Science (Artificial Intelligence) student has publicly shared a personal roadmap for learning AI, emphasizing foundational programming, mathematics, data handling, and hands-on proje…
OpenDataLoader, an open-source tool from the OpenDataLoader project, converts PDF files into AI-ready formats such as Markdown, JSON, HTML, and plain text, preserving document structure and semantics.…
A developer summarized a paper by Surya Rao Rayarao and Naga Donikena on integrating AI into Java enterprise applications. The paper covers machine learning, deep learning, and NLP techniques, emphasi…
Modelio 6.2 has been ported to native Apple Silicon ARM64 by OpenAI's Codex, using GPT-5.6 Sol, in an autonomous coding task. The independent community fork, released under GPLv3, adds a visual query …
A senior software engineer at BS23 in Dhaka rebuts Google's claim that Go is the ideal language for AI-assisted coding, arguing that Java's stronger type system provides better guardrails against AI-g…
A developer explains why they target Common Lisp for AI code generation, citing its homoiconicity, macro system, and REPL introspection as advantages over mainstream languages. The developer argues th…
A senior Android developer argues that AI-generated code is degrading codebases and proposes that prompts and specification files could become a new programming language, but warns that human language…
A new analysis by Dan Luu challenges the claim that token-efficient languages like Clojure and J are better for AI coding agents. Luu found that on real-world tasks, popular languages like Python and …
A developer with 26 years of enterprise software experience has built an AI-powered integration testing flow that chains API calls, database queries, AWS services, and LLM validation into a single end…
A developer argues that using autonomous AI agents to directly rewrite large Java codebases is risky, and instead recommends using Claude Code CLI to author deterministic OpenRewrite LST recipes for l…
A study on code formatting and LLM budgets found that removing formatting elements like indentation, extra whitespace, and newlines reduced input tokens by an average of 24.5% across models and langua…
Java is a strong choice for AI development in enterprise settings, offering mature frameworks like Spring Boot and Spring AI to integrate AI capabilities into existing systems. The tutorial demonstrat…
A developer explains why they target Common Lisp for AI code generation, citing its homoiconicity, macro system, and REPL introspection as advantages over mainstream languages. The developer argues th…
LangGraph4j, a Java port of the Python LangGraph library, enables stateful multi-agent workflows in enterprise Spring Boot applications, addressing the limitations of linear execution chains in produc…
A developer at an unnamed company migrated a 10,000-line Java codebase for a competitive coding game platform to Rust using AI tools, and documented techniques for ensuring confidence in AI-generated …
American Express researchers led by distinguished engineer Andras Ferenczi built a system that migrates COBOL programs to Java while preserving bugs, achieving 96.8% branch coverage on a 430-line prog…
A team successfully migrated COBOL programs to Java using an AI LLM, preserving legacy bugs as intentional behavior because existing behavior is the specification. The team treated old COBOL as ground…