I saw it again yesterday. A senior Java developer — 15 years of experience, architect-level skills, built systems serving millions of users — asking in a Slack channel: “Should I learn Python to stay relevant?” The responses? A mix of well-meaning advice and subtle condescension. “Yes, Python is essential for AI.” “Java’s not really used for ML.” “Maybe it’s time to adapt.” I wanted to say so
So I've been using swaggo for documenting Go APIs and honestly it works great, but... // @Param id query string true "User ID" Every single time I write this I have to stop and think "wait which one comes first again?" And I know I'm not the only one because our team slack has like 10 messages asking "what's the order for @param again?"
When is a side project worth committing to? Ben Halpern ・ Jan 8 #ai #gemini #sideprojects #showdev
Somtochi Onyekwere explains the architecture of Corrosion, a distributed system designed for low-latency state replication. She shares how Fly.io transitioned from Consul to a gossip-based SQLite solution to handle global machine data. By discussing CRDTs, the SWIM protocol, and QUIC, she shares how to build resilient systems that prioritize speed while managing the complexities of CAP theorem. By
This special edition of The InfoQ eMag, contains a comprehensive collection of our popular InfoQ Trends Reports from 2025, a year with both evolution and revolution within the landscapes of technology, software development trends. This collection does not just reflect the past year's technological trends. We aspire to use it as a guide for future exploration and innovation. By InfoQ
If you’ve ever worked with a Data Scientist, you’ve likely experienced "The Handoff." They hand you a Jupyter Notebook named final_model_v3_really_final.ipynb. It’s 500 lines of unorganized Python, it requires a GPU to run, and it has a dependency list that just says pip install tensorflow. And now, it’s your job to put it into production. At Besttech, we see this friction constantly.
The importance of Side Projects When I was doing my Masters degree I used to come back from my part time job at 7pm and start working on side projects until 11pm. I didn't even have time for cooking so I used to get a chinese takeaway and start playing with whatever new technology I was interested in. Proof of how many fortune cookies I collected in those days in a single week 😅
Introducing TanStack AI: a revolutionary, framework-agnostic toolkit empowering developers with unparalleled control over their AI stack. This open-source release features a unified interface across multiple providers and ensures type safety with innovative isomorphic tools. Say goodbye to vendor lock-in and hello to freedom in AI development! By Daniel Curtis
My favorite albums from last year. Balkan brass, an acoustic favorite of 80s returns, Ethio-jazz, Guatemalan singer-guitarist, jazz-rock/Indian classical fusion, and a unique male vocalist. more…
Anthropic report on how their AI is changing their own software development practice. Most usage is for debugging and helping understand existing code Notable increase in using it for implementing new features Developers using it for 59% of their work and getting 50% productivity increase 14% of developers are “power users” reporting much greater gains Claude helps developers to work o
A secure software development life cycle means baking security into plan, design, build, test, and maintenance, rather than sprinkling it on at the end, Sara Martinez said in her talk Ensuring Software Security. Testers aren’t bug finders but early defenders, building security and quality in from the first sprint. Culture first, automation second, continuous testing and monitoring all the way. By
AWS previews Route 53 Global Resolver, using Anycast to decouple DNS from regional failures. It simplifies hybrid setups with unified public/private resolution, DoH/DoT, and Zero-Trust security. By Steef-Jan Wiggers
In this article author Sachin Joglekar discusses the transformation of CLI terminals becoming agentic where developers can state goals while the AI agents plan, call tools, iterate, ask for approval where needed, and execute the requests. He also explains the planning styles for three different CLI tools: Gemini, Claude, and Auto-GPT. By Sachin Joglekar
Conducted among over 1,200 respondents, Facebook's 2025 Typed Python Survey highlights how and why Python developers have increasingly adopted the language's type hinting system. The survey also sheds light on what developers value most, as well as their biggest frustrations and wishes. By Sergio De Simone
Alex Seaton discusses the architecture of ArcticDB, a high-performance Python/C++ library that replaces traditional database servers with a thick-client model. He explains how to achieve atomicity on object storage through bottom-up writes and shares deep insights into conflict-free replicated data types (CRDTs). He also explores the pitfalls of clock drift and distributed locking. By Alex Seaton
Meta applies large language models to mutation testing through its Automated Compliance Hardening system, generating targeted mutants and tests to improve compliance coverage, reduce overhead, and detect privacy and safety risks. The approach supports scalable, LLM-driven test generation and continuous compliance across Meta’s platforms. By Leela Kumili
DeepSeek released DeepSeek-V3.2, a family of open-source reasoning and agentic AI models. The high compute version, DeepSeek-V3.2-Speciale, performs better than GPT-5 and comparably to Gemini-3.0-Pro on several reasoning benchmarks. By Anthony Alford
Docker has launched Kanvas, a new platform designed to bridge the gap between local development and cloud production. By automating the conversion of Docker Compose files into Kubernetes artefacts, the tool challenges established solutions like Helm and Kustomize. Developed with Layer5, it marks a shift toward Infrastructure as Code, offering visualisations to simplify cloud-native deployments. By
Intel has announced DeepMath, a lightweight agent built on Qwen3-Thinking that specializes in solving mathematical problems. To address common limitations of LLMs in math reasoning, DeepMath generates small Python scripts that support and enhance its problem-solving process. By Sergio De Simone
JEP 525, a highlight in the upcoming JDK 26, refines structured concurrency for clearer, safer task management. This iteration introduces a timeout callback for custom joiners, enhancing flexibility and error handling. With streamlined APIs and focus on practical usage, it empowers developers to efficiently manage concurrent tasks, paving the way for advanced Project Loom features. By A N M Bazlur