InfoQ Homepage Programming Content on InfoQ
-
/articles/AI-legacy-modernization/en/smallimage/AI-legacy-modernization-thumbnail-1746528855677.jpg)
AI Interventions to Reduce Cycle Time in Legacy Modernization
In this article, we share our experiences and insights on how large language models (LLMs) helped us uncover and enhance the conceptual constructs behind software. We discuss how these approaches address the inherent complexity of software engineering and improve the likelihood of success in large, complex software modernization projects.
-
/articles/rxjs-angular16-best-practices/en/smallimage/rxjs-angular16-best-practices-thumbnail-1747139973479.jpg)
RxJS Best Practices in Angular 16: Avoiding Subscription Pitfalls and Optimizing Streams
This article delves into modern Angular (16+) RxJS best practices. It emphasizes using AsyncPipe for templates, flattening streams with operators, ensuring proper cleanup with takeUntil and DestroyRef, implementing error handling, and combining RxJS with Angular signals for efficient state management, ultimately leading to future-proof and maintainable code in Angular 17/18.
-
/articles/complex-applications-storage-constraints/en/smallimage/compex-applications-storage-constraints-thumbnail-1747126977374.jpg)
Binary Size Matters: the Challenges of Fitting Complex Applications in Storage-Constrained Devices
This article explores developing software for microcontrollers in C or C++, where constraints are the limited amount of volatile memory and the embedded hardware platform on which the software runs. It shows how to adopt languages like C++ while optimizing for binary size due to stringent hardware constraints, and trade off between runtime efficiency and binary size in architecture decisions.
-
/articles/practical-design-patterns-modern-ai-systems/en/smallimage/practical-design-patterns-modern-ai-systems-thumbnail-1747122253617.jpg)
Beyond the Gang of Four: Practical Design Patterns for Modern AI Systems
In this article, author Rahul Suresh discusses emerging AI patterns in the areas of prompting, responsible AI, user experience, AI-Ops, and optimization, with code examples for each design pattern.
-
/articles/lcm-paradigm-shift-ai-reasoning/en/smallimage/lcm-paradigm-shift-ai-reasoning-thumbanil-1747043782723.jpg)
Large Concept Models: a Paradigm Shift in AI Reasoning
Differently from LLMs, Large Concept Models (LCMs) use structured knowledge to grasp relationships between concepts, enhancing the decision-making process and providing a transparent reasoning audit trail. Using LCMs with LLMs can facilitate building AI systems that can analyze complex scenarios and effectively communicate insights, driving towards developing more reliable and explainable AI.
-
/articles/best-practices-energy-efficient-ai-ml-systems/en/smallimage/best-practices-energy-efficient-ai-ml-systems-thumbnail-1746711047911.jpg)
Best Practices to Build Energy-Efficient AI/ML Systems
In this article, author Lakshmithejaswi Narasannagari discusses the sustainable innovations in AI/ML technologies, how to track carbon footprint in all stages of ML systems lifecycle and best practices for model development and deployment.
-
/articles/culture-trends-2025/en/smallimage/infoq-trends-report-small-logo-1746021971556.jpeg)
InfoQ Culture and Methods Trends Report - 2025
This report summarizes how the InfoQ Culture and Methods editorial team sees the ongoing and emergent trends in the culture and methods space.
-
/articles/domain-driven-rag/en/smallimage/domain-driven-rag-thumbnail-1746086725084.jpg)
Domain-Driven RAG: Building Accurate Enterprise Knowledge Systems through Distributed Ownership
Retrieval augmented generation (RAG) can help reduce LLM hallucination. Learn how applying high-quality metadata and distributing ownership of documents and prompts to domain experts can further increase accuracy in RAG applications. An additional layer of intelligence can use metadata to focus RAG searches on a specific domain for even better results.
-
/articles/shared-libraries-dotnet-enterprise/en/smallimage/shared-libraries-dotnet-enterprise-thumbnail-1745919135446.jpg)
Best Practices for Managing Shared Libraries in .NET Applications at Scale
This article discusses real-world cases of using shared libraries, their consequences, and possible solutions to blockers caused by using them in many dependent projects.
-
/articles/ocr-ai-document-processing/en/smallimage/ocr-ai-document-processing-thumbnail-1745914250509.jpg)
Beyond OCR: How AI is Transforming Document Processing for Enterprise Applications
In this article, author Jitender Jain discusses AI driven document processing techniques for an intelligent, adaptive approach to document processing, to interpret documents in context and not just by visual structure.
-
/articles/architecting-real-time-systems-around-mainframe/en/smallimage/thumbnail-1745312950914.jpg)
Legacy Modernization: Architecting Real-Time Systems around a Mainframe
At its heart, our transformation journey is about breaking dependencies at multiple levels. Many enterprises face similar challenges with legacy systems: tightly coupled architectures that are difficult to scale, change, or maintain. For us at National Grid, the solution came through four complementary paradigms that worked together to enable different forms of decoupling.
-
/articles/architecture-trends-2025/en/smallimage/the-infoq-trends-report-small-logo-1744808318307.jpeg)
InfoQ Software Architecture and Design Trends Report - 2025
The InfoQ Trends Reports offer InfoQ readers a comprehensive overview of key topics worthy of attention. The reports also guide the InfoQ editorial team towards cutting-edge technologies in our reporting. In conjunction with the report and trends graph, our accompanying podcast features insightful discussions among the editors digging deeper into some of the trends.