InfoQ Homepage Software Development Content on InfoQ
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From Prompts to Production: A Playbook for Agentic Development
In this article, author Abhishek Goswami shares a practitioner's playbook with development practices, that describes building agentic AI applications and scaling them in production. He also presents core architecture patterns for agentic application development.
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Building LLMs in Resource-Constrained Environments: A Hands-On Perspective
In this article, the author argues that infrastructure and compute limitations can drive innovation. It demonstrates how smaller, efficient models, synthetic data generation, and disciplined engineering enable the creation of impactful LLM-based AI systems despite severe resource constraints.
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Virtual Panel - AI in the Trenches: How Developers Are Rewriting the Software Process
This virtual panel brings together engineers, architects, and technical leaders to explore how AI is changing the landscape of software development. Practitioners share their insights on successes and failures when AI is incorporated into daily workflows, emphasizing the significance of context, validation, and cultural adaptation in making AI a sustainable element of modern engineering practices.
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Article Series: AI-Assisted Development: Real World Patterns, Pitfalls, and Production Readiness
In this series, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline. As AI transitions from proof of concept to production, teams are discovering that the challenge extends beyond model performance to include architecture, process, and accountability. This transition is redefining what constitutes good software engineering.
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InfoQ Cloud and DevOps Trends Report - 2025
This InfoQ Trends Report offers readers a comprehensive overview of emerging trends and technologies in the areas of Cloud and DevOps. This report summarizes the InfoQ editorial team’s and external guests' view on the current trends in Cloud and DevOps technologies and what to look out for in the next 12 months.
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A Plan-Do-Check-Act Framework for AI Code Generation
AI code generation tools promise faster development but often create quality issues, integration problems, and delivery delays. A structured Plan-Do-Check-Act cycle can maintain code quality while leveraging AI capabilities. Through working agreements, structured prompts, and continuous retrospection, it asserts accountability over code while guiding AI to produce tested, maintainable software.
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Sandbox as a Service: Building an Automated AWS Sandbox Framework
This article outlines an automated AWS Sandbox Framework to provide secure, cost-controlled environments for innovation. It leverages AWS services like Control Tower and open-source tools to automate provisioning, enforce security policies, manage resource lifecycles, and optimize costs through automated cleanup and governance.
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A First-Timer’s Guide to Curating a Technical Conference Track
One first-time track host shares the process, constraints, and takeaways from building a track from scratch at QCon London 2025.
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Engineering Principles for Building a Successful Cloud-Prem Solution
Discover how Cloud-Prem solutions combine cloud efficiency with on-premise control, meeting data sovereignty and compliance demands while optimizing operational costs and enhancing customer security.
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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.
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Virtual Panel: Increasing Engineering Productivity, Develop Software Fast and in a Sustainable Way
Companies need to balance between rapid feature development and long-term product sustainability. Engineers are taking on more left-shifted, cognitive load as their features intersect with user privacy, security, accessibility, and regulations. We'll discuss approaches, philosophies, and techniques that companies and products applied to improve the effectiveness and efficiency of development.
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Prompt Engineering: Challenges, Strengths, and Its Place in Software Development's Future
Prompt engineering is evolving as a crucial skill that bridges AI communication and programming, blending creativity and precision to shape the future of software development. The future of software development might involve a synergistic blend of both approaches. Prompt engineering can accelerate prototyping and enhance interactivity, while traditional programming ensures robustness.