InfoQ Homepage Software Engineering Content on InfoQ
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Optimizing Software Workflow: Exploring Fundamental Impacts in Technology
Software only has value when shipped; faster release cadence matters. Development, deployment, and operations require different thinking, metrics, and investments. There are four impacts in tech: product success, compute capacity, engineering capacity, and strategic innovation. The biggest expense is people. AI shifts engineers toward deeper problem understanding, not fewer engineers.
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QCon London 2027 Announces 15 Tracks on Production AI, Architecture, and Engineering at Scale
A preview of the 15-track QCon London 2027 program, covering agent evaluation and guardrails, AI-era architecture, distributed-system debugging, modern data platforms, high-performance engineering, and Staff+ leadership.
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How to Develop Software Engineering Skills in the Age of AI
Software engineering skill development requires slowing down. Generative AI has changed the landscape of skill development for software engineering. Tools and AI can accelerate outcomes, but they may not support skill development. Engineers must understand how systems work to learn things. Senior developers can coach juniors by using learning techniques.
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Agents Refactor 300K Lines in Three Weeks, and Practitioners Ask What it Proves
CodeScene has published a case study in which coding agents refactored 300,000 lines of C over three weeks for roughly $4,000 in tokens, verified by a frame-by-frame replay harness. The agents built a playbook of codebase-specific recipes along the way. Practitioners have questioned the scope, the metric, and how much of the result depends on the harness.
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Swiggy Uses 350+ Features and Multi-Task MLP to Predict Customer Lifetime Value
Swiggy developed an in-house predicted lifetime value model using more than 350 pre order features and a multi task MLP for Food and Instamart. Adding order count as an auxiliary task reduced model parameters by 63% while improving predictive performance. The pLTV signal is used with Google Target ROAS bidding to optimize customer acquisition.
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AWS Introduces Specification-Driven Composition for Flexible Data Workflows
AWS describes a specification-driven approach for composing flexible data workflows by separating intent from processing logic. Architecture uses declarative specifications, reusable processing capabilities, and validation before execution. AWS reports that the approach can reduce dataset onboarding from weeks to days while supporting traceability, versioning, data classification, and governance.
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Cloudflare Turns Engineering Standards into an AI-Enforced Control System
Cloudflare has recently detailed how it is using AI to transform internal engineering standards from passive documentation into an actively enforced control system across the software development lifecycle.
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How Artificial Intelligence Disrupts Engineering Progression
AI is disrupting career progression by eliminating the learning opportunities at each rung while simultaneously enabling people to perform above their experience level, Alasdair Allan explained in his talk Engineering Progression When AI Ate the Middle at QCon London. Fewer junior developers join the industry, and AI slows hiring at the entry level.
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Three InfoQ Certification Cohorts Start This August: Meet the Facilitators
InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants' own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul.
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Stripe Benchmark Shows AI Agents Build Integrations but Struggle with Validation
Stripe introduces a benchmark suite to evaluate whether AI agents can build real-world Stripe integrations across backend, frontend, and browser-based checkout workflows. The study examines end-to-end software engineering capability, focusing on execution, testing, and validation gaps in agentic systems under production-like constraints.
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Slack Introduces Agent Driven End-to-End Testing to Improve Resilience in UI Test Automation
Agentic testing is an AI-driven approach to end-to-end test automation introduced by Slack engineering. It uses AI agents that execute workflows based on intent rather than fixed scripts, adapting to UI and system changes at runtime. The approach aims to reduce brittle tests in distributed systems while complementing deterministic unit, integration, and E2E testing strategies.
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GitHub Copilot CLI Gets Tabs and No-Config-File Tool Setup in Redesigned Terminal UI
GitHub has made the redesigned GitHub Copilot CLI terminal interface generally available. It adds a tabbed layout for sessions, gists, issues, and pull requests; an in-session, form-driven setup for MCP servers, skills, and plugins that avoids hand-editing config files; and a cleaner, theme-aware, more accessible UI with screen reader support.
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AI Is Moving up the Software Lifecycle: from Code Review to PRD Governance
Technology companies are extending AI beyond code generation into earlier stages of the software lifecycle, including PRD validation, design inputs, and code review. Initiatives from Uber, DoorDash, and Cloudflare highlight a shift toward AI-driven governance layers that evaluate engineering artifacts before implementation while preserving human oversight across the development pipeline.
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GitHub Slashes Agent Workflow Token Spend up to 62% with Daily Audits and MCP Pruning
GitHub reports cutting token costs in agentic CI workflows by up to 62% by pruning unused MCP tools, swapping some MCP calls for gh CLI, and running daily “auditor” and “optimizer” agents. A token-usage.jsonl artefact and an Effective Tokens metric help track spend across models and spot regressions.
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InfoQ Online Certification Program: New AI Engineering and Organizational Architecture Cohorts
InfoQ expands its online certification portfolio with new AI Engineering and Organizational Architecture cohorts, giving senior practitioners a confidential peer group to pressure-test production AI, platform, team design, and architecture decisions.