InfoQ Homepage Culture & Methods Content on InfoQ
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Agentic AI Patterns Reinforce Engineering Discipline
Paul Duvall recently discussed his library of engineering patterns for AI assisted development and practices that ground high quality delivery. Related discussions from Paul Stack and Gergely Orosz highlight a shift toward remixing and specification driven development.
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QCon London 2026: Team Topologies as the ‘Infrastructure for Agency’ with AI
At QCon London 2026, Matthew Skelton argued that AI success depends on organisational maturity. He highlighted bounded agency, security, and stewardship as key to managing AI agents. By using Innovation and Practices Enabling Teams, companies can drive knowledge diffusion and optimise internal processes to see real-world returns on their AI investments.
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Teleport Report Finds Over-Privileged AI Systems Linked to Fourfold Rise in Security Incidents
Enterprises that grant excessive access permissions to AI systems experience 4.5 times as many security incidents as those that do not, according to The 2026 State of AI in Enterprise Infrastructure Security, a report published by infrastructure identity company Teleport. The study found that identity management hasn't kept up with AI adoption in production systems.
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QCon London 2026: AI Agents Write Your Code. What’s Left for Humans?
Hannah Foxwell began her QCon London 2026 talk by noting that the long-sought velocity in development has arrived, but the industry is unsure how to use it. She set aside the technical details of agentic coding, focusing instead on its implications for the people working with these systems.
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Green IT: How to Reduce the Impact of AI on the Environment
AI poses major challenges for green IT: each query consumes vast energy, GPU chips last only 2-3 years, and costs stay hidden from users. Regulatory frameworks like the EU AI Act fall short on enforcement, Ludi Akue said. In her talk What I Wish I Knew When I Started with Green IT she presented model compression, quantization, and novel architectures, using sustainability as a design constraint.
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Stripe Engineers Deploy Minions, Autonomous Agents Producing Thousands of Pull Requests Weekly
Stripe engineers describe Minions, autonomous coding agents generating over 1,300 pull requests per week. Tasks can originate from Slack, bug reports, or feature requests. Using LLMs, blueprints, and CI/CD pipelines, Minions produce production-ready changes while maintaining reliability and human review.
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How to Shape the Engineering Culture in Software Companies
You can find your way through an organization by figuring out what artifacts people leave behind, David Grizzanti mentioned at InfoQ Dev Summit Boston. He compared culture to anthropology, suggested studying behaviors, power dynamics, and decisions first, and then patiently model and reward new norms, build allies, and use influence and leading by example, to shift engineering culture over time.
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HubSpot’s Sidekick: Multi-Model AI Code Review with 90% Faster Feedback and 80% Engineer Approval
HubSpot engineers introduced Sidekick, an internal AI powered code review system that analyzes pull requests using large language models and filters feedback through a secondary “judge agent.” The system reduced time to first feedback on pull requests by about 90 percent and is now used across tens of thousands of internal pull requests.
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QCon London 2026: SBOMs Move from Best Practice to Legal Obligation as CRA Enforcement Looms
In a talk at QCon London 2026, Viktor Petersson argued that software teams are running out of time to adopt SBOMs (Software Bills of Materials) due to pending legislative changes in both the US and Europe. He walked through the current regulatory landscape, spoke on the practical mechanics of generating high-quality SBOMs and on the emerging standards for distributing the resulting artefacts.
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QCon London 2026: Blurring the Lines: Engineering & Data Teams in the Age of AI
At QCon London 2026, Lada Indra, head of data platform at Pleo, shared insights from his experience across high-scale data systems. He illustrated both the risks of poorly aligned teams and the practical strategies that organizations can adopt to bridge the gap.
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QCon London 2026: Shipping Constantly with Humans and beyond at Monzo
At QCon London 2026, Suhail Patel, a principal engineer at Monzo who leads the bank’s platform group, described how the bank has built a developer platform capable of shipping hundreds of changes to production every day.
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Making Retrospectives Effective with Small Concrete Actions and Rotating Facilitators
Teams can run regular retrospectives that focus on 1–2 concrete weekly actions to avoid complaint circles, Natan Žabkar Nordberg mentioned at QCon London. You can rotate facilitators to build ownership, with each one bringing their own unique perspective. He suggested framing bigger changes as 4–6 week experiments, then vote to keep, tweak, or revert, ensuring learning and continuous improvement.
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Decentralizing Architectural Decisions with the Architecture Advice Process
Our system architectures have changed as technology and development practices have evolved, but the way we practice architecture hasn’t kept up. According to Andrew Harmel-Law, architecture needs to be decentralized, similar to how we have decentralized our systems. The alternative to having an architect take and communicate decisions is to “let anyone make the decisions” using the advice process.
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From Central Control to Team Autonomy: Rethinking Infrastructure Delivery
Adidas engineers describe shifting from a centralized Infrastructure-as-Code model to a decentralized one. Five teams autonomously deployed over 81 new infrastructure stacks in two months, using layered IaC modules, automated pipelines, and shared frameworks. The redesign illustrates how to scale infrastructure delivery while maintaining governance at scale.
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Lessons from Growing a Software Leadership Team
Thiago Ghisi explained how he guided managers and senior ICs to build a resilient leadership group beneath him in his talk Lessons from Growing Engineering Organizations at QCon London. Regular syncs, expectation calibration, and alignment on broader goals made leaders multipliers of culture and performance. Culture is what you do, not what you say.