InfoQ - Artificial Intelligence

Instacart Builds Blueberry, an AI-Powered Assistant to Help On-Call Engineers Investigate Incidents

Leela Kumili — Fri, 07 Aug 2026 14:34:00 GMT

Instacart introduced Blueberry, an AI-assisted incident response system that helps on-call engineers investigate production issues faster. It combines AI agents, operational data, and historical incident knowledge to generate grounded root cause hypotheses in Slack. It uses parallel subagents, MCP integrations, and incident history to reduce investigation time while keeping engineers in control.

By Leela Kumili

AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans

Craig Risi — Fri, 07 Aug 2026 12:00:00 GMT

Artificial intelligence is rapidly changing how engineering teams respond to production incidents, offering the ability to summarize incident channels, analyze unfamiliar code, suggest remediation steps, generate pull requests, and increasingly assist with diagnosis.

By Craig Risi

Presentation: Rewriting All of Spotify's Code Base, All the Time

Jo Kelly-Fenton, Aleksandar Mitic — Fri, 07 Aug 2026 11:00:00 GMT

Jo Kelly-Fenton and Aleksandar Mitic explain how Spotify created "Honk," an AI coding agent, to handle complex fleet-wide codebase migrations. They share key architectural insights on decoupling CI verification runtimes from AI agents, dealing with automated pull request bottlenecks, and driving aggressive standardization across thousands of engineering repositories.

By Jo Kelly-Fenton, Aleksandar Mitic

Article: InfoQ Culture and Methods Trends Report - 2026

Fri, 07 Aug 2026 09:00:00 GMT

This report summarizes how the InfoQ Culture and Methods editorial team sees the ongoing and emergent trends in the culture and methods space in 2026.

By Shane Hastie, Ben Linders, Vanessa Formicola, Shawna Martell, Rafiq Gemmail, Craig Smith, Phillip Mortimer, Yinka Omole

Article: Runtime-Agnostic AI Workflows: A Pattern for Production Durability and Fast Eval Iteration

Mateus Moury — Thu, 06 Aug 2026 09:00:00 GMT

AI workflows have two needs that trade off directly. Running reliably in production requires persisting and distributing every step so it survives crashes, deploys, and restarts. But that same machinery is what makes runs too heavy for the fast, throwaway loop you need to check an LLM's output quality. The properties that buy durability are the ones that kill iteration speed.

By Mateus Moury

Platform Engineering Maturity Emerges as a Key Differentiator for Enterprise AI Success

Craig Risi — Tue, 04 Aug 2026 12:00:00 GMT

Platform engineering maturity is emerging as an important factor in determining whether organizations can turn AI adoption into sustainable operational value, according to Perforce Software's 2026 Platform Engineering Report.

By Craig Risi

Dropbox Integrates MCP and Dash to Close the Gap between Security Design and Code Review

Leela Kumili — Fri, 31 Jul 2026 14:36:00 GMT

Dropbox has integrated Model Context Protocol (MCP) with its internal knowledge platform, Dash, to surface security design context during AI assisted code reviews. The system retrieves threat models and security requirements for pull requests, helping reviewers validate implementation against design intent. An InfoQ Q&A explores the architecture and key lessons learned.

By Leela Kumili

Presentation: The Free-Lunch Guide to Idea Circularity

Holly Cummins — Fri, 31 Jul 2026 11:00:00 GMT

Holly Cummins discusses why "nothing is new under the sun" in tech. She maps historical architectural tradeoffs to modern cloud, microservices, and AI hype cycles. She connects financial debt (post-ZIRP) and technical debt to epistemic and sleep debt, showing engineering leaders how to navigate shifts in assumptions, embrace sustainability, and revive proven engineering disciplines.

By Holly Cummins

AI-Assisted Software Development: Team Profiles and Capabilities for Putting Research into Action

Ben Linders — Thu, 30 Jul 2026 11:30:00 GMT

AI is an amplifier; strategic focus on the organizational system brings the greatest returns. DORA's 2025 research on AI in software development provides team profiles and success capabilities that can be used to put the research into practice.

By Ben Linders

Presentation: Getting Rid of LeetCode Interviews in the World of AI

Daniel Doubrovkine — Wed, 29 Jul 2026 10:25:00 GMT

Daniel Doubrovkine explains why traditional LeetCode whiteboard interviews fail to evaluate senior engineering talent. He discusses his own experience bombing basic algorithm tests despite decades of leadership, and shares actionable frameworks for redefining the interview loop. Discover how evaluating human judgment, system design, and hands-on AI collaboration yields far better hiring signals.

By Daniel Doubrovkine

Article: Securing MCP in Production: Defense-in-Depth beyond the Gateway

Nik Kale — Wed, 29 Jul 2026 09:00:00 GMT

This article presents a defense-in-depth approach for securing Model Context Protocol (MCP) deployments in production. It outlines four architectural control layers: safe execution, management infrastructure, outbound trust, and semantic integrity, arguing that production security requires enforcement beyond the gateway at the earliest trustworthy control points.

By Nik Kale

Grafana Assistant Expands to More Than 30 Data Sources

Craig Risi — Tue, 28 Jul 2026 12:00:00 GMT

Grafana Labs has expanded the capabilities of Grafana Assistant, enabling its AI-powered observability assistant to query and correlate data across more than 30 different data sources through natural language.

By Craig Risi

Presentation: The Future of Engineering: Mindsets That Matter When Code Isn’t Enough

Ben Greene — Tue, 28 Jul 2026 11:10:00 GMT

Ben Greene discusses how software engineers can adapt and thrive in an era of rapid AI code automation. Drawing on his startup experience, he explains key mindsets like starting simple, maintaining code comprehension, attacking hard problems first, and focusing on customer impact. He shares why human empathy, agency, and practical problem-solving remain irreplaceable when code is automated.

By Ben Greene