# QCon Software Development Conference Published articles for QCon Software Development Conference. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How Marathon Incidents Expose Organizational Fragility and Require Structured Incident Response DevFeed: [How Marathon Incidents Expose Organizational Fragility and Require Structured Incident Response]() Original publisher: [Read original article]() Author: Vanessa Huerta Granda Published: 2026-09-17T09:30:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [incident](), [Incident response]() Tags: [devops](), [incident](), [incident-response](), [infoq](), [limits](), [organizational](), [outages](), [presentation](), [qcon-san-francisco-2026](), [qcon-software-development-conference](), [real-world](), [stream-incidents](), [structured](), [system](), [transcripts]() ### AI overview Vanessa Huerta Granda discusses how prolonged incidents reveal gaps between planned work and work as performed. Drawing on real-world scenarios, the presentation examines organizational fragility, human limits, system interdependencies, and the need for structured, humane, cross-functional incident response. ### Source excerpt Vanessa Huerta Granda explains how marathon incidents expose the gap between work as imagined and work as done. Drawing from real-world scenarios, she shares how complex outages reveal organizational fragility, human limits, and system interdependencies--and why incident response requires structured endurance, humane rotations, and holistic cross-functional coordination. By Vanessa Huerta Granda ## Presentation: Teaching Engineers, Trusting AI: How Education Enabled Autonomous Code Review DevFeed: [Presentation: Teaching Engineers, Trusting AI: How Education Enabled Autonomous Code Review]() Original publisher: [Read original article]() Author: Sarah Deitke Published: 2026-09-16T11:00:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [Artificial Intelligence](), [Code review](), [Pull Request](), [Tooling](), [engineering-culture](), [observability]() Tags: [adoption](), [agile](), [ai](), [ai-ml-data-engineering](), [architecture-design](), [artificial-intelligence](), [automated](), [automation](), [autonomous](), [case-study](), [code-review](), [code-reviews](), [culture](), [culture-methods](), [developer](), [developer-experience](), [development](), [duolingo-ai-literacy-code-review](), [infoq](), [metrics](), [ml-data-engineering](), [observability](), [pairing](), [presentation](), [qcon-london-2026](), [qcon-software-development-conference](), [transcripts]() ### AI overview Sarah Deitke presents Duolingo's approach to cultural AI adoption through internal AI literacy workshops, observability dashboards, and safe AI guardrails. The presentation includes a case study on redesigning code review with an automated PR risk-assessment bot and reports faster delivery without increased defect rates. ### Source excerpt Sarah Deitke discusses how Duolingo drives cultural AI adoption beyond tooling access. She explains their internal AI literacy workshops and observability dashboards, then shares a case study on redesigning code review using an automated PR risk-assessment bot. Deitke demonstrates how pairing targeted developer education with safe AI guardrails speeds up delivery without increasing defect rates. By Sarah Deitke ## Presentation: Lead Without a Ladder: How I Climbed Into Engineering Leadership DevFeed: [Presentation: Lead Without a Ladder: How I Climbed Into Engineering Leadership]() Original publisher: [Read original article]() Author: Pauline Jepp Published: 2026-09-15T09:10:00Z Content type: opinion Language: en Sources: [InfoQ]() Topics: [engineering-leadership](), [systems]() Tags: [alignment](), [careers](), [chief-engineer](), [culture-methods](), [engineering](), [engineering-leadership](), [infoq](), [leadership](), [mentorship](), [presentation](), [qcon-san-francisco-2025](), [qcon-software-development-conference](), [safety](), [team](), [transcripts](), [trust]() ### AI overview Pauline Jepp discusses how systems thinking, rock climbing, and flocking behaviors inform engineering leadership. She covers balancing team autonomy with alignment, supporting mentorship and other invisible work, and transitioning from hands-on engineering to leadership while maintaining organizational trust and psychological safety. ### Source excerpt Pauline Jepp explains how systems thinking, rock climbing, and flocking behaviors apply to engineering leadership. She shares strategies for balancing team autonomy with alignment, supporting invisible work like mentorship, and navigating transitions from hands-on engineer to engineering leader while maintaining organizational trust and psychological safety. By Pauline Jepp ## Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills DevFeed: [Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills]() Original publisher: [Read original article]() Author: Alex Porcelli Published: 2026-09-14T11:00:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [Agent Skills](), [Artificial Intelligence](), [Large Language Model](), [NeMo]() Tags: [agent](), [agent-skills](), [agentic](), [agentic-ai-architecture](), [agents](), [ai](), [ai-architecture](), [ai-ml-data-engineering](), [architecture](), [architecture-design](), [architectures](), [artificial-intelligence](), [business](), [decision-models-agentic-ai](), [development](), [enterprise](), [enterprise-architecture](), [governance](), [infoq](), [large-language-models](), [llms](), [ml-data-engineering](), [models](), [nemo](), [presentation](), [production](), [qcon-ai-boston-2026](), [qcon-software-development-conference](), [skills](), [transcripts]() ### AI overview Alex Porcelli explains how DMN decision models can be integrated with LLMs, agent skills, and NeMo guardrails to create auditable and deterministic agentic architectures for high-stakes enterprise decisions. ### Source excerpt Alex Porcelli discusses the critical gap in enterprise AI: non-deterministic output and lack of accountability in high-stakes decisions. He shares how integrating DMN decision models with LLMs, agent skills, and NeMo guardrails creates auditable, deterministic agentic architectures - allowing business leaders to own decision logic while engineers maintain robust architectural governance. By Alex Porcelli ## Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs DevFeed: [Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs]() Original publisher: [Read original article]() Author: Cassie Shum Published: 2026-09-12T11:00:00Z Content type: tutorial Language: en Sources: [InfoQ]() Topics: [Graphs](), [Architecture & Design](), [Retrieval Augmented Generation (RAG)](), [Code]() Tags: [agentic-ai](), [agentic-ai-architecture](), [agents](), [ai](), [ai-architecture](), [ai-ml-data-engineering](), [architecture](), [architecture-design](), [artificial-intelligence](), [code](), [development](), [engineering](), [infoq](), [knowledge-graph](), [knowledge-graphs-agentic-systems-patterns](), [large-language-models](), [ml-data-engineering](), [presentation](), [production](), [qcon-ai-boston-2026](), [qcon-software-development-conference](), [rag](), [reasoning](), [retrieval-augmented-generation](), [transcripts]() ### AI overview A presentation on using knowledge graphs as a foundation for production-ready agentic AI systems. It covers architectural patterns for context bundling, decision provenance, code as truth, and agent visibility, along with a graph-based engineering harness for feedback loops, token optimization, and reliability. ### Source excerpt Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability. By Cassie Shum ## Presentation: How To Run on Three Clouds at Once, and When Not To DevFeed: [Presentation: How To Run on Three Clouds at Once, and When Not To]() Original publisher: [Read original article]() Author: Ross McFarlane, Kevin Holditch Published: 2026-09-11T11:00:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [networking](), [Databases](), [Kubernetes]() Tags: [amazon](), [architecture](), [architecture-design](), [availability](), [aws](), [cloud](), [cloud-architecture](), [cloud-computing](), [cloud-networking](), [cockroach-labs](), [cockroachdb](), [containers](), [databases](), [devops](), [disaster-recovery](), [engineering](), [europe](), [financial-applications](), [fintech](), [form3-multicloud-architecture](), [infoq](), [kubernetes](), [microservices](), [networking](), [presentation](), [qcon-london-2026](), [qcon-software-development-conference](), [resilience](), [transcripts](), [us]() ### AI overview A presentation on Form3's move from one cloud to a triple-active multi-cloud architecture, covering cross-cloud networking, distributed databases, Kubernetes operators, and regional disaster-recovery expectations. ### Source excerpt Ross McFarlane and Kevin Holditch discuss Form3's evolution from a single-cloud setup to a triple active multi-cloud architecture. They share key engineering strategies for cross-cloud networking, distributed databases with CockroachDB and NATS, custom Kubernetes operators, and navigating distinct regional disaster recovery expectations across the UK, Europe, and US financial markets. By Ross McFarlane, Kevin Holditch ## Presentation: Accelerating Performance by Incrementally Integrating Rust Into Existing Codebase DevFeed: [Presentation: Accelerating Performance by Incrementally Integrating Rust Into Existing Codebase]() Original publisher: [Read original article]() Author: Lily Mara Published: 2026-09-10T09:34:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [rust refactoring](), [Refactoring](), [Integration testing]() Tags: [architecture](), [cost](), [culture-methods](), [design](), [development](), [engineering](), [infoq](), [infrastructure](), [performance](), [presentation](), [python](), [qcon-san-francisco-2025](), [qcon-software-development-conference](), [refactoring](), [rust](), [rust-refactoring](), [system-programming](), [testing](), [transcripts]() ### AI overview A presentation on incrementally refactoring Python bottlenecks into Rust with PyO3 to improve function-level performance, retain integration testing, and reduce infrastructure costs. ### Source excerpt Lily Mara explains how to avoid high-risk software rewrites through incremental FFI refactoring. She shares how engineering teams can replace Python bottlenecks with Rust via PyO3, demonstrating how to achieve dramatic function-level speedups, seamless integration testing, and meaningful infrastructure cost savings without microservice overhead. By Lily Mara