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Anthropic reliability engineer Alex Palcuie shares practical lessons on using LLMs for real-world incident response. He explains where AI acts as a superhuman for observing logs and traces, why it still struggles with causation versus correlation during root-cause analysis, and how engineering leaders can integrate AI into on-call workflows without eroding human expertise. By Alex Palcuie
Artificial intelligence (AI) makes all code write-only,. It’s too dense to read, and tests define the behaviour and become the documentation. Code is also disposable; it becomes easier to rewrite than to debug. Humans can't review AI-generated code at scale. Intent decouples from implementation; developers should focus on creativity. By Ben Linders
Sam Newman discusses the concept of progressive collapse in civil engineering and how it applies to distributed systems. Using real-world examples - from the 1968 Ronan Point tower failure to AWS outages - he shares crucial resilience engineering strategies for software leaders. Learn how to strengthen components, isolate failures, and reduce interconnections to prevent catastrophic cascades. By Sam Newman
Baruch Sadogursky and Patrick Debois discuss why coding agents fail due to bloated context windows and stuffed prompts. They explain practical context engineering fixes, including lazy-loaded skills, versioned context artifacts, externalized memory banks, and LLM-as-a-judge evals. Software architects & engineering leaders will learn how to turn raw markdown files into reliable agentic workflows. By Patrick Debois, Baruch Sadogursky
David Chisnall discusses how the CHERI hardware architecture redefines pointer safety to solve isolation and sharing challenges. He explains how CHERI enables spatial and temporal memory safety for C/C++, scales down to microcontrollers with CHERIoT, and replaces costly OS-level RPC mechanisms with lightweight, auditable compartmentalization - all without requiring massive codebase rewrites. By David Chisnall
Laurence Tratt discusses yk, an open-source meta-tracing JIT compiler framework. He shares how to automatically speed up C-based language interpreters like Lua and MicroPython with minimal, non-invasive code changes. He explains the inner workings of tracing loops, optimizing compiled traces using developer hints, and managing complex deoptimization back to the interpreter. By Laurence Tratt
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 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
Martin Kleppmann discusses the urgent need for technological sovereignty in modern infrastructure. Exploring the shifting landscape of global tech dependencies, he shares how engineering leaders can leverage multi-cloud architecture, de facto API standardization, the AT Protocol, and local-first development paradigms to reclaim user agency and build highly resilient systems. By Martin Kleppmann