标签：#2026

Fabiane Nardon shares how TOTVS prepares enterprise data for token-hungry AI agents. She discusses balancing deterministic logic and non-deterministic LLMs across precision, security, and cost. Nardon details using data mesh, low-latency database architectures, semantic ontologies, and dynamic MCP tool selection to optimize context windows and reduce token overhead in transactional systems. By Fabiane Nardon

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

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Andrew Swerdlow shares how Roblox scales autonomous software development from prompt to production. He discusses building robust security sandboxes, extracting institutional knowledge via code review exemplars, updating engineering infrastructure, and redefining productivity metrics around feature velocity and long-running AI turns to achieve trusted, automated deployment at scale. By Andrew Swerdlow

Contributor: Nikhil Kumar Rajak ( @ryzrr ) Organization: webpack · Project: webpack-doc-kit Mentors: Aviv Keller ( @avivkeller ), Claudio Wunder ( @ovflowd ), Sebastian Beltran ( @bjohansebas ) Teammates: Mohamed Shams El-Deen ( @moshams272 ), Tushar Thakur ( @TusharThakur04 ) Period: 25 May to 17 August 2026 The problem webpack's docs lived at webpack.js.org and every API change meant somebody updating them by hand. Pages go stale and nobody notices until a reader does. webpack-doc-kit fixes that. It takes webpack's TypeScript declarations, runs them through TypeDoc, hands the output to nodejs/doc-kit for linking and UI, and produces a site that regenerates itself. We split the work three ways. Shams took AST parsing and content, Tushar took routing and navigation and UI, and I took the operational side: how docs get generated on a release, versioned & deployed. My six deliverables were PR-based doc sync, release-aware doc generation, versioned output folders, a deployment pipeline, CI validation before merge, and README fetch automation. All six shipped. Merged PRs in webpack-doc-kit 31 Lines added / removed +1,959 / −1,419 Distinct files touched 89 First / last merge 28 May ( #110 ) / 14 Aug ( #241 ) Merged PRs in other repos 2 Upstream issue filed and fixed 1 Everything below is merged into main . Nothing is open or pending. The release pipeline webpack releases happen in webpack/webpack . The docs live in webpack/webpack-doc-kit . A release in one needs to produce updated docs in the other with nobody doing anything. #110 set up versions.json as the single source of truth everything downstream reads, plus the script that maintains it and the workflow that runs it. My mentor proposed an object schema with latest , label , major , exactVersion , commit and frozen per entry. Review cut it to a flat array of tag strings, because everything else is derivable from the semver string and position [0] with unshift() already tells you which is latest. Right call, and I d

Bruna Pereira explains how DoorDash built a content-agnostic AI moderation platform. She covers replacing costly LLM-only pipelines with a hybrid pattern: using fast internal models to filter obvious cases, LLM multi-axis scoring for nuanced decisions, and no-code workflows with backtesting. Discover how this architectural pattern cut safety incidents while scaling to millions of daily messages. By Bruna Pereira

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

Sudeep Das shares how DoorDash shifts from legacy one-shot predictions to an agentic recommendation platform. He discusses leveraging language-native consumer memory, RQ-VAE semantic IDs for catalog representation, and grounded search to dramatically boost relevance and conversion metrics. By Sudeep Das

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

Next month, on September 8, MIT Technology Review will reveal its 2026 list of Innovators Under 35, recognizing 35 young people from around the world who are doing groundbreaking scientific work and building clever technical fixes for sticky problems. By finding the top young innovators globally and learning what they’re focused on in their work,…

Martin Spier explains how agentic workflows dramatically increase code change volume at OpenAI. He discusses the hidden systemic performance costs of rapid shipping beyond GPUs, and shares how deploying always-on AI agents automates profiling, regression detection, and continuous optimization to maintain product speed and scalability at massive global scale. By Martin Spier

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

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

Quotient CEO Lizzie Matusov explains why soaring AI spend often fails to improve software delivery. She presents a research-backed AI maturity framework designed to help engineering leaders move beyond vanity metrics like token usage, align organizational AI adoption, and address critical bottlenecks across the software development life cycle to deliver measurable business outcomes. By Lizzie Matusov

Want to tap into the energy of 1,100+ startup founders, investors, and tech leaders descending on Boston for the Founder Summit 2026 on June 9? Host your own Side Event during “Founder Summit Week,” happening June 4-10!

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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