/ THE FEED /

Read what ships.

Deep, recent reads ranked by depth and freshness.

  1. Behind the build: Generative plugins and shaders at Figma

    Figma developed generative plugins and shaders by replacing a prototype WebGL system with an enterprise-scale WebGPU pipeline, sandbox isolation, and custom UI kits. Through rapid prototyping and cross-functional collaboration, the team shipped the feature suite in two months for Config.

    DEPTH ■■■■■8 min read7 weeks ago

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  2. Running multi-day AZ evacuation drills with ARC Zonal Shift

    This post explains how to run multi-day Availability Zone evacuation drills using ARC Zonal Shift to prove application resilience under sustained stress. The team details step-by-step procedures across ECS, EKS, and PostgreSQL databases to uncover hidden failure modes like unoptimized scaling and stale connections. The result is a practical framework for moving from theoretical multi-AZ architectures to proven operational resilience.

    DEPTH ■■■■■19 min read3 weeks ago

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  3. “Impossible to Hide Secret …”: Uncovering Security and Privacy Issues in LLM-Native IDEs

    Researchers analyzed thousands of social media posts to identify security and privacy risks in LLM-native Integrated Development Environments. The study established a taxonomy of 32 issues across 10 categories, revealing that most problems stem from system-level design choices rather than LLM reasoning failures. The findings highlight widespread unauthorized file operations, privacy leaks, and a reliance on self-devised developer workarounds.

    DEPTH ■■■■■3 min read2 weeks ago

    Machine LearningSecurity

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  4. Seer, the Sentry MCP and CLI, or your own coding agent: where each one fits

    Engineers often struggle to choose between native debugging agents, Model Context Protocols, and command-line tools when integrating error tracking into their workflows. Sentry demonstrates how its debugging assistant Seer, the Sentry MCP, the Sentry CLI, and various coding agent integrations complement each other rather than compete. The resulting setup allows teams to diagnose complex application errors and automatically generate pull requests through whichever surface they prefer.

    DEPTH ■■■■■11 min read3 weeks ago

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  5. How the Math Used in 19th-Century Heat Physics Helps LLMs Understand Sentences

    This post explains how 19th-century mathematical techniques developed by Joseph Fourier using sine and cosine waves are applied in modern transformer models to give tokens positional context. The author demonstrates how word order dictates semantic meaning and how multi-speed rotational patterns provide bounded, scalable positional encodings. Ultimately, this mathematical structure helps attention mechanisms account for relative token distances during training.

    DEPTH ■■■■■13 min read13 days ago

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  6. Handling hot shards

    Growing applications often encounter hot shards when certain tenants or data subsets outgrow initial sharding strategies based on workspace IDs. To mitigate this, teams can scale up resources, isolate large tenants into specific key ranges, or fundamentally change the shard key for problematic tables based on access patterns. Neki facilitates these adjustments by allowing declarative data topologies and online resharding without downtime.

    DEPTH ■■■■■7 min read4 weeks ago

    MySQLPostgreSQL

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  7. How MHK built a HIPAA-eligible agentic AI solution on Amazon Bedrock

    Healthcare technology company MHK faced fragmented AI infrastructure and lengthy development cycles while trying to process unstructured medical documents under strict HIPAA standards. To solve this, they built a multi-tenant, event-driven agentic workflow framework called the SmartProminence AI Orchestrator on AWS using Amazon Bedrock, ECS, and SQS. The new system reduced manual review effort by 90% and shortened AI feature deployment times from months to weeks.

    DEPTH ■■■■■12 min read3 weeks ago

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  8. How River takes security work from a fix to merge

    Shopify developed an AI agent named River to automate security vulnerability remediation from dependency upgrades to pull request merges. The agent validates live states, replays and repairs fixes on current repository heads, and escalates context-dependent decisions to human engineers. This workflow reduced the open issue backlog by about 70 percent and increased freshness-gated security merges significantly.

    DEPTH ■■■■■9 min read7 weeks ago

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  9. The Regression Tests Nobody Writes: Capturing How Software Actually Behaves

    Standard regression tests usually only verify developer intent rather than the actual, unwritten behaviors that systems accumulate in production over time. By capturing real production traffic and network-level interactions, teams can build characterization test suites to automatically detect unintended behavioral shifts. This approach prevents accidental regressions during legacy refactoring, rewrites, and major framework upgrades.

    DEPTH ■■■■■6 min read3 days ago

    Testing

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  10. How do you actually measure the impact of AI on design?

    Figma conducted a multi-year research project to track the impact of AI on product design by building an AI sentiment index and running hundreds of AI-moderated interviews. To process the massive volume of qualitative data, the team engineered a custom thematic analysis tool and an internal dashboard to serve as a cross-functional source of truth. The results showed that AI's impact on workflows and collaboration nearly doubled over three years.

    DEPTH ■■■■■6 min read8 weeks ago

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  11. Build adaptive AI interfaces with the AG-UI protocol, agent swarms, and Nova Act on AWS

    AI applications produce variable outputs that cannot be effectively handled by static user interfaces, leading to development friction and poor user experiences. The team implemented an adaptive interface pattern using the AG-UI protocol, the Strands Agents SDK Swarm pattern, and Amazon Nova Act on AWS to dynamically render components and automate legacy integrations. This architecture streams agent findings over Server-Sent Events, enabling real-time multi-agent consensus and reducing interface development overhead.

    DEPTH ■■■■■22 min read3 weeks ago

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  12. Localizing compliance at scale: achieving South Korea’s ISMS certification

    To achieve South Korea's ISMS certification, Cloudflare had to modify its account sign-up flow to itemize required consents and disable third-party social logins that bypassed the form. By combining IP geolocation with user country selection, the team ensured localized compliance without breaking global functionality. The resulting certification provides a localized assurance benchmark for Korean users.

    DEPTH ■■■■■8 min read4 days ago

    Security

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  13. Survey Says: You'll swap the model, but everything you build around it is staying put

    Stacklok surveyed technical leaders to understand enterprise AI adoption and vendor lock-in concerns. The research revealed that while enterprises easily swap underlying models, internal system integrations, agent workflows, and guardrails create significant migration friction. Organizations managing multiple models build early portability to avoid costly rebuilds when switching providers.

    DEPTH ■■■■■4 min read5 days ago

    Machine Learning

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  14. Measuring the back/forward cache with Application Metrics

    Engineering teams often lack visibility into back/forward cache performance because successful cache hits leave no telemetry traces and browser heuristics frequently change. To solve this blind spot, the team introduced an opt-in application metrics integration in their JavaScript SDK that models browser bfcache signals into hits, specific miss reasons, and reload durations. As a result, developers can track, query, and fix silent navigation regressions using customizable dashboards.

    DEPTH ■■■■■6 min read4 weeks ago

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  15. Don't forget about the UI for AI

    OpenAI developed ChatGPT Space, a real-time collaborative workspace designed to allow software engineering teams and individual AI agents to work together on shared artifacts. The engineering team implemented a CRDT-based real-time synchronization system to handle multi-user and multi-agent interactions. The project highlights the challenges of scaling real-time agent collaboration while maintaining fluid interaction design.

    DEPTH ■■■■■26 min read6 days ago

    Machine Learning

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  16. Beyond the patch: Protecting your NetScaler gateway against future vulnerabilities

    Recent major vulnerabilities in Citrix NetScaler exposed public-facing authentication gateways to unauthenticated remote code execution. To prevent similar emergency patches, the team recommends placing an independent Zero Trust access layer, web application firewall, and strict origin connection controls in front of the application server. Implementing these defense-in-depth measures reduces exposure and ensures a single software flaw does not result in total system compromise.

    DEPTH ■■■■■9 min read7 days ago

    Security

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  17. Building Sentry's Laravel AI Integration

    The Sentry team built a Laravel AI integration to support Agent Tracing during an internal hackweek. Because Laravel AI lacked events for individual LLM invocations, the integration correlates outgoing HTTP requests with active invocations using provider URL prefixes. The resulting zero-config feature is available in sentry-laravel 4.27 and automatically traces agents, LLM requests, and tool calls.

    DEPTH ■■■■■4 min read5 weeks ago

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  18. Production-grade LLMs and agents: a field guide

    Deploying LLMs and agents to production requires surrounding probabilistic models with deterministic machinery like evaluations, guardrails, and audit trails rather than relying on the model alone. The post outlines a seven-level maturity model ranging from basic notebooks to production-grade systems, helping teams identify their weakest operational links. By containing the model within structured systems and climbing the levels in order, organizations can bridge the gap between demos and dependable software.

    DEPTH ■■■■■4 min read7 days ago

    Machine Learning

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  19. How Dynata scaled AI across the development lifecycle with AI-DLC and Kiro IDE

    Dynata adopted the AI-Driven Development Lifecycle methodology using Kiro IDE and Amazon Q Developer to compress multi-sprint feature delivery into a single sprint. The team progressed from code generation to integrating knowledge ecosystems and conducting structured three-day feature workshops. As a result, requirements ambiguities surfaced early during planning and the team achieved faster, more aligned feature delivery.

    DEPTH ■■■■■15 min read11 days ago

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  20. AI says you’re right, formal methods say you’re wrong

    Engineers often struggle with the intimidating reputation and adoption of formal verification tools like TLA+ and its derivatives, despite their value in catching elusive edge cases and race conditions. Using specification languages to model systems allows teams to test fixes and optimizations mathematically before deploying them to production. This approach helps prevent complex bugs that take weeks to manifest in real-world traffic.

    DEPTH ■■■■■28 min read10 days ago

    Machine Learning

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