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Deep, recent reads ranked by depth and freshness.

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  1. 01Shopify · architecture

    We gave AI agents a mobile dev environment

    Engineering teams outgrew their local machines while running parallel AI mobile development agents, constrained by heavy builds and lack of iOS tools on Linux. To solve this, they built Remote Dev using warm pools of remote Macs connected via SSH alongside separate Linux VMs for Android virtualization, paired with agent skills and live browser streaming. This setup shifted workflow bottlenecks, increasing AI-merged pull requests from 6 percent to 61 percent.

    DEPTH ■■■■■9 min read3 days ago

    ArchitectureMobile

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  2. 02GitLab · tutorial

    PHP2Shell: GitLab helps find and remediate critical PHP flaws

    Critical remote code execution vulnerabilities known as PHP2Shell affect the PHP engine across multiple versions, requiring immediate runtime updates to fixed versions or patched distribution packages. The team utilized platform features like container scanning, code search, and automated agent workflows to locate PHP projects and remediate vulnerabilities. Operators must also check logs and environments for signs of compromise as framework updates and input validations cannot prevent these engine-level flaws.

    DEPTH ■■■■■10 min read3 days ago

    ArchitectureSecurity

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  3. 03Amazon Web Services · architecture

    Automate medical coding with Step Functions and Amazon Bedrock AgentCore

    Automating medical coding requires a hybrid approach that combines deterministic orchestration with bounded agentic reasoning to ensure safety, auditability, and human oversight. The team built a workflow using AWS Step Functions, AWS Lambda, and Amazon Bedrock AgentCore that evaluates terms cheapest-first via block-lists, exact matching, and finally an LLM agent for ambiguous cases. This design successfully autocodes confident cases while routing ambiguous ones to human reviewers with full audit trails and decision explanations.

    DEPTH ■■■■■15 min read3 days ago

    AWS

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  4. 04Grab · architecture

    App stability at scale with a layered defense

    To maintain app stability amidst rapid weekly releases and AI-generated code, Grab uses a layered defense strategy covering prevention, release gates, and incident response. This pipeline includes static analysis via custom lint rules, multiple tiers of automated and manual testing, a pre-production early access build, staged rollouts, and feature flags with instant kill switches. As a result, critical defects are caught early in the development lifecycle before reaching the wider production user base.

    DEPTH ■■■■■16 min read4 days ago

    MobileReliability

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  5. 05Shopify · architecture

    How Shopify turns open models into task experts

    Shopify uses a continual learning flywheel to post-train open models, such as NVIDIA Nemotron, to serve as dedicated subagents for specific tasks like GraphQL generation. By optimizing inference and utilizing automated self-healing to generate training data from production failures, the team successfully created task experts that outperform frontier models while reducing serving costs by 90-98% and improving response times.

    DEPTH ■■■■■5 min read4 days ago

    Architecture

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  6. 06Shopify · architecture

    Cross-store product clustering across millions of stores

    Shopify needed to group identical product listings from millions of different merchants under a single global identifier. To solve this at scale without comparing every possible pair, the team implemented a multi-stage pipeline using vector retrieval, a tiered scoring system of ML models, and a bounded graph clustering approach. This architecture successfully standardizes product data across the entire platform while controlling computational costs.

    DEPTH ■■■■■13 min read5 days ago

    Architecture

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