Read what ships.

01GitLab · 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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02Amazon 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 read4 days ago

AWS

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03ByteByteGo · migration

Why Shopify Migrated From React Native

Shopify migrated its mobile applications from React Native to native Swift and Kotlin because AI coding agents made the cost of duplicating features across platforms negligible. Using a greenfield approach and a custom tool called Helix to break down the migration into small, reviewable steps, the team successfully rewrote the apps. The resulting native applications showed significant improvements in startup time, crash rates, and app size.

DEPTH ■■■■■11 min read5 days ago

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04Martin Fowler · architecture

When Software Meets Hardware

A software engineering team modernizing a large-scale retail IoT system of 800,000 battery-powered sensors faced challenges integrating software practices with embedded hardware. By building physical sensor farms, virtual emulators, and self-diagnosing firmware, the team learned to design for intermittent connectivity, power efficiency, and fleet-level observability. The project succeeded by treating the physical world, hardware constraints, and engineering environments as core parts of the system lifecycle.

DEPTH ■■■■■12 min read10 days ago

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05ByteByteGo · architecture

How Uber Built a Genie to Answer Questions Correctly

Uber built an internal AI assistant called Genie to answer engineering support questions directly within Slack. The system uses a retrieval-augmented generation (RAG) architecture powered by Apache Spark, LangChain, and vector databases to fetch and explain documentation. As a result, Genie reduces repetitive on-call support burdens while providing source attribution and fallback paths to human engineers.

DEPTH ■■■■■13 min read6 days ago

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06Amazon Web Services · architecture

Multi-region disaster recovery for Amazon API Gateway WebSocket APIs

Real-time applications using WebSocket connections face disruptions during regional AWS outages because connections are tied to specific regions. The team implemented an active-passive multi-region disaster recovery architecture using Route 53 DNS failover, DynamoDB Global Tables, an automated canary health probe, and client-side exponential backoff with jitter. This design automatically detects failures, redirects traffic, and restores client state without manual intervention.

DEPTH ■■■■■10 min read11 days ago

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07Martin Fowler · performance

Are Harnesses Worth the Cost?

An experiment was conducted to evaluate whether behavioral harnesses improve coding agent reliability when building a complex backend-for-frontend service. While frontier models succeeded consistently with or without a harness, the harness significantly increased token usage, time, and cost without improving final output. However, for a cost-optimized model, the harness improved success rates from 30 percent to 100 percent.

DEPTH ■■■■■17 min read12 days ago

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08GitLab · scaling

Make every AI credit count: See, cap, and reduce agent spend

Uncontrolled AI agent spending can be mitigated by combining open-weight models, centralized context graphs to reduce retries, and usage analytics with credit caps. GitLab introduced these capabilities in its Duo Agent Platform to help platform teams trace, limit, and optimize AI credit consumption. The resulting architecture matches specific tasks to lower-cost models while maintaining task completion quality.

DEPTH ■■■■■6 min read12 days ago

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09Amazon Web Services · architecture

How UTS established a modern curriculum data services foundation on AWS

University of Technology Sydney rearchitected its curriculum data integration using serverless AWS services to decouple systems of record from downstream consumers. By implementing domain-driven design with an event-driven architecture and purpose-built persistence layers, the team achieved zero production incidents, low latency, and reduced operational overhead while managed by a single engineer.

DEPTH ■■■■■9 min read11 days ago

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10ByteByteGo · architecture

LLM Prompt Caching Versus Semantic Caching

This post compares prompt caching and semantic caching for large language models to reduce costs and latency. Prompt caching reuses intermediate KV states for shared prefixes, while semantic caching stores previously generated answers for similar questions using vector embeddings. The article explains the mechanics, pricing models, and trade-offs of both approaches.

DEPTH ■■■■■16 min read4 days ago

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11Amazon Web Services · tooling

Scope workloads and share resilience policies with AWS Resilience Hub

Engineering teams often struggle to scope workloads and maintain up-to-date resilience policies in shared Kubernetes clusters after migrations or deployments. AWS Resilience Hub introduced features enabling Kubernetes label-based resource scoping, generative AI-powered dependency insights, and cross-account resilience policy sharing via AWS Organizations. These capabilities allow teams to isolate specific workloads, prioritize dependency investigations, and enforce centralized recovery standards.

DEPTH ■■■■■14 min read12 days ago

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12ByteByteGo · architecture

How Netflix Taught an LLM to Recommend Movies So That You Keep Watching

Netflix developed GenRec, an LLM-based recommendation ranker designed to interpret viewing histories and item metadata in plain text to score movies and TV shows. By adapting an open-source foundation model in a two-phase training process and employing context engineering to reduce token usage, the team improved catalog ranking and satisfaction prediction. The system balances general language knowledge with domain-specific constraints to manage costs and personalization.

DEPTH ■■■■■15 min read2 weeks ago

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13Amazon Web Services · architecture

Stopping business email compromise with AI-driven email security: How VIPRE protects modern enterprises on AWS

VIPRE developed an AI-driven, cloud-native email security solution on AWS to protect enterprises against business email compromise and advanced phishing attacks. The system uses layered machine learning, semantic analysis, and dynamic sandboxing orchestrated via serverless containers and message queues to evaluate over half a million messages daily. In production testing, the architecture successfully identified thousands of BEC attempts while maintaining low-latency processing and reducing administrative overhead.

DEPTH ■■■■■12 min read12 days ago

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14Amazon Web Services · architecture

Bulk Executor for Amazon DynamoDB, Part 2: Lessons we learned the hard way

Engineering a bulk execution tool for Amazon DynamoDB using AWS Glue required addressing several architectural challenges, including cost estimation, graceful job termination, and error handling across hundreds of parallel workers. The team overcame limitations in CloudWatch logging and the Spark connector by combining serverless execution with direct API calls and distributed rate limiting. As a result, the tool provides a scalable, script-like interface for managing large-scale table operations safely.

DEPTH ■■■■■14 min read12 days ago

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15ByteByteGo · architecture

Why LLMs Agree With You Even When You’re Wrong

Large language models often agree with incorrect user claims because their training rewards human approval and helpfulness over strict accuracy. This behavior, known as sycophancy, is driven by reinforcement learning from human feedback and conversational pressure. Teams can mitigate this issue by using synthetic training data, Constitutional AI principles, and internal activation probes to penalize agreeable falsehoods.

DEPTH ■■■■■13 min read2 weeks ago

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16Martin Fowler · practice

Fragments: October 21

This post discusses commentary on AI usage in writing, the cancellation of the Grace Hopper Celebration, and reviews a detailed article by Cindy Sridharan on debugging with AI agents. The reviewed article highlights that AI agents excel at processing raw data rather than reading code first, and outlines a three-step debugging process involving controls, signals, and hypothesis validation. The lesson is that engineers must guide AI agents by setting up verification loops and providing raw data rather than human-centric abstractions.

DEPTH ■■■■■5 min read4 days ago

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17Amazon Web Services · architecture

Agentic antimicrobial resistance surveillance with AWS HealthOmics and Amazon Bedrock AgentCore

Processing public bacterial sequencing data for antimicrobial resistance surveillance typically requires specialized bioinformatics and SQL skills. To streamline this process, the team built a reference architecture using AWS HealthOmics, Amazon S3 Tables, and an Amazon Bedrock AgentCore conversational agent that ingests raw reads, normalizes findings, and answers plain-language questions with cited evidence. The resulting system automates the path from public accession numbers to natural-language epidemiological answers.

DEPTH ■■■■■10 min read13 days ago

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18ByteByteGo · architecture

How to Build Models Without Language, with Logical Intelligence

This article explores the limitations of large language models on constraint satisfaction problems like Sudoku and introduces energy-based reasoning models as an alternative. It explains how energy-based models utilize continuous latent spaces and descending energy gradients rather than left-to-right token generation. The result is a more reliable approach for non-language reasoning tasks.

DEPTH ■■■■■19 min read13 days ago

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19Martin Fowler · practice

Practitioner Voice: The Writing Category Nobody has Named Yet

The author explores a missing category of writing called Practitioner Voice, which is grounded in earned experience and visible personal judgment rather than academic rigor, corporate polish, or AI generation. They examine how AI can be used as an extended cognitive tool for practitioners without losing human accountability. Ultimately, the piece argues that maintaining personal judgment and consequence-bearing experience is essential for authentic professional writing.

DEPTH ■■■■■39 min read12 days ago

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20Amazon Web Services · tutorial

Deploy Oracle Database step by step on Amazon EVS with FSx for ONTAP

This post provides a step-by-step guide to deploying Oracle Database 19c on Amazon Elastic VMware Service using Amazon FSx for NetApp ONTAP as an NFS datastore. It covers provisioning storage, mounting datastores, installing Oracle, configuring SnapMirror for cross-region disaster recovery, and outlining four migration paths. The result is a fully functional enterprise database deployment that preserves existing operational workflows.

DEPTH ■■■■■11 min read3 weeks ago

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