AI Briefing
Karrot news
The latest AI and developer news from Karrot, with short summaries.
Visit website →Carrot Launches Korea's First Public Beta for Advertising MCP, Sharing a Case Study on Expanding Developer Roles
Carrot launched Korea's first advertising MCP as a public beta on September 16.
Danggeun: Cache hit rate drops to 2.3% after GPT-5.6 swap, increasing LLM costs by 3.2x
Danggeun reduced costs to one-fifth by adding explicit breakpoints after costs increased 3.2x due to automatic cache rule changes following the transition to GPT-5.6.
Aurora MySQL: Index DDL Flaw Invalidates Reader Buffer Pool
A flaw has been identified in Aurora MySQL versions 3.08.0 to below 3.14 where index DDL operations clear the Reader buffer pool.
PickKarrot Releases QAHub for Running Real-Device Tests from a Single Sentence Input
The platform introduces a structure where AI generates test flows, executes them on real devices, and performs self-recovery upon failure.
PickKarrot Introduces Promise Queuing System for Concurrency Control of Neighborhood Walking Overlays
Handled 15 ordering change requests over 4.5 months, validated by 29 CI test cases.
How Daangn's Authentication Has Evolved
Daangn outlines the evolution of its authentication system from SMS verification and identity confirmation to SSO and global adaptation.
Beyond WebView: Why Karrot Chose Lynx
Karrot adopted Lynx to eliminate WebView's initial loading overhead.
Laying the Groundwork Beyond WebView: Why Danggeun Chose Lynx
Danggeun adopted Lynx as a screen-level rendering layer to reduce the initial loading limitations of WebView.
Daangn's Experiment Platform for More Convenient Experiment Design
Daangn's Data Value Team introduces an in-house experiment platform that supports everything from A/B test design to analysis.
What happens when you merge frontend and backend into one team
Karrot Market shared its experience of integrating frontend and backend developers into a single team and the resulting outcomes.
Introducing the Community System That Supports 10 Million MAU
This introduces the system architecture and technical choices behind the community service that Karrot built to handle 10 million MAU.
Is it enough for a design system team to just build a good design system
This piece covers what Danggeun's design system team thinks about beyond simply making components, in order to improve both the product's efficiency and quality.
How Karrot Built DT Platform, an ELT Platform for Migrating 200+ DBs
Karrot built DT Platform, a dedicated ELT platform, to efficiently transfer data from more than 200 global service DBs to BigQuery.
How Karrot Introduced LLM Release Notes for a Second-hand Trading Server, Readable by Anyone
Karrot accumulated deployment records in Notion and used an LLM to automatically generate release notes.
How Danggeun Protects Its Internal PyPI Proxy from Supply Chain Attacks
Danggeun blocked a Supply Chain Attack by applying a cooldown to its internal PyPI Proxy.
How Danggeun Responds to Python Supply Chain Attacks
Danggeun introduced a proxy cooldown to block Python package supply chain attacks.
The Age of Building Screens with One Prompt Line, and How to Make a 'Daangn-like Screen'
Instead of focusing on screen generation, Daangn evolved Kraft into an admin, CLI, and agent form aimed at automating SEED decision-making.
In an AI Era Where Everyone Handles Data, How Has the Data Team Changed Over the Past Year?
Karrot's Data Value Team sees AI not as a tool but as the core driver of transformation in data work, platforms, and culture.
The Journey to Auto-Scaling EKS Node Groups for Job Workloads
Using PodAffinity and do-not-disrupt, we auto-scaled EKS node groups for Job workloads.
Introducing EKS Node Group Autoscaling for Job Workloads
A case study on introducing EKS Node Group autoscaling tailored to Job workloads.