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Tech Blog

Technical articles from the KGA engineering team

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Developer Tools15分

RevOps Tooling Stack 2026: Clari, Gong, Lakehouse and AI Forecasting

Clari, Gong, and Salesforce Einstein integration; contract data aggregation in a Lakehouse; AI-driven Net Retention forecasting; and billing x accounting x CPM finance integration — the full 2026 RevOps stack dissected.

RevOpsClariGongSalesforce EinsteinLakehouseNet Retention

岡田 玲奈

Head of Revenue Operations

2026-04-23
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Infrastructure16分

Edge Platform Benchmark 2026: Fastly, Akamai, AWS Lambda@Edge, Cloudflare Workers

Fastly Compute (WASM), Akamai EdgeWorkers, AWS Lambda@Edge, and Cloudflare Workers compared on cold start, memory, GB-second cost, geographic distribution, and WAF integration — with a Japan x Southeast Asia traffic selection matrix.

FastlyAkamaiAWSCloudflareLambda@EdgeWASMBenchmark

平井 翔大

Infrastructure Solution Architect

2026-04-23
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AI / AGI14分

Raising RAG Retrieval Quality in 2026: Hybrid, Rerankers, HyDE, and Late Chunking

Retrieval determines 80% of RAG quality. Hybrid (BM25 + Dense), two-stage ranking with Cohere Rerank-3/Voyage Rerank-2, query expansion via HyDE and Query2Doc, semantic/recursive/late-chunking strategies, and evaluation design with nDCG@10 and MRR — implementation code included.

RAGRetrievalRerankerHyDEChunkingEvaluation

石川 大地

AI Solutions Architect

2026-04-23
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Enterprise16分

Measuring Platform Engineering in 2026: DevEx Framework, SPACE, DORA, and DXI

Proving platform engineering ROI is the top CTO priority of 2026. DevEx Framework (Nicole Forsgren), SPACE, DORA, and Developer Experience Index (DXI) aligned with Opsera, Faros AI, and Jellyfish — plus a measurement strategy matched to organizational maturity.

Platform EngineeringDevExDORASPACEMetricsEnterprise

長岡 龍彦

Director of Platform Strategy

2026-04-23
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Enterprise17分

Retention Analytics 2026: Cohort Retention, Quick Ratio, Power User Curves, North Star Design, and Churn Prediction for Japanese SaaS

A systematic 2026 guide to retention analytics. Cohort Retention, Quick Ratio, L7/L28 Power User Curves, North Star Metric design, and churn prediction models (XGBoost, Causal Forest) for Japanese SaaS products.

RetentionCohortNorth StarPower UsersChurn PredictionXGBoostCausal Forest

濱田 大志

Principal Retention Scientist

2026-04-23
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Security14分

Secrets Management and Workload Identity 2026: Vault, SPIFFE, and AI Agent NHI Integration

Long-lived API keys are disappearing. HashiCorp Vault, AWS Secrets Manager, and Doppler combined with SPIFFE/SPIRE, Workload Identity Federation, and Secretless Broker — extended to AI agent NHI. Tool comparisons and implementation patterns.

Secrets ManagementVaultSPIFFESPIREWorkload IdentityNHIAWSGCP

佐々木 賢

Principal Platform Engineer

2026-04-23
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DevOps15分

Incident Management and LLM-Assisted Postmortems 2026: PagerDuty, Incident.io, Rootly, FireHydrant and Quantifying MTTR Reduction

Incident management SaaS evolved dramatically with LLM features in 2025-2026. Automatic timeline generation, impact estimation, blameless postmortem drafting, and action item tracking. PagerDuty, Incident.io, Rootly, and FireHydrant compared from an operations perspective.

Incident ManagementPagerDutyIncident.ioRootlyFireHydrantLLMPostmortem

本多 雄太

Incident Response Lead

2026-04-23
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Industry14分

Legal AI Copilots 2026: Harvey, Hebbia, Robin AI, LegalOn & LegalForce Deep Dive

Legal AI copilots have entered serious production use. Harvey AI, Hebbia, Robin AI, and Japan's LegalOn and LegalForce compared on contract review accuracy, hallucination control, and EN-JA translation quality.

Legal TechHarvey AIHebbiaRobin AILegalOnLegalForce

鈴木 恵理

Legal Tech Principal

2026-04-23
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Developer Tools15分

Building a Production-Grade Claude Code Plugin: Design, Distribution, Operations

Everything from zero to a published Claude Code plugin. Repo structure, plugin.json manifest, semantic versioning, marketplace distribution, telemetry, breaking-change management, and user settings merge strategy — using gsd-build and wshobson/agents as worked examples.

Claude CodePluginMarketplaceDevOpsTypeScriptDeveloper Tools

山田 健一

Staff Developer Experience Engineer

2026-04-22
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AI / AGI14分

Open LLM Fine-Tuning 2026: Synthetic Data, DPO Variants, Japanese-Specific Models

Synthetic data and DPO/IPO/KTO dominate 2026 fine-tuning. Claude Opus 4.7 teacher distillation, the Phi recipe, Swallow/Rinna/Sarashina, and reproducible recipes with axolotl and unsloth.

Fine-TuningDPOSynthetic DataJapanese LLMaxolotl

山本 健一

Applied Research Lead

2026-04-22
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Industry14分

From PLG to Sales-Led: The Playbook for Breaking the 80M Yen ARR Ceiling

PLG-only growth has a ceiling. Drawing on Notion, Linear, and Vercel, this post defines PQL criteria, SDR trigger events, and sales content design for a hybrid GTM that breaks through the 80M yen ARR wall.

PLGSales-LedPQLNotionLinearVercel

山本 大輔

VP of Revenue Strategy

2026-04-22
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Cloud14分

Vercel Edge Runtime 2026: Fluid Compute Meets Next.js 16 RSC

Vercel Fluid Compute collapses the old Edge/Serverless binary. Next.js 16 RSC edge rendering, streaming SSR, Partial Prerendering, and Edge Config-based feature flag operations — the 2026 production architecture.

VercelEdge FunctionsNext.jsRSCFeature FlagsFluid Compute

中野 彩子

Senior Frontend Infrastructure Engineer

2026-04-22
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Infrastructure14分

OLAP in 2026: ClickHouse Cloud, DuckDB 1.2, MotherDuck, and Turso in Production

ClickHouse Cloud serverless, DuckDB 1.2 HTTP server mode, MotherDuck's commercial launch, and Turso's LibSQL extensions. OLAP in 2026 is shifting from centralized clusters toward lightweight engines at the edge, browser, and notebook level — including Japanese-language workload considerations.

ClickHouseDuckDBMotherDuckTursoOLAPEdge AnalyticsWASM

藤原 和也

Senior Data Platform Engineer

2026-04-22
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Infrastructure15分

KV Cache Management 2026: FP8 KV, MoE Memory Profiles, CPU/NVMe Offload, Multi-Tenant Isolation

The definitive 2026 guide to KV cache in LLM serving. FP8 KV quality tradeoffs, MoE routing memory profiles, paging, CPU/NVMe offloading, LMCache vs SGLang RadixAttention benchmarks, and fairness in multi-tenant isolation.

KV CacheFP8MoELMCacheSGLangvLLMMulti-Tenant

吉田 遼

Senior Systems Engineer, LLM Serving

2026-04-22
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Security13分

The Future of Identity 2026: Passkeys, SCIM, SAML-to-OIDC Migration and the Japanese Enterprise Wall

B2B Passkey rollout crossed an inflection point in 2026. SAML-to-OIDC migration, SCIM automation, step-up and Adaptive MFA in unified operation — and a head-on treatment of the collision with Japan's My Number and shared-account culture.

PasskeysWebAuthnSCIMSAMLOIDCAdaptive MFAIdentity

大石 麻衣

Senior Identity Engineer

2026-04-22
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DevOps14分

Chaos Engineering in Production 2026: Gremlin, LitmusChaos, Chaos Mesh, and Japanese Enterprise Game Day Culture

More than a decade after Netflix's Chaos Monkey, chaos engineering in 2026 has shifted from "break things intentionally" to "design for failure and verify on a schedule." Includes how to navigate Japan's planned-outage culture.

Chaos EngineeringGremlinLitmusChaosChaos MeshKubernetesGame Day

安藤 美佐

Staff Reliability Engineer

2026-04-22
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Developer Tools14分

Micro Frontends Reconsidered 2026: Module Federation 2.0, Rspack/Vite, and Japanese Enterprise Migrations

Module Federation 2.0, Single-SPA, Rspack/Vite integration, edge delivery, and cache invalidation strategy — with concrete design decisions and gotchas from phased migrations at major Japanese financial and SaaS companies in 2025-2026.

Micro FrontendModule FederationRspackViteArchitectureEnterprise

藤本 知佳

Staff Frontend Engineer

2026-04-22
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Enterprise13分

Sales Engineering & Revenue Ops AI Copilots 2026: Gong, Clari, Breeze, Glossary Deep Comparison

Gong Anywhere, Clari Copilot, HubSpot Breeze, and Glossary AI compared on real-time call analysis, deal risk scoring, and Japanese-language support — plus where Japanese B2B SaaS RevOps stands today.

Sales TechRevOpsGongClariHubSpot BreezeGlossary AI

北村 智宏

Revenue Operations Architect

2026-04-22
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AI / AGI13分

Claude Plugins Ecosystem: Building MCP Servers, Slash Commands & Hooks

A deep dive into the Claude Code plugin ecosystem. Covers popular plugins like get-shit-done, simplify, and ultrareview, plus building custom plugins and securing shell-execution workflows.

Claude CodePluginsMCPSlash CommandsHooks

田中 翔太

Lead AI Engineer

2026-04-22
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AI / Market14分

NVIDIA/TSMC/ASML Q1 2026 Earnings: AI Semiconductor Supply Chain Analysis

NVIDIA's data center segment hit $52.1B in Q1 2026, up 71% year-over-year. A data-driven dissection of TSMC 2nm yield, ASML EUV shipments, hyperscaler capex, and downstream impact on Japanese equipment makers.

NVIDIATSMCASMLSemiconductorEarningsJapan Tech

木村 啓介

Senior Semiconductor Analyst

2026-04-21
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Developer Tools14分

AI Agent SDK Deep Comparison 2026: Anthropic Agent SDK, Vercel AI SDK 5, LangGraph, Mastra, OpenAI Assistants v2

Production-focused comparison of Anthropic Agent SDK, Vercel AI SDK 5, LangGraph Studio, Mastra, and OpenAI Assistants v2. Covers agent loop design, tool-call conventions, state management, and observability.

Agent SDKAnthropicVercel AI SDKLangGraphMastraOpenAI

西野 翔

Principal Agent Engineer

2026-04-21
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Enterprise15分

Usage-Based vs Subscription: SaaS Pricing Migration in the AI Era

The evolution of consumption-based pricing at Snowflake, Datadog, and Twilio — plus the "token as unit of consumption" debate in the AI API era. How to design hybrid pricing that fits Japanese enterprise budget cycles.

SaaS PricingUsage-BasedSubscriptionAI APISnowflakeDatadog

藤井 恵美

Principal Pricing Strategist

2026-04-21
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Infrastructure15分

Cloudflare Workers & Durable Objects Deep Dive: Designing Global State Machines

Durable Objects' single-thread transaction model, Workers KV vs Hyperdrive vs D1 trade-offs, Workers AI inference routing, and hot-path optimization via Rust + WASM bindings — all codified as of 2026.

CloudflareWorkersDurable ObjectsWASMRustTypeScriptEdge Computing

村田 聡

Principal Edge Architect

2026-04-21
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AI / AGI14分

Embedding Models 2026 Landscape: text-embedding-3-large, Voyage-3, Cohere Embed v4, BGE-M3, Jina v3

2026 embedding model leaders measured on MTEB, BEIR, and JMTEB. OpenAI text-embedding-3-large, Voyage-3, Cohere Embed v4, OpenAI Embed-4, BGE-M3, and Jina v3 compared in English and Japanese. Matryoshka Representation dimensionality reduction and ColBERT Late Interaction covered at implementation depth.

EmbeddingMTEBJMTEBMatryoshkaColBERTRAG

青木 知美

Senior AI Research Engineer

2026-04-21
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Data14分

Transformation Layer 2026: dbt Core 1.10 vs SQLMesh 0.150 vs Dagster 1.10

dbt Core 1.10, SQLMesh 0.150, and Dagster 1.10 compared on Semantic Layer, incremental materialization, CI/CD, and cost monitoring. Covers dbt Labs' commercial pivot, SQLMesh virtual data environments, and Dagster asset-centric maturity.

dbtSQLMeshDagsterSemantic LayerMetricFlowCube.devCI/CD

久保 真由美

Lead Analytics Engineer

2026-04-21
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Infrastructure16分

LLM Serving Batching Strategies 2026: Continuous Batching, Chunked Prefill, RadixAttention

How continuous batching, chunked prefill, PagedAttention, RadixAttention, and sorted batching affect TTFT, ITL, and throughput. Enterprise-focused coverage of prompt cache strategies including system-prompt sharing and tenant partitioning.

BatchingvLLMSGLangPagedAttentionRadixAttentionSLO

竹内 葵

Staff Serving Infrastructure Engineer

2026-04-21
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DevOps14分

Designing Golden Paths: Backstage Templates, Cookiecutter, Nx Plugins for Opinionated Scaffolding

Golden Paths are the most frequently touched platform engineering artifact. How to combine Backstage Software Templates, Cookiecutter, and Nx Plugins to create templates that are production-ready from day one — including CI integration and automatic Secret provisioning.

Golden PathScaffoldingBackstageCookiecutterNxDevOps

柴田 美月

Staff Developer Experience Engineer

2026-04-21
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Data16分

Experimentation Platforms 2026: Statsig, LaunchDarkly, GrowthBook, and Unleash with CUPED and Sequential Testing

Statsig, LaunchDarkly, GrowthBook, and Unleash compared as experimentation platforms. Bayesian vs frequentist approaches, CUPED, Sequential Testing, Guardrail Metrics implementation differences, and the server-side vs client-side decision axis.

StatsigLaunchDarklyGrowthBookUnleashBayesianCUPEDFeature Flags

西田 明香

Principal Experimentation Scientist

2026-04-21
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AI / AGI14分

Astro 5 / Qwik 2 / Svelte 5 in 2026: Where Islands, Resumability, and Runes Win

The React/Next.js monoculture is cracking. Astro 5 Server Islands, Qwik 2 Resumability, Svelte 5 runes, and Solid Start 1.0 compared on three axes — content-first, interaction-first, and DX — with project-type selection criteria.

AstroQwikSvelteSolidFrontendPerformance

河野 拓真

Senior Frontend Architect

2026-04-21
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Developer Tools12分

Skills vs Hooks vs Subagents: The Definitive Guide to Claude Code Extensibility

Skills encode procedural knowledge, Hooks intercept events, Subagents delegate autonomous work. A decision matrix and real-world patterns — pre-commit security review, long-form research delegation, and domain expert specialization.

Claude CodeSkillsHooksSubagentsPluginAI/AGI

田中 翔太

Lead AI Engineer

2026-04-20
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Regulation13分

US AI Regulation Patchwork: Executive Orders, State Laws, NIST RMF v2, and SEC Disclosure

The regulatory landscape for Japan-based IT companies operating in the US — no federal unified law but a patchwork of executive orders (2024-2026), post-SB 1047 California, Colorado AI Act enforcement, NIST RMF v2, and SEC/FTC AI-related actions.

US RegulationNIST AI RMFSECFTCState Laws

斎藤 麻衣

US Regulatory Affairs Lead

2026-04-20
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Data15分

Vector Database Production Comparison 2026: pgvector 0.9, Qdrant 1.12, Weaviate 1.28, Chroma 1.0, Pinecone Serverless

pgvector 0.9 HNSW iterative scan, Qdrant 1.12 quantized GPU indexing, Weaviate 1.28 multi-tenancy, and Pinecone Serverless real pricing curves — all benchmarked at 100M vector scale. p99 latency, recall, sharding strategy, and hybrid search implementation for production migration decisions.

Vector DatabasepgvectorQdrantWeaviatePineconeHNSWRAG

橋本 祐介

Principal Data Platform Engineer

2026-04-20
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Data15分

Lakehouse Showdown 2026: Apache Iceberg 1.7, Delta Lake 3.3, and Apache Hudi 1.0

Snowflake Iceberg write GA, Databricks Unity Catalog going open, and AWS S3 Tables arriving — the table format wars showed signs of convergence in 2026. Real benchmarks across Trino 465, Spark 4.0, DuckDB 1.2, and StarRocks 3.4.

Apache IcebergDelta LakeApache HudiSnowflakeDatabricksTrinoS3 Tables

川口 拓也

Principal Data Engineer

2026-04-20
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Infrastructure15分

Speculative Decoding in Production 2026: EAGLE-3, Medusa-2, and Lookahead Benchmarks

Internals and production pitfalls of EAGLE-3, Medusa-2, and Lookahead decoding. Draft model selection, accept-rate tuning, vLLM/SGLang configuration examples, and real throughput improvements of 40-60% on 70B and MoE models.

Speculative DecodingEAGLEMedusavLLMSGLangLLM Inference

三木 純平

Principal Inference Engineer

2026-04-20
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Developer Tools15分

IDP Selection 2026: Backstage v1.30 vs Port vs Cortex vs OpsLevel vs Humanitec

IDP selection is the defining platform engineering decision of 2026. Backstage v1.30, Port, Cortex, OpsLevel, and Humanitec compared on plugin ecosystem, TechDocs, Software Catalog, Scorecards, and implementation cost — with Japanese enterprise case studies.

IDPBackstagePortCortexPlatform EngineeringDeveloper Tools

荒木 健斗

Principal Platform Engineer

2026-04-20
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Data15分

Product Analytics Deep Comparison 2026: PostHog 1.100, Mixpanel, Amplitude, Heap, and June

PostHog 1.100, Mixpanel, Amplitude, Heap, and June compared for production teams. Self-host vs SaaS, cookieless tracking and server-side events, natural language query performance, and real TCO in Japanese yen.

PostHogMixpanelAmplitudeHeapJunePrivacyCookieless

秋山 翔

Head of Product Analytics

2026-04-20
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Security13分

ZTNA Implementation 2026: Running BeyondCorp, Cloudflare Access, and Tailscale in Japanese Enterprises

VPN elimination is becoming realistic in 2026. BeyondCorp Enterprise, Cloudflare Access, Tailscale, Twingate, and Zscaler compared on device posture, mTLS, and SSO integration — with practical coverage of Japan-specific barriers like approval workflows, leaver accounts, and IT permission segregation.

Zero TrustZTNABeyondCorpCloudflare AccessTailscalemTLSSSO

松田 健

Principal Security Architect

2026-04-20
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Infrastructure15分

SLO/SLI/Error Budget Policy Design Practice 2026: Multi-Window Multi-Burn-Rate Alerts and LLM Service Reliability Targets

A decade after the SRE book, SLO operations have matured past "define and dashboard" to board-agreed Error Budget Policies and multi-window multi-burn-rate alerts as standard practice. Includes SLI design specific to LLM services.

SRESLOSLIError BudgetLLMObservability

中川 一郎

Principal SRE

2026-04-20
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Developer Tools15分

React Server Components 2026 in Production: Rebuilding with Next.js 16 PPR and use cache

Stable PPR (Partial Prerendering), use cache, and cache tags in Next.js 16 — design decisions and migration pitfalls from a team that shipped RSC to production. Real bundle size reductions, Suspense boundary placement, and stale-while-revalidate operations.

ReactNext.jsRSCPPRStreamingPerformance

今井 理香

Principal Frontend Engineer

2026-04-20
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Enterprise13分

Customer Support AI Copilots 2026: Intercom Fin 3, Zendesk Copilot, Ada, Dialpad Ai Benchmark

Intercom Fin 3, Zendesk Copilot, Ada, and Dialpad Ai benchmarked on deflection rate, human escalation accuracy, CSAT impact, Japanese honorific handling, and compliance recording requirements.

Customer SupportIntercom FinZendeskAdaDialpadCX

前田 彩香

CX Automation Lead

2026-04-20
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Open Source15分

Inference Engine Wars 2026: vLLM, SGLang, TensorRT-LLM, llama.cpp, MLX

vLLM 0.8, SGLang 0.4, TensorRT-LLM, llama.cpp, and MLX compared head-to-head on throughput, latency, VRAM, batching strategy, and quantization. Practical tuning guide for 7B, 70B, and 405B models.

vLLMSGLangTensorRT-LLMInferenceQuantization

佐藤 美咲

ML Infrastructure Engineer

2026-04-19
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AI / AGI14分

LLM Observability 2026: OpenLLMetry, Prompt Traces & Hallucination Detection in Production

OpenLLMetry/OpenInference semantic conventions, tool-call span attributes, and how to choose between Langfuse, Helicone, Arize Phoenix, and W&B Weave. Cost allocation by feature, latency SLIs, and hallucination detection built on Grafana Tempo and ClickHouse.

ObservabilityOpenTelemetryLangfuseGrafanaClickHouseLLM Ops

宮崎 慎太郎

Senior Observability Engineer

2026-04-19
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Industry11分

AI Market Financial Reactions 2026: NVIDIA, Anthropic Funding, TSMC & ETF Trends

AI-related equities continue to swing wildly into 2026. An investor-focused analysis of NVIDIA's correction, Anthropic's fundraise, OpenAI's valuation, TSMC/ASML prices, and AI ETF flows.

AI MarketNVIDIAAnthropicTSMCETF

中村 大輔

AI Industry Analyst

2026-04-19
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Developer Tools14分

MCP Server Deep Dive: Building the Heart of Claude Plugins

Model Context Protocol server internals, plus hands-on implementation of Slack integration, DB queries, and filesystem access. Covers permission models and comparison with OpenAI Function Calling and ChatGPT Plugins.

ClaudeMCPPluginTypeScriptSecurityDeveloper Tools

佐藤 美咲

Principal Platform Engineer

2026-04-18
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Finance13分

AI Unicorn Private Market 2026: Anthropic, OpenAI IPO, xAI, Mistral Valuations

Anthropic at $320B, OpenAI IPO speculation, xAI Series F, Mistral's European strategy, Cohere's enterprise pivot. The latest private market dynamics and secondary trading activity — and what it means for Japanese investors.

AnthropicOpenAIxAIMistralIPOPrivate Markets

森 千里

Private Markets Strategist

2026-04-18
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AI / AGI12分

AI Agent Marketplace Monetization 2026: GPT Store, Claude Artifacts & Gemini Gems Economics

The AI agent marketplace is a real business now. Usage-based, subscription, and revenue-share models analyzed with real data from GPT Store, Claude Artifacts, and Gemini Gems.

MarketplaceMonetizationGPT StoreClaudeGemini

高橋 由紀

AI Platform Economist

2026-04-18
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AI / AGI15分

Migrating from RAG to Agentic Workflows: Strategy and Evaluation Redesign

Static RAG is showing its limits on complex business workflows. Migration to agentic workflows is irreversible — but you don't have to abandon RAG. Hybrid design, cost-quality tradeoffs, governance changes, and evaluation harness reconstruction at implementation depth.

RAGAgentic WorkflowsArchitectureEvaluationMigration

酒井 弘樹

Principal AI Architect

2026-04-17
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Industry12分

Enterprise AI Spending Shift 2026: SaaS Budget Reallocation and Fortune 500 Reality

Fortune 500 companies now have standalone AI budget line items, with LLM APIs at 14% of enterprise cloud spend. SaaS budget reallocation, build-vs-buy decisions, and how NTT Data, NEC, and Fujitsu are responding — verified with Q1 2026 data.

Enterprise AISaaSCloud SpendMcKinseyGartnerJapan SI

大野 一馬

Enterprise Technology Strategist

2026-04-16
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AI / AGI14分

Open LLM Shootout 2026: Qwen 3 vs Llama 4 vs DeepSeek R2 vs Mistral Large 3

Qwen 3 72B, Llama 4 405B, DeepSeek R2, and Mistral Large 3 pushed hard on MMLU-Pro, SWE-Bench, tool use, and inference cost. A use-case recommendation matrix included.

Open SourceLLMQwenLlamaDeepSeekBenchmark

田中 翔太

Lead AI Engineer

2026-04-16
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Policy13分

Japan's AI Governance Evolution: Hiroshima Process, AI Promotion Act, and Copyright 30-4 in 2026

Two years after the Hiroshima AI Process international code of conduct — METI guideline updates, PPC LLM-specific guidance, the 2026 AI Promotion Act deliberations, and Copyright Article 30-4 interpretation. Japan's position benchmarked against Singapore, South Korea, and India.

広島AIプロセスAI推進法著作権法PPCアジア比較

小林 健二

Principal Policy Analyst

2026-04-16
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AI / AGI14分

Claude Opus 4.7 vs Sonnet 4.6: Benchmarks, Cost & When to Use Which

Technical breakdown of Claude Opus 4.7 and Sonnet 4.6: SWE-bench, Terminal-bench, and MMLU-Pro scores, cost efficiency, prompt caching behavior, and a use-case decision guide.

ClaudeOpusSonnetBenchmarkPrompt Caching

田中 翔太

Lead AI Engineer

2026-04-16
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Infrastructure15分

Enterprise LLM Inference Patterns 2026: GPU Sharing, Autoscaling & SLO-Driven Routing

When to self-host vs use managed inference (Bedrock/Vertex/Azure AI), GPU sharing via MIG/MPS, KEDA queue-length autoscaling, and SLO-driven routing. A real case that reduced serving costs from $85k/month to $12k/month.

LLM InferenceKubernetesKEDAMIGAutoscalingCost Optimization

池田 千夏

Staff Platform Engineer

2026-04-15
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Developer Tools15分

Long-Horizon Agent Memory Architectures: Episodic Stores, Entity Graphs, MemGPT & Anthropic Memory Tool

Memory system design for long-running agents. Episodic vector stores, KùzuDB/Neo4j entity graphs, MemGPT hierarchical memory, and Anthropic Memory Tool patterns with pgvector/DuckDB code examples.

MemoryVector StorepgvectorMemGPTKnowledge Graph

渡辺 光輝

Memory Systems Architect

2026-04-14
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Enterprise14分

Zero-Trust Identity for AI Agents: NHI and Audit Trail Design

Human authentication models break down when AI agents operate internal systems autonomously. Non-Human Identity, scoped API keys, mTLS, and audit trail design explained with Okta for Agents, Workload Identity Federation, and HashiCorp Boundary examples.

Zero TrustAI AgentsNHIOAuthmTLSSecurity

内田 拓海

Principal Security Architect

2026-04-14
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AI / AGI12分

The Rise of AI Agent Marketplaces: SDKs, LangGraph Studio & Emerging Business Models

AI agent marketplaces are maturing fast. In-depth analysis of the Anthropic Agent SDK, Vercel AI SDK agents, LangGraph Studio, and new revenue models including revenue sharing and consumption pricing.

AI AgentMarketplaceLangGraphVercel AI SDKAnthropic Agent SDK

佐藤 美咲

ML Infrastructure Engineer

2026-04-13
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Regulation14分

EU AI Act Enforcement Phase 2026: Fines, National Authorities, and Cross-Border SaaS Compliance

The EU AI Act entered full enforcement in 2026. Covers prohibited practices, high-risk system obligations, GPAI rules, CNIL and BfDI enforcement actions, and a checklist for Japanese SaaS operators.

EU AI ActGDPRGPAIComplianceCross-Border

中村 理恵

Senior Regulatory Counsel

2026-04-12
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Infrastructure16分

AI Accelerator Deep Dive 2026: H200, B200, GB200 NVL72, MI300X, TPU v6, Trainium3, Gaudi 3

Cross-platform comparison of MFU, HBM bandwidth, NVLink/Infinity Fabric topology, and TCO for 70B training. Includes Japan procurement availability via NTT, KDDI, and Sakura Internet.

GPUTPUNVIDIAAMDGoogle CloudAWSIntelHardware

長谷川 武

Principal Infrastructure Architect

2026-04-11
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Enterprise14分

Measuring AI Copilot ROI Honestly: DevEx Methodology in 2026

Reporting Copilot ROI as "acceptance rate x time saved" is over. Combining DORA, SPACE, controlled experiments, and bug-rate deltas, this post presents an honest measurement methodology using data from LINE Yahoo, Mercari, and Cybozu.

AI CopilotDevExDORASPACEROIProductivity

伊藤 絵里

Principal DevEx Researcher

2026-04-11
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Industry12分

Generative AI Regulation 2026: EU AI Act, US Executive Orders & Japan's AI Policy

A comprehensive look at 2026 AI regulation. Covers EU AI Act enforcement, revised US executive orders, Japan's AI Basic Act, and what enterprises need to do today to stay compliant.

AI RegulationEU AI ActGovernanceCompliancePolicy

山田 美和

AI Policy Analyst

2026-04-11
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AI / AGI14分

Open-Source LLM Landscape 2026: Llama 4, Mistral Large 3, Qwen 3, DeepSeek, Phi-4

A full survey of the 2026 open-source LLM field. Compares Llama 4, Mistral Large 3, Qwen 3, DeepSeek, and Phi-4, plus inference optimization with vLLM, SGLang, and TensorRT-LLM.

Open SourceLLMvLLMSGLangTensorRT-LLM

佐藤 美咲

ML Infrastructure Engineer

2026-04-10
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AI / AGI12分

OpenClaw: Open-Source AI Agent Framework Deep Dive

An architectural breakdown of OpenClaw, the next-generation AI agent framework positioned beyond LangChain, CrewAI, and AutoGen. From tool-use patterns to memory system internals.

AI AgentLangChainFunction CallingOSS

田中 翔太

Lead AI Engineer

2026-04-09
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AI / AGI15分

Hermes 3 & Local LLM Inference Practical Guide

A complete guide to deploying Nous Research's Hermes 3 locally. Covers Ollama and vLLM inference optimization, GGUF quantization, and benchmark comparisons against cloud APIs.

Hermes 3OllamavLLMQuantizationGGUF

佐藤 美咲

ML Infrastructure Engineer

2026-04-08
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AI / AGI14分

Path to AGI: Autonomous Agents & Super Brain Architecture

Designing a multi-LLM orchestration layer that dynamically routes across GPT-4o, Claude, and Gemini. Architecture and implementation of a Super Brain system where specialized sub-agents report to a meta-agent.

AGIMulti-AgentLLM OrchestrationSuper Brain

田中 翔太

Lead AI Engineer

2026-04-08
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Quantum11分

Free Quantum Computing: From China's Origin Quantum to IBM Qiskit

A hands-on comparison of free quantum computing platforms. We actually ran quantum circuits on Origin Quantum, IBM Quantum, Google Cirq, and Amazon Braket's free tiers.

Quantum ComputingQiskitOrigin QuantumCirq

山田 健一

Research Engineer

2026-04-07
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AI / AGI13分

MDS: Deploying Large Models to Edge with Model Distillation System

How to distill a 70B-parameter model down to 7B for consumer GPUs and edge devices. Practical GPTQ vs AWQ vs GGUF comparison and distillation techniques that preserve output quality.

DistillationQuantizationEdge AIGGUFGPTQ

佐藤 美咲

ML Infrastructure Engineer

2026-04-06
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Developer Tools10分

2025 Free AI API Guide: 15 Services You Should Know

A practitioner's review of 15 free AI APIs — Groq, Together.ai, Hugging Face, Gemini, and more. Covers rate limits, available models, and the best use cases for each.

APIFree TierLLMInference開発ツール

鈴木 大輔

Full-Stack Engineer

2026-04-06
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Developer Tools9分

CLI Tools 2025: Essential DevOps Engineer Toolchain

The CLI tools DevOps engineers actually use in 2025 — from starship, ripgrep, lazygit, and k9s to AI-powered CLIs. Includes setup steps and real-world usage tips.

CLIDevOpsProductivityTerminalInfrastructure

木村 拓也

DevOps Engineer

2026-04-05
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AI / AGI11分

Subvertentes: Advanced Prompt Engineering & Multi-Step Reasoning

Practical prompt engineering beyond Chain-of-Thought, Tree-of-Thought, and Graph-of-Thought. Multi-step prompt chaining for business process automation, illustrated with KGA's real client projects.

Prompt EngineeringCoTToTAutomationLLM

田中 翔太

Lead AI Engineer

2026-04-04
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AI Models12分

DeepSeek R1: The Impact of a Reasoning-Specialized Model

DeepSeek R1 beat GPT-4o on reasoning benchmarks. A technical analysis of its chain-of-thought internals and what its open-source strategy means for the broader AI ecosystem.

DeepSeekReasoningChain-of-ThoughtOpen SourceBenchmarks

中村 悠太 / Yuta Nakamura

Lead AI Engineer

2026-04-04
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AI Models14分

Claude 4 Sonnet/Opus: Comprehensive Review of Anthropic's Latest Models

The Claude 4 family is a full redesign. We review Constitutional AI advances, tool-use performance gains, and coding benchmark results — all backed by hands-on test data.

ClaudeAnthropicConstitutional AITool UseCoding

林 美咲 / Misaki Hayashi

Infrastructure Lead

2026-04-03
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AI Models10分

Gemini 2.0 Flash: Google's Multimodal Strategy

Testing Gemini 2.0 Flash's multimodal capabilities and 1M-token context in practice. Also covers when to use Gemma open models versus the full Gemini API.

GeminiGoogleMultimodalLong ContextGemma

金 東勲 / Kim Dong-hoon

Security Engineer

2026-04-02
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AI Models11分

Llama 4: Meta's Open Source Revolution Accelerates

Llama 4 arrives with Scout and Maverick variants. Analysis of the Mixture of Experts architecture and its implications for the open-source AI community.

LlamaMetaOpen SourceMoEScoutMaverick

鈴木 健一 / Kenichi Suzuki

Full-Stack Engineer

2026-04-02
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AI Models9分

Grok-3: xAI's Challenge and Real-Time AI

Grok-3 carves out a unique position through real-time data integration. We test X (Twitter) integration in practice and compare performance against other leading models.

GrokxAIReal-time AIX PlatformBenchmarks

中村 悠太 / Yuta Nakamura

Lead AI Engineer

2026-04-01
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AI Models11分

Mistral Large 2 and Mixture of Experts Complete Guide

A technical deep dive into Mistral Large 2's MoE architecture. Covers Codestral's coding performance and the practical GDPR compliance advantages of a European-hosted model.

MistralMoEEuropean AICodestralOpen Weight

林 美咲 / Misaki Hayashi

Infrastructure Lead

2026-03-31
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AI Models10分

Qwen 3: Alibaba's AI Reaches World-Class Level

Qwen 3 achieves top-tier performance in multilingual tasks, math, and coding. Analysis of its open-weight strategy and measurable advantages in Asian languages.

QwenAlibabaMultilingualOpen WeightMath

金 東勲 / Kim Dong-hoon

Security Engineer

2026-03-31
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AI / AGI15分

Running RAG in Production: Design Patterns and Pitfalls

RAG is easy to prototype, hard to operate. KGA shares real-world design patterns and failure stories from production: chunking strategies, reranking, and evaluation pipelines.

RAGVector DBEmbeddingChunkingReranking

中村 悠太 / Yuta Nakamura

Lead AI Engineer

2026-03-30
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AI / AGI13分

LoRA/QLoRA Fine-Tuning Practical Guide 2026

A practitioner's guide to LLM fine-tuning with LoRA and QLoRA. Covers dataset preparation, optimal hyperparameter settings, and evaluation — drawn from KGA's real client engagements.

LoRAQLoRAFine-tuningDatasetHyperparameters

林 美咲 / Misaki Hayashi

Infrastructure Lead

2026-03-29
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Developer Tools12分

AI Code Assistants Comparison 2026: Cursor vs Claude Code vs Copilot

A head-to-head comparison of Cursor, Claude Code, and GitHub Copilot on real development tasks. Ten benchmark tasks covering code generation accuracy, refactoring, cost, and developer experience.

CursorClaude CodeGitHub CopilotAI CodingIDE

鈴木 健一 / Kenichi Suzuki

Full-Stack Engineer

2026-03-29
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AI / AGI10分

FLUX vs SDXL: The Cutting Edge of AI Image Generation

A thorough comparison of FLUX.1 and Stable Diffusion XL image generation. Includes ComfyUI workflow construction and practical prompt engineering techniques.

FLUXSDXLImage GenerationComfyUIPrompt Engineering

中村 悠太 / Yuta Nakamura

Lead AI Engineer

2026-03-28
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AI / AGI11分

AI Video Generation 2026: Comparing Sora, Kling, and Runway Gen-4

Sora, Kling, and Runway Gen-4 tested on actual business use cases. An honest review of quality, cost, and constraints across all three tools.

SoraKlingRunwayVideo GenerationAI Video

林 美咲 / Misaki Hayashi

Infrastructure Lead

2026-03-27
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Infrastructure14分

Kubernetes Production 2026: Lessons We Learned

Three years of running Kubernetes in production, shared honestly. Autoscaling traps, observability setup, cost optimization, and post-incident analyses of real outages.

KubernetesK8sAutoscalingObservabilityCost Optimization

金 東勲 / Kim Dong-hoon

Security Engineer

2026-03-27
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Infrastructure11分

Terraform vs Pulumi: Complete IaC Tool Comparison

After partially migrating from Terraform to Pulumi, KGA compares both tools from an operational perspective. Includes the migration decision criteria and the actual migration process.

TerraformPulumiIaCInfrastructureDevOps

鈴木 健一 / Kenichi Suzuki

Full-Stack Engineer

2026-03-26
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Security13分

Zero Trust Architecture Implementation Record

The full record of KGA's real Zero Trust deployment. BeyondCorp model implementation, identity-based access control, phased migration process, and measured outcomes.

Zero TrustBeyondCorpIdentitySecurityAuthentication

金 東勲 / Kim Dong-hoon

Security Engineer

2026-03-25
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AI / AGI12分

7 Lessons Learned from Deploying AI Agents to Production

Seven hard lessons from running AI agents in production. Failure modes, guardrail design, monitoring, and cost runaway prevention — illustrated with real failure cases.

AI AgentProductionGuardrailsMonitoringCost Control

中村 悠太 / Yuta Nakamura

Lead AI Engineer

2026-03-25
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Infrastructure10分

Edge Computing in Practice: What You Can Do with Cloudflare Workers

Real-world edge computing examples using Cloudflare Workers, D1, R2, and KV. Performance benchmarks and concrete use cases from production deployments.

Edge ComputingCloudflare WorkersD1R2KVPerformance

鈴木 健一 / Kenichi Suzuki

Full-Stack Engineer

2026-03-24
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AI / AGI14分

vLLM & TensorRT-LLM: Inference Server Optimization in Practice

Benchmarking vLLM's PagedAttention against TensorRT-LLM's FP8 kernels. Covers batching strategy, KV cache management, and production operations know-how.

vLLMTensorRT-LLMInferencePagedAttentionKV Cache

中村 悠太

Senior AI Engineer

2026-03-23
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Developer Tools13分

Next.js 16 Migration Guide: App Router Practical Patterns

Challenges and solutions from our Next.js 16 migration. React Server Components patterns, streaming, cache strategy optimization — the full production migration record.

Next.jsApp RouterRSCReact Server ComponentsMigration

林 美咲

Frontend Tech Lead

2026-03-23
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Infrastructure12分

PostgreSQL 17 New Features & Our Migration Record

PostgreSQL 17 validated in production. JSON_TABLE, incremental backups, MERGE improvements, and performance gains — with real benchmarks and our PG16-to-PG17 migration steps.

PostgreSQLDatabaseMigrationPerformanceJSON

金 東勲

Infrastructure Engineer

2026-03-22
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AI / AGI13分

Building an LLM Evaluation Framework: How to Measure Quality

Building an LLM output quality evaluation framework from scratch. Custom benchmarks, calibration against human evaluation, and the design and operation of automated test pipelines.

LLMEvaluationBenchmarkTestingQuality Assurance

鈴木 健一

ML Platform Engineer

2026-03-21
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Security11分

Docker Container Security Hardening: Practical Checklist

A checklist-driven guide to container security. Rootless Docker, image scanning, runtime protection, and network isolation — covering everything a production environment requires.

DockerSecurityContainerDevSecOpsRootless

中村 悠太

Senior AI Engineer

2026-03-21
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Infrastructure12分

gRPC vs REST: Choosing Microservice Communication

How to choose between gRPC and REST for inter-service communication. Protocol Buffers, streaming, error handling — plus real benchmark data from KGA's production systems.

gRPCRESTMicroservicesProtobufAPI Design

林 美咲

Frontend Tech Lead

2026-03-20
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AI / AGI11分

How We Cut API Costs by 80% with Prompt Caching

The full story behind reducing LLM API spend by 80% through prompt caching. From exact-match to semantic caching, with Redis-based implementation patterns.

Prompt CachingCost OptimizationRedisSemantic CacheLLM

金 東勲

Infrastructure Engineer

2026-03-19
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Developer Tools12分

GitHub Actions Advanced Workflows: Matrix Builds to Self-hosted Runners

Advanced GitHub Actions in practice. Matrix build optimization, reusable workflows, caching strategies, and how to build and operate self-hosted runners.

GitHub ActionsCI/CDDevOpsAutomationSelf-hosted Runners

鈴木 健一

ML Platform Engineer

2026-03-19
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Infrastructure13分

WebAssembly Transforms Server-Side: Wasmtime, Spin, Fermyon

WebAssembly is moving beyond the browser into server-side runtimes. An honest assessment of Wasmtime, Spin, and Fermyon Cloud — including real performance data and practical limitations.

WebAssemblyWASMWasmtimeSpinEdge Computing

中村 悠太

Senior AI Engineer

2026-03-18
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AI / AGI14分

AI-Powered Monitoring: From Anomaly Detection to Incident Response

Building an AI-powered monitoring system from scratch. Metric anomaly detection, automated log analysis, alert aggregation, and incident response automation — with an honest AIOps evaluation.

AIOpsMonitoringAnomaly DetectionObservabilityIncident Response

林 美咲

Frontend Tech Lead

2026-03-17
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Infrastructure12分

Redis 8: Beyond Caching

Using Redis 8's new features for non-cache workloads. Vector search, Pub/Sub, Streams, and native JSON support — all with implementation patterns and real performance measurements.

RedisVector SearchPub/SubStreamsJSON

金 東勲

Infrastructure Engineer

2026-03-17
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Security13分

Software Supply Chain Security 2025

Supply chain attack realities and defenses. SBOM generation, Sigstore artifact signing, SLSA framework implementation, and real incident analysis — comprehensive coverage.

Supply ChainSBOMSigstoreSLSASecurity

鈴木 健一

ML Platform Engineer

2026-03-16
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AI / AGI15分

Multi-Agent Framework Comparison: CrewAI vs AutoGen vs LangGraph

Three multi-agent frameworks tested on production workloads. Architecture philosophy, implementation patterns, performance, and operational challenges — based on KGA's real project experience.

Multi-AgentCrewAIAutoGenLangGraphAI Agent

中村 悠太

Senior AI Engineer

2026-03-15
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Infrastructure13分

Observability Stack 2025: OpenTelemetry, Grafana, Tempo, Loki

Building a 2025 observability stack from zero. OpenTelemetry instrumentation, Grafana+Tempo+Loki integration, distributed tracing in practice, and cost-efficient operations design.

ObservabilityOpenTelemetryGrafanaDistributed TracingLoki

林 美咲

Frontend Tech Lead

2026-03-15
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AI / AGI14分

AI Voice Synthesis 2025: ElevenLabs, XTTS, Bark & Practical Voice Cloning

Hands-on reviews of ElevenLabs, Coqui XTTS v2, Bark, and StyleTTS2. Quality comparisons, voice cloning implementation, ethical considerations, and real project application examples.

Voice SynthesisTTSElevenLabsXTTSVoice Cloning

金 東勲

Infrastructure Engineer

2026-03-14
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Developer Tools12分

Bun vs Deno vs Node.js: Runtime Comparison 2025

Three JavaScript/TypeScript runtimes tested on production workloads. Startup speed, HTTP throughput, bundle performance, ecosystem maturity, and a migration guide — with real benchmark data.

BunDenoNode.jsJavaScriptRuntime

鈴木 健一

ML Platform Engineer

2026-03-13
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AI / AGI15分

Vector Database Comparison: Pinecone, Qdrant, Weaviate, Milvus, Chroma

Five major vector databases tested on production workloads. Search accuracy, latency, scalability, cost, and operational overhead evaluated with real data — plus a use-case selection guide.

Vector DatabasePineconeQdrantWeaviateRAG

中村 悠太

Senior AI Engineer

2026-03-13
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AI Models13分

Phi-4 & the SLM Revolution: When Small Models Outperform Giants

Microsoft Phi-4 proved that small models can punch above their weight. Domains where 14B outperforms 70B, edge deployment in practice, and realistic design patterns for mobile AI.

Phi-4SLMEdge AIMobile AIModel Optimization

中村 悠太

Senior AI Engineer

2026-03-12
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Infrastructure11分

Cloudflare AI Gateway: Build AI App Infrastructure in 10 Minutes

A setup guide for AI application infrastructure using Cloudflare AI Gateway. Rate limiting, caching, analytics, and provider fallback — all configured in 10 minutes.

CloudflareAI GatewayRate LimitingCachingObservability

林 美咲

Frontend Tech Lead

2026-03-11
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AI / AGI14分

OpenAI Realtime API: Building Real-Time Voice AI

Design and implementation of real-time voice AI applications using the OpenAI Realtime API. WebSocket connections, voice mode, Function Calling integration, and latency optimization.

OpenAIRealtime APIWebSocketVoice AIFunction Calling

金 東勲

Infrastructure Engineer

2026-03-11
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Infrastructure12分

AWS Bedrock in Production: Design and Operations Reality

Practical know-how for deploying AWS Bedrock in production. Architecture decisions, model selection, Guardrails configuration, RAG via Knowledge Bases, and cost optimization.

AWSBedrockRAGGuardrailsKnowledge Bases

鈴木 健一

ML Platform Engineer

2026-03-10
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Infrastructure13分

GraphQL Federation v2: The Definitive Microservices API Integration

Design and implementation of microservice API integration with Apollo Federation v2. Subgraph design, supergraph composition, schema merging, and a phased migration strategy from REST.

GraphQLApollo FederationMicroservicesAPI GatewaySchema

中村 悠太

Senior AI Engineer

2026-03-09
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AI / AGI14分

AI Safety & Alignment: A Practitioner's Perspective

AI safety treated as an engineering problem, not an academic one. Guardrail implementation, content filtering, Red Teaming techniques, and the real cost of over-cautious AI systems.

AI SafetyAlignmentGuardrailsRed TeamingContent Filtering

林 美咲

Frontend Tech Lead

2026-03-09
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Developer Tools15分

Rust for Backend Developers: A Practical Introduction

A hands-on guide for Go/Node.js engineers considering Rust. Actix-web vs Axum comparison, async runtimes, and a practitioner's approach to understanding the ownership model.

RustActix-webAxumBackendMemory Safety

金 東勲

Infrastructure Engineer

2026-03-08
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AI / AGI13分

MLOps Pipeline Architecture: From Model Development to Production

End-to-end MLOps pipeline design. MLflow experiment tracking, Feature Store, model registry, production deployment strategy, and drift detection — KGA's full operational playbook.

MLOpsMLflowFeature StoreModel RegistryDrift Detection

鈴木 健一

ML Platform Engineer

2026-03-07
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Quantum11分

Google Willow Quantum Chip: Breakthrough in Quantum Error Correction

Google's Willow quantum chip and what it achieved in quantum error correction. The significance of 105 qubits, random circuit sampling results, and the path to practical quantum computing.

Google WillowQuantum ComputingError CorrectionQubit

中村 悠太

Senior AI Engineer

2026-03-07
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Developer Tools10分

OpenRouter: Accelerating Development with Unified AI API

A practical guide to multi-model AI development with OpenRouter. Unified API, model routing, fallback strategies, and cross-provider cost comparison and optimization.

OpenRouterUnified APIModel RoutingCost OptimizationAI API

林 美咲

Frontend Tech Lead

2026-03-06
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Security12分

Incident Response Automation: From PagerDuty to Slack Bots

Automating incident response end to end. PagerDuty and Slack Bot integration, automated runbook execution, auto-remediation, and building a blameless postmortem culture.

Incident ResponsePagerDutyAutomationRunbookPostmortem

金 東勲

Infrastructure Engineer

2026-03-05
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AI / AGI12分

Embedding Models Comparison 2025: OpenAI, Cohere, BGE, Jina

A practitioner's comparison of major 2025 embedding models. OpenAI text-embedding-3, Cohere embed-v3, BGE-M3, and Jina Embeddings v3 — multilingual performance, cost, and retrieval quality.

EmbeddingRAGVector SearchMultilingualBenchmark

鈴木 健一

ML Platform Engineer

2026-03-05
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Developer Tools11分

Building a Design System with Tailwind CSS v4

A design system construction guide using Tailwind CSS v4. CSS-first configuration, design tokens, component library patterns, and a migration strategy from v3.

Tailwind CSSDesign SystemCSSDesign TokensComponent Library

中村 悠太

Senior AI Engineer

2026-03-04
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Infrastructure13分

API Rate Limiting Strategies: Token Bucket, Sliding Window & Distributed Implementation

Comparison of major API rate limiting algorithms — Token Bucket, Sliding Window Log, Sliding Window Counter — with Redis-based distributed implementation patterns.

Rate LimitingRedisAPI DesignDistributed SystemsToken Bucket

林 美咲

Frontend Tech Lead

2026-03-03
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AI / AGI13分

Training AI with Synthetic Data: Methods and Limitations

Major synthetic data generation approaches — LLM generation, GANs, simulation — plus quality evaluation metrics, privacy-preserving applications, and a frank look at model collapse.

Synthetic DataData AugmentationAI TrainingData QualityPrivacy

金 東勲

Infrastructure Engineer

2026-03-03
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Infrastructure14分

Platform Engineering 2025: Designing Developer Experience

Platform engineering in practice. Internal Developer Platform (IDP) design, Golden Paths, self-service enablement, Backstage adoption, and making developer experience measurable.

Platform EngineeringIDPDeveloper ExperienceBackstageGolden Path

鈴木 健一

ML Platform Engineer

2026-03-02
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