How Teams Should Audit Claude Code Usage After the Leak
A practical post-incident audit guide for teams using Claude Code after the March 31 leak, including permissions, MCP servers, telemetry, repo scope, and approval policy checks.
Read articleAI Reliability Blog
Original long-form analysis focused on incident behavior, provider reliability strategy, and production operations for AI APIs.
Publishing cadence: 1-2 original articles per week. The blog now covers 51 original posts spanning provider reliability, migration guidance, incident strategy, quota behavior, deprecations, and production operations.
Latest Articles
What the Claude Code Leak Means for MCP Connector Trust Boundaries
A practical analysis of how the Claude Code leak should change how teams think about MCP connector trust boundaries, project-scoped servers, remote tools, and approval policy.
Read articleClaude Code vs Codex Security Posture After the Leak
A practical security comparison of Claude Code and Codex after the March 31 Claude leak, focused on sandboxing, approvals, MCP exposure, and enterprise trust boundaries.
Read articleWhat Is Axios on npm, and How the Compromise Put Code at Risk
A practical explainer on what Axios is on npm, what happened in the March 31 compromise reports, which versions were flagged, and how a package update can put code and machines at risk.
Read articleClaude Code Source Leak Today: What Happened and Why It Matters
A practical breakdown of the Claude Code source leak reported on March 31, 2026, including the source-map issue, what appears exposed, and why it matters for AI coding tools.
Read articleClaude Code Source-Map Leak: What It Reveals About AI Agent Security
What the reported Claude Code source-map leak says about permission models, release hygiene, and the security posture AI coding agents need in 2026.
Read articleClaude Code Leak: Reported Features and What Builders Should Ignore for Now
A practical look at the hidden Claude Code features people say the leak exposed, what might matter, and what builders should avoid over-reading before Anthropic confirms anything.
Read articleGPT-4o Retired From ChatGPT: What Changes and What Stays
A practical guide to the 2026 GPT-4o retirement in ChatGPT, including what changed for users, what still works in the API, and what teams should do next.
Read articleCustom GPTs After ChatGPT Model Retirements in 2026
A practical guide to how ChatGPT model retirements affect Custom GPTs, workspace admins, and default model behavior in real organizations.
Read articleGPT-5.3-Codex vs Codex-Spark: Which One Fits Real Developer Work?
A practical guide to GPT-5.3-Codex and Codex-Spark, including where each fits and how teams should think about speed versus full agentic depth.
Read articleIs OpenAI Shutting Down Sora? What Is Confirmed vs Reported
A news-style breakdown of the latest Sora shutdown reports, what OpenAI has officially confirmed, and where the line is between reporting and product documentation.
Read articleClaude Desktop Access Gets Serious: What Anthropic Is Actually Building
A practical guide to Claude desktop access now that Anthropic is pushing desktop apps, extensions, local MCP workflows, and Cowork for longer-running tasks.
Read articleWhy OpenAI Stepped Back From Sora Inside ChatGPT
A sharper read on the Sora shift: OpenAI is deprecating the old Sora 1 web experience while centering Sora 2 on the app and sora.com.
Read articleWhat Is MCP? Why Model Context Protocol Matters for Real AI Tools
A practical guide to MCP, including hosts, clients, servers, tools, resources, prompts, and why protocol boundaries matter for real AI workflows.
Read articleWhat Is A2A? Why Agent-to-Agent Protocols Matter Beyond One AI Agent
A builder-focused guide to A2A, remote agents, service boundaries, and why multi-agent systems need stronger contracts than prompt glue.
Read articleWhy Sora Is Becoming Its Own App, Not Just Another GPT Feature
A practical reading of OpenAI’s Sora direction and why a dedicated app makes more product sense than treating video creation like another chat feature.
Read articleClaude’s New Launches: What Actually Matters for Builders
A builder-focused reading of recent Claude launches, including Claude 4, Opus 4.5, Claude Code, Files API, and MCP connectors.
Read articleAnthropic Prompt Caching in 2026: Cost, TTL, and Latency Planning
A March 2026 guide to Anthropic prompt caching, including automatic caching, TTL choice, and how to avoid paying write cost without enough cache reads.
Read articleOpenAI Background Mode in 2026: When To Use It and When Not To
A March 2026 guide to OpenAI background mode, including long-running Responses API jobs, polling tradeoffs, and ZDR implications.
Read articleMistral OCR in 2026: Operational Guide for Document AI Pipelines
A March 2026 guide to Mistral OCR, including markdown output, table extraction options, and how OCR should fit into a production document pipeline.
Read articleOpenAI GPT Image 1 in 2026: Operational Guide for Quality, Cost, and Latency
A March 2026 operational guide to OpenAI GPT Image 1, including quality tiers, token-driven cost, latency, and moderation controls.
Read articleGemini 2.5 Pro Quota Planning in 2026: RPM, TPM, RPD, and Batch Headroom
A March 2026 planning guide for Gemini 2.5 Pro quotas, including current free-tier RPM/TPM/RPD limits and batch headroom.
Read articleOpenAI DALL·E Deprecation in 2026: Migration Guide for Image APIs
A March 2026 guide to OpenAI DALL·E 2 and DALL·E 3 deprecations, the May 12, 2026 shutdown date, and what image workflows should migrate now.
Read articleGemini Batch API in 2026: Rate Limits, Quotas, and Safe Async Design
A March 2026 guide to Gemini Batch API limits, queue planning, and when asynchronous Gemini workloads are safer than standard realtime calls.
Read articleAnthropic Message Batches in 2026: When the 50% Discount Is Worth It
A March 2026 guide to Anthropic Message Batches, queue limits, and when the 50% batch discount is actually operationally worth it.
Read articleOpenAI API Deprecations in 2026: What Production Teams Need To Change
A March 2026 deprecation map covering Responses migration pressure, Realtime beta shutdowns, GPT-4 preview retirement, and Assistants sunset planning.
Read articleOpenAI Responses API in 2026: What Changed for Production Teams
A current guide to the newer OpenAI Responses stack, the Agents-era tooling launched in 2026, and what production teams should change now.
Read articleOpenAI Realtime API Beta Deprecation Guide for March 2026
A current guide to the March 24, 2026 OpenAI realtime beta shutdown and how to migrate audio and realtime traffic cleanly.
Read articleGPT-4 Preview Shutdown in March 2026: What to Migrate Now
A current guide to the March 26, 2026 shutdown of older GPT-4 preview models and how production teams should retire them safely.
Read articleGemini 2.0 Shutdown Before June 1, 2026: Migration Guide
A current guide to Google’s June 1, 2026 Gemini 2.0 shutdown schedule and how to move to the supported 2.5 generation safely.
Read articleAnthropic Long-Context Rate Limits in 2026: Planning Guide
A current planning guide for Anthropic’s long-context requests, token buckets, and what breaks when teams scale context windows without revisiting rate limits.
Read articleOpenAI Responses API Migration Guide for Production Teams
A production-focused guide to migrating from Chat Completions and Assistants-era patterns to the OpenAI Responses API.
Read articleAssistants API Sunset 2026: What AI Teams Should Change Now
A practical planning guide for teams that still rely on Assistants-era patterns and need to move safely before the 2026 sunset.
Read articleAnthropic Rate Limits Explained: Spend Tiers, Token Buckets, and Production Planning
How Anthropic API spend limits and token-bucket rate limits affect real production systems and what teams should plan for.
Read articleGemini API Quotas Explained: Project-Based Limits, Free Tier Traps, and Upgrade Strategy
A production guide to Gemini API quotas, project-based enforcement, free-tier limitations, and safe upgrade planning.
Read articleWhy 429 Spikes Happen Even Below Published Limits
Why teams still hit 429s even when headline quota math looks safe, and what to change in traffic shaping, retries, and routing.
Read articleBatch API vs Realtime AI Workloads: Which Pattern Is Safer, Cheaper, and Easier to Operate?
A production comparison of batch and realtime AI patterns across cost, reliability, incident handling, and operational simplicity.
Read articleWhy We Started AI Checker Hub: The Problem Nobody Was Solving
The founder perspective on why AI Checker Hub was built and what operational gap it aims to solve for AI teams.
Read article3 Months of Data: Which AI Provider Is Actually Most Reliable?
How to interpret 90-day reliability data correctly across providers without oversimplifying to a single winner.
Read articleIs AI API Reliability Getting Worse? Data Analysis 2025-2026
A practical analysis of reliability signals from 2025 to 2026 and what teams should change in response.
Read articleShould You Trust Official Status Pages? Our Take
A balanced view on official provider status pages and how to combine them with independent monitoring for better decisions.
Read articleBuilding Your First AI Failover System: Complete Tutorial
A practical tutorial for implementing your first AI API failover strategy with triggers, routing, and rollback safeguards.
Read article5 Signs Your AI Integration Is About to Break (And How to Fix It)
Early warning signs that predict AI API integration incidents and practical fixes before customer impact escalates.
Read articleThe Complete Guide to AI API Cost Optimization
How to optimize AI API cost without damaging reliability, including routing policy, caching, and incident-aware controls.
Read articleRegional Differences in AI API Performance: What You Need to Know
Why AI API behavior differs by region and how to build routing and alerting policies that account for geographic variance.
Read articleHow We Built an Independent AI API Monitor (Behind the Scenes)
A practical behind-the-scenes look at building AI Checker Hub, from incident pain points to architecture and operational lessons.
Read articleThe Day OpenAI API Went Down: What We Learned
A structured post-incident breakdown of how teams should classify, respond to, and recover from OpenAI API outage patterns.
Read articleOpenAI vs Anthropic vs Google: The Reliability Wars
A practical comparison framework for AI API reliability tradeoffs across providers, regions, latency behavior, and cost risk.
Read articleHow to Choose Your Primary AI Provider (Decision Framework)
A step-by-step framework to choose a primary AI provider using reliability, latency, fallback readiness, and cost controls.
Read articleThe Hidden Costs of AI API Downtime (Real Company Patterns)
Beyond obvious outage minutes: a breakdown of hidden engineering, support, and reputation costs of AI API downtime patterns.
Read articleUnderstanding AI API Latency: What Is Normal and What Is Not
A practical guide to interpreting p50/p95 latency for AI APIs and separating acceptable variance from true degradation.
Read articleCategories
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- How-To
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