Ten pillar guides covering every major AI API error surface — from Anthropic Claude and OpenAI to Google Gemini, cloud platforms, agent frameworks, and the Model Context Protocol. Written for engineers building production AI applications.
Pillar guides are our reference layer — deep, evergreen documents that cover an entire provider or protocol end-to-end. Each guide runs 12,000 to 16,000 words and links out to the specific error-fix pages that answer narrower questions. Think of a pillar as the map; the error pages are the destinations.
We're publishing one pillar per month through mid-2027. Guides marked Coming soon are on the roadmap; guides marked Building next are actively in progress. Every published guide comes with a newsletter announcement and updated internal linking from every anchored error page.
If you need a specific fix rather than the full reference, jump straight to the provider error pages at the bottom of this page — 270+ error-specific walkthroughs organized by API surface.
Foundation model APIs from the labs building the frontier models. Each guide covers every error category, migration path, cost optimization, and production checklist for the provider.
Every Claude API error explained — from Opus 4.7/4.8 breaking changes and the five-level effort ladder to MCP connector setup, prompt caching thresholds, and Managed Agents migration. Anchors 105 error-fix pages across core errors and two deepening series.
The definitive OpenAI API troubleshooting reference: Chat Completions vs Responses API, Assistants v2 migration, GPT-5 family routing, Batch API workflows, function calling, structured outputs, and cost optimization. Anchors 60 error-fix pages.
Gemini 2.5 and 3.x API reference: model IDs, thinking config, Live API for bidirectional streaming, code_execution and google_search grounding, long-context 2M-token workflows, and safety settings. Anchors 25 error-fix pages.
Provider-managed cloud deployments of foundation models. Different auth, different regional availability, different feature parity than direct APIs.
Bedrock-hosted Claude, Llama, Titan, and Mistral models: IAM policies, cross-region inference profiles, provisioned throughput, Converse API vs InvokeModel, guardrails, and knowledge bases. Anchors Bedrock error-fix pages.
Azure-hosted OpenAI deployments: resource creation, model deployment names vs model IDs, content filters, PTU vs pay-as-you-go, Entra ID auth, and On Your Data. Anchors Azure error-fix pages.
Higher-level libraries for building LLM applications: chains, agents, RAG pipelines, and stateful graphs. Each layer adds its own error surface on top of the underlying LLM.
LangChain v0.3 patterns: LCEL chains, tool calling, structured outputs, streaming, callbacks, LangSmith tracing, memory, and multi-provider routing. Migration from legacy chains to LCEL. Anchors LangChain error-fix pages.
LangGraph stateful agents: StateGraph construction, nodes and edges, human-in-the-loop interrupts, subgraphs, persistence, streaming events, and the LangGraph Platform deployment. Anchors 15 error-fix pages.
LlamaIndex RAG pipelines: document loaders, node parsers, embedding models, vector stores, query engines, agents, workflows, and LlamaCloud services. Anchors LlamaIndex error-fix pages.
Cross-provider protocols and specifications that any LLM app touches. Understanding these is what separates fluent AI engineers from prompt-and-pray developers.
The Model Context Protocol from spec to production: STDIO/SSE/Streamable HTTP transports, OAuth flows, tool schema validation, resources, prompts, sampling, roots, and integration with Claude Desktop, Cursor, Continue, and Zed. Anchors 15 future error-fix pages.
Guides that span every provider. Cost, latency, reliability — the concerns that don't care which model you called.
The definitive cost playbook for production AI applications: prompt caching economics across providers, batch API discounts, model routing by task complexity, effort tuning, tokenizer inflation, monitoring and alerting, and 40-item cost audit checklist. Cross-vertical, cites all 270 error pages.
Every pillar guide across every category, in build order. Bookmark this page — we ship one guide per month through mid-2027.
| # | Guide | Provider | Pages | Status |
|---|---|---|---|---|
| #01 | The Complete Guide to Claude API Errors in 2026/guides/claude-api-errors-complete-guide-2026/ |
Anthropic Claude | 105 | Coming soon |
| #02 | The Complete Guide to OpenAI API Errors in 2026/guides/openai-api-errors-complete-guide-2026/ |
OpenAI | 60 | Coming soon |
| #03 | The Complete Guide to Google Gemini API Errors in 2026/guides/gemini-api-errors-complete-guide-2026/ |
Google Gemini | 25 | Coming soon |
| #04 | The Complete Guide to Amazon Bedrock Errors in 2026/guides/amazon-bedrock-errors-complete-guide-2026/ |
Amazon Bedrock | 15 | Coming soon |
| #05 | The Complete Guide to Azure OpenAI Errors in 2026/guides/azure-openai-errors-complete-guide-2026/ |
Azure OpenAI | 15 | Coming soon |
| #06 | The Complete Guide to LangChain Errors in 2026/guides/langchain-errors-complete-guide-2026/ |
LangChain | 15 | Coming soon |
| #07 | The Complete Guide to LangGraph Errors in 2026/guides/langgraph-errors-complete-guide-2026/ |
LangGraph | 15 | Coming soon |
| #08 | The Complete Guide to LlamaIndex Errors in 2026/guides/llamaindex-errors-complete-guide-2026/ |
LlamaIndex | 15 | Coming soon |
| #09 | The Complete Guide to MCP Protocol Errors in 2026/guides/mcp-protocol-errors-complete-guide-2026/ |
Model Context Protocol | 15 | Coming soon |
| #10 | AI API Cost Optimization: The Complete Playbook (2026)/guides/ai-api-cost-optimization-playbook-2026/ |
Cross-provider | 270 | Coming soon |
Our guides are the pillar reference. For narrower fixes to specific error messages, we maintain 270+ error-fix pages organized by provider. Each page walks through the exact error, root causes with frequency data, and 3 tested fixes with code.