From User Input to Provider API: The Five-Stage Message Flow
From User Input to Provider API: The Five-Stage Message Flow — companion deep-dive for the NeuroLink blog with architectural detail and code examples.
Seventeen file processors, six categories, one priority system
Seventeen file processors, six categories, one priority system — companion deep-dive for the NeuroLink blog with architectural detail and code examples.
Four-stage context compaction: what runs when the model window fills up
Four-stage context compaction: what runs when the model window fills up — companion deep-dive for the NeuroLink blog with architectural detail and code examples.
What You Actually Inherit When You Extend BaseProvider
What You Actually Inherit When You Extend BaseProvider — companion deep-dive for the NeuroLink blog with architectural detail and code examples.
Ten ESLint rules that hold NeuroLink's type system together
Ten ESLint rules that hold NeuroLink's type system together — companion deep-dive for the NeuroLink blog with architectural detail and code examples.
Four MCP transports: stdio, http, sse, websocket — picking the right one
Four MCP transports: stdio, http, sse, websocket — picking the right one — companion deep-dive for the NeuroLink blog with architectural detail and code examples.
How We Test NeuroLink: 20 Continuous Test Suites and Counting
Inside NeuroLink's testing strategy -- 20 continuous test suites covering providers, MCP, RAG, streaming, memory, middleware, observability, video generation, and more, all running on every commit with a custom tsx runner.
GitHub Actions for AI: Automating NeuroLink in Your CI/CD Pipeline
Ship the NeuroLink GitHub Action into your CI/CD pipeline for automated AI model testing, provider validation, response evaluation, and deployment gating with real LLM calls in your pull request workflow.
Conversation Summarization: Smart Context Management for Long Chats
Keep conversations going indefinitely with NeuroLink's summarization patterns — LLM-powered condensation, sliding window plus summary hybrids, token budget strategies, and the four-stage context compaction pipeline.
Dynamic Model Selection: Routing AI Requests at Runtime
Route AI requests to the optimal model at runtime based on task complexity, cost budgets, latency requirements, and provider availability using NeuroLink's dynamic model selection system.