All Posts

Set up LangSmith automated regression testing in GitHub Actions. Catch LLM output regressions before they ship with eval datasets and pass/fail gates.

Tag LangSmith traces by feature, query token costs with the SDK, and build a spend-by-feature dashboard. Stop billing surprises before they hit.

Create, version, and run evals against LangSmith datasets. Build reliable LLM benchmarks that catch regressions before they reach production.

Set up automated LLM quality testing with LangSmith evaluations. Define datasets, run evaluators, and catch regressions before they hit production.

Learn how to push, pull, and version prompt templates using LangSmith Hub. Share prompts across teams and reuse them in LangChain pipelines.

Configure LangSmith for multi-tenant apps by isolating projects, rotating API keys per tenant, and preventing trace data leakage between clients.

Use LangSmith Playground to test, compare, and improve prompts visually — no Python needed. Faster iteration for LLM apps in 2026.

Set up LangSmith alerts and dashboards for LLM apps in production. Monitor latency, cost, errors, and token usage with real working config.

Manage, version, and deploy LangSmith prompt templates across teams. Learn to create, pull, and iterate prompts with full version control. 155 chars

Deploy LangSmith on your own server with Docker Compose. Full setup for tracing, evaluation, and LLM observability on private infrastructure.

Set up LangSmith tracing in your LangChain app in minutes. Debug prompts, track token costs, and monitor agent runs in production.

Set up LangSmith tracing to debug slow, hallucinating, or failing LLM chains. Pinpoint latency, token costs, and errors in minutes.

LangSmith vs Langfuse vs Helicone compared on tracing, evals, self-hosting, and pricing. Pick the right LLM observability tool for your stack.

Set up LangSmith tracing for LangGraph multi-agent workflows. Debug node execution, inspect tool calls, and monitor agent state in production. · 152 chars

Connect Model Context Protocol servers to Cursor and Windsurf IDEs. Configure MCP tools, debug connections, and boost AI coding workflows in 20 min.

Build an n8n AI Agent that calls GPT-4 and connects to any REST API. Step-by-step setup with tool nodes, memory, and error handling.

Connect n8n to Airtable and automate database sync workflows. Covers credentials, triggers, CRUD operations, and error handling in 2026.

n8n Cloud vs self-hosted compared on cost, control, setup time, and team size. Pick the right deployment for your workflow automation stack.

Use n8n's Code node to write custom JS and Python logic inside workflows. Transform data, call APIs, parse responses, and handle edge cases.

Set up n8n cron triggers for scheduled workflows. Covers cron syntax, timezone config, error handling, and production patterns for self-hosted n8n.

Set up n8n email automation with Gmail OAuth2 and SMTP. Send triggered emails, build notification workflows, and handle errors in production.

Connect n8n to GitHub to automate PR reviews, issue triage, and Slack notifications. Step-by-step setup with real workflow JSON. Saves 2+ hours/week.

Connect Google Sheets to any app with n8n. Read, write, and sync rows automatically using triggers, HTTP nodes, and real workflow examples.

Learn to use the n8n HTTP Request node to call REST APIs, handle auth, pagination, and errors. Works with any API in your workflow.

Connect n8n to LangChain and build RAG pipelines without writing boilerplate. Ingest docs, embed, retrieve, and generate — all from n8n's canvas.

Connect n8n to Notion and process notes automatically with AI. Auto-summarize, tag, and route pages using Claude or GPT-4o in under 30 minutes.

Build a DALL-E image generation pipeline in n8n using the OpenAI node. Automate prompt intake, image creation, and file storage in under 20 minutes.

Connect n8n to PostgreSQL, run queries, insert rows, and trigger workflows from database events. Full setup guide with real examples.

Stop API throttle errors in n8n. Configure rate limiting with Wait nodes, batch splitting, and retry logic to keep workflows running reliably.

Use the n8n REST API to trigger workflows via webhook and API calls. Covers auth, payloads, error handling, and real Python/Node examples.

Build an n8n RSS feed reader that monitors sources, filters posts, and auto-publishes to WordPress, Ghost, or a webhook — no manual copy-paste.

Build a Slack AI assistant in n8n using GPT-4o or Claude. No code required — trigger on messages, respond with AI, deploy in 20 minutes.

Connect n8n to Supabase with the Supabase node, set up real-time database triggers, and automate workflows on INSERT, UPDATE, and DELETE events.

Build a Telegram AI chatbot in n8n using the Telegram trigger, OpenAI node, and memory buffer. No code required — live in under 30 minutes.

n8n vs Flowise compared on self-hosting, LLM integration, custom code, and pricing. Pick the right AI automation tool for your stack in 2026.

n8n vs Zapier vs Make compared on pricing, self-hosting, AI integration, and developer control. Pick the right automation tool for your stack.

Connect n8n to the OpenAI API to automate blog posts, product descriptions, and social copy at scale. Step-by-step workflow setup with error handling.

Add semantic search to PostgreSQL with pgvector. Store embeddings, run similarity queries, and build RAG pipelines — no extra infra needed.

Qwen 2.5-Coder vs DeepSeek Coder compared on HumanEval, SWE-bench, speed, and local deployment. Pick the right coding model for your stack.

Set up DeepSeek R1-Distill-Qwen-7B on a 6–8GB consumer GPU using Ollama. Covers install, quantization, GPU config, and benchmarks.

Deploy TensorFlow Lite and ONNX models on Raspberry Pi 5 for real-time edge inference. No cloud, no latency, no API costs — just local AI.

Run LLM inference with Rust Candle and beat Python PyTorch by 3x. Step-by-step guide: setup, quantization, CUDA, and production benchmarks.

Provision GPU instances for AI workloads with Terraform, auto-scale on inference demand, and enforce budget limits to prevent runaway cloud bills.

Windsurf vs Cursor compared on AI models, agent mode, autocomplete, pricing, and real dev workflows. Pick the right AI IDE for your stack in 2026.

Build a working RAG chatbot in Flowise without writing code. Connect a vector store, embed documents, and deploy a Q&A bot in under 30 minutes.

Compare Flowise and LangFlow for building LLM apps without code. Covers setup, features, performance, and when to pick each in 2026.

Compare spaCy, HuggingFace Transformers, and LLM-based NER for production: real accuracy scores, latency benchmarks, and when to use each.

Build a multi-agent CrewAI workflow where a Researcher agent gathers information, a Critic agent validates accuracy, and a Writer agent produces the final output — with real task delegation and output passing.

How to build production ML pipelines that don't leak data between train and test — correct sklearn Pipeline construction, ColumnTransformer for mixed types, proper cross-validation, and serving the final pipeline as a FastAPI endpoint.

Use Anthropic's Model Context Protocol (MCP) to connect Claude agents to GitHub, PostgreSQL, and Slack — setting up MCP servers, tool discovery, authentication, and building an agent that can actually do work.