n8n Form Trigger + AI Agent: Build a Smart Intake Form
A contact form that sits in an inbox helps nobody. Wire n8n's Form Trigger to an AI agent and every submission gets classified, answered, and routed the moment it arrives.
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118 tested guides on AI agents, n8n, RAG, and automation — newest first.
Build an AI Research Assistant in n8n: Search, Read, Cite
You want a short answer with real, clickable links, not a confident paragraph the model invented. This is how to build an ai research assistant in n8n: capture a question, search the web, fetch and clean the top pages, and summarize with citations grounded only in that fetched
Query Rewriting for RAG: Fix Retrieval at the Query Side
You tuned chunking, added a reranker, and swapped embeddings, but RAG still misses on short or conversational questions. The reason is often the query itself. Here is how query rewriting, multi-query, HyDE, and expansion fix retrieval at the query side, and how to measure
n8n Webhooks vs Polling: Which Trigger to Use, and Why
Should an n8n workflow fire the instant an event happens (a webhook, push) or check on a timer (polling, pull)? The wrong pick means missed events or wasted executions. Here is the decision framework plus how to wire each trigger.
Writing AI Agent Tool Descriptions the Model Actually Uses
Your agent keeps calling the wrong tool or passing bad arguments, and you blame the model. The real lever is the tool description and its JSON schema: the model picks and fills every tool from that alone. Here is how to write ai agent tool descriptions like onboarding docs for a
The 2026 Model Wave: What It Changes for Automation Builders
Three model releases landed in two weeks in June 2026: Fable 5, open-weight GLM-5.2, and limited-preview GPT-5.6. Skip the leaderboard drama. Here is the builder's take on which model belongs on which workflow step, with every price and benchmark dated and attributed.
Fable 5 vs GLM 5.2 vs GPT-5.6: The 2026 Frontier Landscape
Three frontier models landed in June 2026: Claude Fable 5, Z.ai's open-weight GLM-5.2, and OpenAI's limited-preview GPT-5.6. The numbers do not all measure the same thing, so here is an honest, dated comparison on coding score, price, and openness.
GPT-5.6 Explained: Sol, Terra, Luna, and a Limited Launch
OpenAI previewed GPT-5.6 on June 26, 2026 in three tiers, Luna, Terra, and Sol, with public per-token prices. The twist is access: launch was limited to roughly 20 partners at the behest of the U.S. government, with general availability promised in the coming weeks. Here is the
GLM-5.2: Open-Weight Frontier Coding at a Fraction of the Cost
Z.ai's GLM-5.2 ships open weights under MIT and reportedly leads the open-weight field on SWE-bench Pro while trading blows with Opus 4.8 on FrontierSWE and MCP-Atlas, at roughly one-sixth of GPT-5.5's blended cost. The catch is a hosted-API data-residency caveat.
Claude Fable 5: Anthropic's Mythos-Class Model, Explained
Anthropic's Claude Fable 5 shipped on June 9, 2026 topping the coding benchmarks it publishes and priced near twice Opus 4.8. Here is an honest read on the reported numbers, the real trade-off, and who should pay the premium.
AI Content Repurposing in n8n: One Post into a Week of Social
You spent hours on one post and it went out once. An n8n workflow reshapes that single source into platform-native LinkedIn, X, and Instagram drafts with an LLM and structured output, then routes them to a human review store. Here is the honest build.
HNSW vs IVFFlat: Choosing and Tuning Your pgvector Index
In pgvector you choose an index type, and the two real options are HNSW and IVFFlat. With no index, queries do exact search on every row: accurate but slow at scale. Here is the trade-off between the two approximate indexes and how to tune each one.