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The n4n AI blog
Guides, comparisons and deep dives on LLM routing, pricing, agents and the models behind them.
7 techniques to shrink token usage in agent loops
Practical, code-level ways to shrink token usage in agent loops — schema trimming, summarization, output pruning, caching, and model tiering.
Adding an LLM chat feature to a Django app
A step-by-step tutorial for wiring a streaming LLM chat feature into a Django app, from the model and view through htmx streaming and error handling.
AI guardrails explained: keeping LLMs safe and on-topic
What are AI guardrails? A practical breakdown of input/output filtering, system prompts, and moderation layers that keep LLM apps safe, on-topic, and on-brand.
Automatic fallback when GPT-5 hits capacity limits
When GPT-5 rate limits or capacity errors hit production traffic, here's how automatic fallback works — and how to build it into your stack today.
Best LLM for Python debugging: GPT-5 vs Claude Opus 4.8
GPT-5 and Claude Opus 4.8 both write clean Python, but debugging demands a different skill. We compare traceback reasoning, tool use, and cost.
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