---
title: "What We’ve Learned From A Year of Building with LLMs – Applied LLMs"
url: https://daily.dev/posts/what-we-ve-learned-from-a-year-of-building-with-llms-applied-llms-28lm4trow
source_url: https://eugeneyan.com/writing/llm-lessons
type: article
source: "Eugene Yan"
published: 2026-05-31T07:40:22.190Z
updated: 2026-05-31T08:22:00.281Z
tags: ["llm", "ai-agents", "rag", "prompt-engineering"]
reading_time: 71
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# What We’ve Learned From A Year of Building with LLMs – Applied LLMs

**[Eugene Yan](https://daily.dev/sources/eugeneyan)** · 71 min read · 0 upvotes · 0 comments

## Summary

A comprehensive guide from six practitioners covering a year of hands-on experience building LLM-powered products. Covers three layers: tactical (prompting best practices, RAG design, workflow optimization, evaluation strategies), operational (data quality, model versioning, product design, team structure), and strategic (when to build vs. buy, avoiding GPU investment before product-market fit, focusing on the system over the model). Key insights include: use n-shot prompts and chain-of-thought, prefer RAG over finetuning for new knowledge, long-context models won't kill RAG, prioritize deterministic workflows for agents, use LLM-as-Judge carefully with pairwise comparisons, pin model versions in production, and choose the smallest model that gets the job done.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://eugeneyan.com/writing/llm-lessons>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#rag](https://daily.dev/tags/rag), [#prompt-engineering](https://daily.dev/tags/prompt-engineering)

[View this post on daily.dev](https://daily.dev/posts/what-we-ve-learned-from-a-year-of-building-with-llms-applied-llms-28lm4trow)
