{
  "video_id": "reddit_1ugba2x",
  "channel_slug": "LocalLLaMA",
  "channel_handle": "r/LocalLLaMA",
  "title": "What's one local AI workflow you wish you'd discovered sooner?",
  "url": "https://www.reddit.com/r/LocalLLaMA/comments/1ugba2x/whats_one_local_ai_workflow_you_wish_youd/",
  "external_url": null,
  "upload_date": "20260626",
  "published_at": "2026-06-26T16:15:07+00:00",
  "transcript": "There are a lot of posts about the models and benchmarks, but I am more interested in the workflows that people use. What is one workflow that really saved you time or made your local LLM more useful? \n\nIt could be anything—RAG, MCP, coding agents, organizing prompt, document indexing, automation or something else entirely. What was it, and why did it make such a big difference in your day-to-day workflow?\n\n\n\n--- Top Comments ---\n\n\n[45 upvotes] the one that stuck for me is a tiny local eval set.\n\nevery useful prompt/workflow gets 5-10 JSONL cases with `input`, `expected_shape`, and `fail_reason`. before i swap models or quantization, i run those through the local server and diff the outputs.\n\nway less exciting than RAG, but it stops the \"new model feels better\" trap fast.\n\n[29 upvotes] Not a workflow but I wish I'd switched to Qwen sooner. I dropped a bunch of money on [Z.AI](http://Z.AI) coding plan, and now I almost always just use Qwen. I actually like it more.\n\nI use the Heretic 3.6 27B Q4\\_K\\_M quant on latest Llama.cpp with all the mtp optimizations on. Get around 50 tps - the prompt processing is slow, but that's just OpenCode's massive system prompt.\n\nAnd no, I won't change to Pi - I've already spent too much time switching tools and I'm locking myself in for the time being to focus on actual work lol.\n\n[11 upvotes] That running a business with a local model is feasible and gives better/more predictable results than frontier models.\n\n[10 upvotes] i hyper-optimized my workflow to hit /new as often as i can get away with. Qwen quickly becomes overwhelmed with large contexts and at least on an m4 macbook, prefilling is the only slow part of working with it. So i often create an md \"state file\" for my bigger tasks that i can then feed into qwen on each new session and it knows immediately what i'm working on today, what's its current progress and both qwen and i can update the file. This feels much faster than compaction and more reliable since i control it at every step\n\n[9 upvotes] giving a small-to-mid size local model a harness that lets me search whatever files or apps i want to use on my pc, this will be better than the default searches available in the OS",
  "transcript_chars": 2204,
  "ingested_at": "2026-06-27T01:30:28.684280+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 53,
    "upvote_ratio": 0.92,
    "num_comments": 42,
    "author": "recro69",
    "is_self": true
  }
}