One of the core problems in LLM-driven software development is not that models are simply "bad at coding." It is that they are often extremely strong at local optimization inside the current task frame, while being much weaker at preserving system intent, architectural boundaries, and domain-level coherence.
This creates a very specific failure mode.
An LLM can often:
I've been using a GPU workstation with an RTX 4090 for almost a year now, and it's been one of the best decisions I've made. With a personal GPU server, you no longer need to rely on cloud-based GPU instances from services like RunPod or Vast.ai every time you want to run a job or try new models. The best part? No stress about recurring GPU instance costs! :-)
However, I rarely work directly on my workstation. Instead, I prefer the flexibility of accessing the GPU remotely using my MacBook, whether I'm working from different locations within my home, from a co-working space, or a cozy cafe in another part of town.
In this blog, I will walk you through the steps to configure a personal GPU Ubuntu server.
For this guide, I assume you already have a workstation running Ubuntu with a GPU and it is connected to your local network
| interval = Date.new(2020, 5, 1)..Date.new(2020, 6, 7) | |
| module FixStuckShipments | |
| FINAL_STATES = %w[ | |
| shipped | |
| canceled | |
| ].freeze | |
| SHIPMENT_STATUS_MAP = { | |
| 'Complete' => 'shipped', |
| # Get Status | |
| get_status = -> (po_number) do | |
| r = Supplier::Alphabroder::OrderStatusV2::GetOrderStatus.new.call(po_number) | |
| doc = Nokogiri::XML(r.body) | |
| nodes = doc.xpath("//order[not(shipstatus)]") | |
| pnode = Supplier::Alphabroder::OrderStatusV2::OrderXmlNode.new(nodes) | |
| pnode.ship_method_nodes.map do |n| | |
| { | |
| number: n.shipper_number, |
| # May | |
| interval = Date.new(2020, 5, 1).all_month | |
| stock_location_ids = Spree::Supplier.alphabroder.stock_location_ids | |
| order_ids = Spree::Order.joins(:shipments).where( | |
| completed_at: interval, | |
| spree_shipments: { | |
| state: 'processing', | |
| stock_location_id: stock_location_ids | |
| } |
| brand_and_catalog_numbers = { | |
| 'Bella + Canvas' => ['BST323', 'BST323C'], | |
| 'Bayside' => ['1900J1'], | |
| 'LAT' => ['J0041', 'J0042'], | |
| 'Rabbit Skins' => ['J0051', 'J0052'], | |
| 'US Blanks' => ['USFM47'], | |
| 'Next Level' => ['NLM100', 'NLM101'] | |
| } | |
| brand_and_catalog_numbers.each do |brand_name, catalog_numbers| |
| shipping_rules = [ | |
| { | |
| brand_name: 'Bella + Canvas', | |
| free_shipping_threshold: 200, | |
| shipping_fees: { | |
| fastest: 9.95, | |
| standard: 0.00, | |
| economy: 5.45 | |
| }, | |
| discount_coupon_allowed: false, |
There's the pervarsive notion that all JS is created equal and that there's only minor and easily detectable differences between the various file formats used to author JavaScript. This is correct, from a certain point of view.
For many people writing JavaScript that gets passed into build tools,
| Spree Guides | |
| Products | |
| 1. Track uniq products | |
| 2. Option Types -> denote the different options for a variant | |
| 3. Option Values -> values for option types | |
| 4. Product must be assigned at least one option type if you wish to create variants for that product | |
| 5. Variants -> individual variants of a Product | |
| 6. Master Variant -> tracks basic information such as a count on hand, a price and a SKU |
First, add pry-rails to your Gemfile:
https://github.com/rweng/pry-rails
gem 'pry-rails', group: :developmentThen you'll want to rebuild your Docker container to install the gems