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AI Design-to-Code: How UI/UX Teams Ship Faster

on September 20, 2026

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Self-Host n8n with Local Ollama: Zero-Cost AI Workflows (2026)

Self-Host n8n with Local Ollama: Zero-Cost AI Workflows (2026) I've been running n8n + Ollama locally for a few months. No OpenAI bill. No data leaving my network. The setup takes under 20 minutes — except for the Docker networking part, which cost me an hour the first time. This post skips the fluff. Table of Contents What n8n and Ollama Do Hardware Checklist Install Ollama and Pull a Model Run n8n with Docker Compose Connect n8n to Ollama Fix Docker Networking 5 Workflows Worth Building Troubleshooting Table Local vs Cloud FAQ What n8n and Ollama Do n8n is a self-hostable workflow automation tool — Zapier, but you own the server. It connects triggers, logic, APIs, databases, and AI models via a visual node editor. Refer to the n8n Docs for official workflow node definitions. Ollama is a local LLM runtime. It downloads model weights, loads them into memory, and exposes a REST API on port 11434. Any app that makes ...

Claude Code CLI Setup: Terminal AI Agents vs. Cursor

Beyond Cursor: Building a Terminal-First AI Dev Environment with Claude Code CLI Published on Neural Craft — AI Engineering in Practice

Open-Weight Reasoning Models vs. Proprietary APIs: Cost, Latency & Privacy Benchmark

Open-Weight Reasoning Models vs. Proprietary APIs: Cost, Latency & Privacy Benchmark Choosing between open-weight reasoning models and proprietary APIs comes down to four variables: cost per successful task, latency under load, VRAM footprint, and data boundary controls. Here's the full benchmark with real 2026 pricing and hardware numbers. Open-Weight vs. Proprietary AI: What Are You Actually Comparing? What Is an Open-Weight Reasoning Model? An open-weight model makes its trained parameters publicly downloadable under a permissive license. DeepSeek-R1 (MIT) and Meta's Llama 4 (Llama Community License) are the current production references. You can run inference on your own hardware, fine-tune on private data, and deploy without per-token billing. DeepSeek-R1 is a 671B-parameter Mixture-of-Experts model with only 37B parameters active per forward pass — MoE gives you 671B-scale quality at 37B-scale compute cost per token. What Is a Proprietary AI API? A closed-sourc...

AI Design-to-Code: How UI/UX Teams Ship Faster

TL;DR: AI design-to-code turns a structured design file into working, framework-specific component code, matching spacing, tokens, and states instead of guessing from a screenshot. Designers ship cleaner files, developers skip repetitive markup, and the handoff gap between the two shrinks to a review step. Why the Handoff Still Breaks The classic handoff problem hasn't changed in a decade: a designer finishes a screen in Figma, a developer opens it, and half the session goes to questions that shouldn't need asking. What's the spacing token here? Is this button component reused elsewhere? What happens on a 320px screen? Screenshot-based AI tools made this worse before they made it better — feed a model a picture and it invents plausible-looking code that ignores your actual design system, hardcodes colors, and duplicates a button that already exists three files over. What's changed is that the good tools now read the design file directly — layers, auto-layout ...

Agentic Coding 2026: The Full Developer Workflow

Agentic Coding 2026 Developer Workflow Agentic coding is a workflow where you hand an AI agent a spec instead of writing code line by line. The agent plans the change, edits files, runs tests, fixes failures, and opens a pull request. You review the diff and the reasoning, not every keystroke. What Changed For years, AI in the editor meant autocomplete. You typed, it guessed the next few tokens, you accepted or ignored it. You stayed in control of every line, and the AI reacted to you. Agentic coding flips that. You describe an outcome, "add rate limiting to the checkout endpoint, return a 429 with a Retry-After header, cover it with tests" and the agent reads the relevant files, decides what to touch, writes the code, runs the suite, reads the failures, fixes them, and stops when the goal is met or it needs your input. Youtube: Connect Vercel v0 to Supabase in Next.js 15 The job doesn't disappear. It moves up a level. You spend less time typing implementation d...

How to Connect Vercel v0 to Supabase in Next.js 15

Connect Supabase through v0's built-in integration, drop in your environment variables, create separate browser and server clients with @supabase/ssr , and enable Row Level Security before you touch a single query, that's the whole job in one sentence. Everything below is the version of this that actually works when your v0 preview looks fine but your production deploy quietly breaks. Most tutorials on this topic were written before Supabase renamed its public API key and before v0 turned into a genuine full-stack app builder instead of a UI generator. That gap causes real bugs: people copy NEXT_PUBLIC_SUPABASE_ANON_KEY snippets from 2023, wire up a single global Supabase client, skip RLS, and then can't figure out why auth breaks the moment they push to Vercel. The Fastest Route If you don't want to read the whole thing: Connect the Supabase integration inside your v0 project. Let v0 pull in the environment variables automatically. Prompt v0 to build the schem...

Top Open-Source Cursor Alternatives for CLI

Top Open-Source Cursor Alternatives for CLI and Terminal-Based AI Coding Twenty dollars a month is nothing until you're paying it for a VS Code fork you use for 30% of its surface area. If your workflow lives in tmux and a shell you've spent a decade customizing, Cursor asks you to relocate into its editor just to get agentic edits. That's the real cost — not the subscription, the tax on your muscle memory. The tools below skip that tax. Quick Answer: Best Open-Source Cursor Alternatives for CLI Tool Interface License Model Freedom Local LLM Support Primary Use Case Aider Pure CLI / chat REPL Apache 2.0 Full BYOK, any provider Yes, via Ollama Git-native multi-file editing, minimal context overhead OpenCode Terminal TUI (Bubble Tea) MIT 75+ providers, BYOK ...