Atul Acharya laventura

April 2026 TLDR setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon) — auto-start, preload, and keep-alive

April 2026 TLDR Setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon)

Prerequisites

Mac mini with Apple Silicon (M1/M2/M3/M4/M5)
At least 16GB unified memory for Gemma 4 (default 8B)
macOS with Homebrew installed

Terminals should generate the 256-color palette from the user's base16 theme.

If you've spent much time in the terminal, you've probably set a custom base16 theme. They work well. You define a handful of colors in one place and all your programs use them.

The drawback is that 16 colors is limiting. Complex and color-heavy programs struggle with such a small palette.

Feld Claude Code Configuration Guide

A comprehensive tour of a professional solo-developer Claude Code setup spanning twelve repositories and twelve worktrees. Covers workflow discipline, session persistence, automated quality gates, business operations, and EOS management.

Last updated: 2026-04-29

What this is: a tour of a working setup and the reasoning behind it — useful for borrowing patterns. What this is NOT: an install guide, a list of best practices, or a snapshot that stays accurate without updates. Plugin versions, pg_cron schedules, and file counts are point-in-time.

I Built an Enterprise AI Avatar Platform. Looking for Partners/Customers in India, UAE, Turkey.

18-month journey building a Soul Machines competitor. Now focusing on viable markets outside the West.

Test the Demo

Book a 15-minute live demo: [Speak with HAVVA]

Modern R Development Guide

This document captures current best practices for R development, emphasizing modern tidyverse patterns, performance, and style. Last updated: August 2025

Core Principles

Use modern tidyverse patterns - Prioritize dplyr 1.1+ features, native pipe, and current APIs
Profile before optimizing - Use profvis and bench to identify real bottlenecks
Write readable code first - Optimize only when necessary and after profiling
Follow tidyverse style guide - Consistent naming, spacing, and structure

Let's hack on `llm`!

If you have uv installed (and you should!), you can install llm globally in a uv-managed tool environment with:

uv tool install llm

If you want to use models other than OpenAI models, you'll need some extensions:

Vibe Building a Client‑Side PDF Compressor with Ghostscript‑WASM

Hosted at: https://austegard.com/pdf-compressor.html

Modern browsers are incredibly powerful. If you’ve ever tried Squoosh.app’s client‑side image compression, you know just how slick a fully‑in‑browser workflow can feel. What if we extended that idea to PDFs—shrinking large documents without ever sending them to a server?

In this post I’ll walk through how we built PDF Compressor, a 100% client‑side PDF optimizer written in pure HTML/JS/WebAssembly. We started with a Claude 3.7 Sonnet–generated plan, iterated with ChatGPT o4‑mini‑high, and ended up with a reasonabvly‑fast, vector‑preserving compressor powered by Ghostscript‑WASM.

This guide is adapted from this original post by Christopher Charles.

Project Setup

1. Get the source:

Clone the MLX Swift Examples GitHub repository:

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp