Hands-on Demo of Glamorous Toolkit & Moldable Development • Tudor Girba & Kris Jenkins • GOTO 2024
youtube.com·16h
Live Coding
Is it Time to Un-Sass?
css-tricks.com·14h
🎮Language Ergonomics
Obelisk 0.24.1
obeli.sk·20h·
📡Erlang BEAM
The Capability-Tractability Tradeoff (2023)
buttondown.com·5d·
Discuss: Hacker News
Partial Evaluation
Modernizing Legacy E-Commerce Platforms: From Oracle ATG To Cloud-Native Architectures
hackernoon.com·8h
🥾Bootstrapping Strategies
Build AI Agents: YouTube Summarizer Agent
hackernoon.com·22h
Incremental Parsing
Ancient Scripts, Modern AI: Bridging the Divide with Morphology-Aware Tokenization by Arvind Sundararajan
dev.to·4d·
Discuss: DEV
Tokenizer Benchmarks
Introducing ts-base: A Modern TypeScript Library Template
dev.to·8h·
Discuss: DEV
📦Monorepos
An End-to-End Differentiable, Graph Neural Network-Embedded Pore Network Model for Permeability Prediction
arxiv.org·43m
📋JSON Parsing
Perspectives, Needs and Challenges for Sustainable Software Engineering Teams: A FinServ Case Study
arxiv.org·1d
📦Dependency Analysis
Building a CLI for database management in Rust
reddit.com·6h·
Discuss: r/rust
🚂Cranelift Backend
Clean Coding Guidelines Every Developer Should Know
dev.to·13h·
Discuss: DEV
📚Self-Documenting Code
Taylor-Series Expanded Kolmogorov-Arnold Network for Medical Imaging Classification
arxiv.org·43m
🌱Minimal ML
Unlock LLM Superpowers: Zero-Shot Graph Reasoning for Unprecedented Problem Solving
dev.to·5h·
Discuss: DEV
🔗Graph Rewriting
The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences
arxiv.org·2d
💬REPL Design
The Best "Man" Wins: Why the Vibe Coder vs. Engineer Debate is Over
dev.to·17h·
Discuss: DEV
📚Self-Documenting Code
Here’s how far I’ve come after 7 days of grinding on system design.
github.com·1d·
Discuss: DEV
🧱First Principles
Cognitive and Gestalt psychology in your code: SMVP pattern
github.com·3d·
Discuss: Hacker News
📋Backus-Naur Form
Large Language Models for One-Day Vulnerability Detection
dev.to·1d·
Discuss: DEV
🎲Parser Fuzzing
When Inverse Data Outperforms: Exploring the Pitfalls of Mixed Data in Multi-Stage Fine-Tuning
arxiv.org·1d
🪜Recursive Descent