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Andreas Siebert IT Consulting
- Cologne, Germany
- http://siebert-it.consulting
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an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
A high-level terminal interface library for node.js.
🌈 React for interactive command-line apps
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
Copy your code and errors in LLM friendly formats, right from inside your favorite IDE
Development environments for coding agents. Enable multiple agents to work safely and independently with your preferred stack.
🛍️ Typescript E-commerce Platform
UI kit to make beautiful, animated interfaces, faster. Customizable. Open Source.
Jotai integration library for TanStack Query
AI agent for building React Native apps
The open source Solver AI for Java and Kotlin to optimize scheduling and routing. Solve the vehicle routing problem, employee rostering, task assignment, maintenance scheduling and other planning p…
Publication-ready NN-architecture schematics.
🌟 JavaScript Style Guide, with linter & automatic code fixer
This bot is impossible to beat at 5x5 tic tac toe (I believe)
📚 Freely available programming books
freeCodeCamp.org's open-source codebase and curriculum. Learn math, programming, and computer science for free.
List of books, blogs, newsletters and people!
Tips and resources to prepare for Behavioral interviews.
All the resources you need to get to Senior Engineer and beyond
Publicly shared solutions to Coding Challenges
Curated coding interview preparation materials for busy software engineers
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
If you want to become good at AI engineering & system design, join this newsletter 👇
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Dependency-Track is an intelligent Component Analysis platform that allows organizations to identify and reduce risk in the software supply chain.
OCR & Document Extraction using vision models
Code for the EMNLP 2024 paper "Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps"