Overview

SMASH is redefining how U.S. companies scale tech teams by connecting them with exceptional talent
from Costa Rica and Colombia. With a people-first, employee leasing model that emphasizes integration over outsourcing, SMASH helps companies quickly and seamlessly fill hard-to-hire roles with long-term team members — not contractors.

Challenge

Many U.S. companies face a critical shortage of qualified technical talent. With over 1.2 million unfilled IT roles, hiring managers are under pressure to scale teams without compromising on quality or culture.

Solution

SMASH offers a unique nearshoring model: placing vetted, high-performing Costa Rican and/ or Colombian professionals as full-time embedded team members — not just contractors or outsourced labor. By managing the hiring, vetting, and onboarding process, SMASH ensures both speed and quality while creating true cultural and operational alignment.

Results

• Extra Space Storage scaled from 5 to 30 developers since 2019
• Customer retention rates of over 80% over the past 6 years
• Growing from 2 to 10 engineers at SILAC company.
• Seamless team integration and accelerated product development

Testimonials

“It’s hard to find good security coders, and we were able to have the ones we needed through SMASH
immediately. They were also very good at helping the rest of the team with the whys and the hows.”
— Christina Belnap, CSO, SILAC

“When I tell SMASH I need technical talent, I trust that they will find exactly what I need.”
— Dan Lauter, CEO & VP of Operations Health Catalyst

“SMASH does a really good job at finding top technical talent.”
— David Callahan, CTO, Experlogix

“The technical skills were solid, and the cultural fit was mutual.”
— Ken Myers, Manager of Data Engineering, Eptura

“SMASH played a significant role for us. They enabled us to scale quickly through skilled talent.”
— Sam Belnap, COO, SILAC

“We couldn’t have scaled this quickly without SMASH. They helped us build software and solutions we couldn’t have done on our own.”
— Rich Keeler, VP of Software Engineering, Extra Space Storage

“SMASH does the legwork. It felt like shooting fish in a barrel — every candidate was hirable. We just had to pick who we liked best.”
— Jeff Scott, SVP Technology, Extra Space Storage

Future Vision

With a proven model and high customer satisfaction, SMASH is poised for exponential growth. The leadership team is focused on expanding sales, building strategic partnerships, and scaling the unique model that clients already love.

“We’ve built an engine that can support massive demand. The future is growth — and we’re ready.”
— Matt Phillipps, COO, SMASH

If you are not familiar with large language models (LLMs) today, you may already be falling behind in the AI revolution. Companies are increasingly integrating LLM-based applications into their workflows. As a result, there is a high demand for LLM engineers and operations engineers who can train, fine-tune, evaluate, and deploy these language models into production.

In this article, we will review 6 GitHub repositories that will help you master the tools, skills, frameworks, and theories necessary for working with large language models.

1. brexhq/prompt-engineering

This repository is a goldmine for learning prompt engineering, one of the most critical skills for working effectively with LLMs. It provides tips, tricks, and examples to help you craft better prompts and get the most out of models like GPT-4o.

Why it is important:

• Focuses on practical techniques for optimizing prompts.
• Includes examples for diverse use cases, such as summarization, coding, and creative writing.

2. mlabonne/llm-course

This repository offers a comprehensive course on LLMs, designed for learners of all levels. It includes tutorials, projects, and hands-on exercises to help you understand and apply LLMs effectively.

Why it is important:

• Covers both theoretical foundations and practical applications.
• Perfect for beginners and professionals looking to deepen their knowledge.

3. Hannibal046/Awesome-LLM

This is a complete list of resources related to LLMs, including research papers, tools, frameworks, and tutorials. It is a one-stop shop for exploring the LLM ecosystem and staying updated on the latest advancements.

Why it is important:

• Includes resources on training, evaluation, and serving LLMs.
• Regularly updated to include new models, tools, and research.

4. WooooDyy/LLM-Agent-Paper-List

This repository is a treasure trove of research papers on LLM-based agents. It is perfect for those interested in cutting-edge AI applications that use AI agents to improve capabilities of LLMs.

Why it is important:

• Stay up-to-date with the latest research on LLM-based agents.
• Ideal for academics and professionals exploring LLM agent applications.

5. avvorstenbosch/Masterclass-LLMs-for-Data-Science

This repository focuses on integrating LLMs into workflows. It provides an ebook-style introduction to various topics such as prompt engineering, local LLMs, retrieval-augmented generation (RAG) problems, and more. Furthermore, it includes exercises with solutions for you to practice your learning.

Why it is important:

• Learn to leverage LLMs in technical projects.
• Tailored for data scientists looking to expand their skill set.

6. Shubhamsaboo/awesome-llm-apps

This repository is a collection of awesome LLM-based applications, showcasing real-world use cases built with OpenAI, Anthropic, Gemini, and open-source models. It also highlights AI agents and retrieval-augmented generation (RAG) systems.

Why it is important:

• Explore real-world applications of LLMs.
• Get inspired by unique use cases and easy to use frameworks.

Conclusion

Mastering LLMs requires a blend of theoretical knowledge, familiarity with modern tools, and hands-on practical experience. The 6 GitHub repositories covered in this blog offer all three by introducing you to cutting-edge AI frameworks, providing valuable resources, papers, and tutorials, and guiding you through exercises and projects to build your own LLM-based applications. Additionally, these repositories are regularly updated, helping you stay current with advancements in LLM applications, AI agents, and frameworks.