#llm Development Tutorials & Tips | Roast Dev

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I thought you’d be more skeptical

A couple of weeks ago, at a weekly family dinner, I was discussing my thoughts on AI with someone when they turned and said, “I’m really interested to see where you go. If anyone was super skeptic...

25.04.2025 0 Read More

The Rise of Agentic AI in Software Development

Agentic AI is reshaping how software is built by thinking, deciding, and acting on its own.In our latest blog, we explore how this evolution moves us from reactive, prompt-based systems to intelligent...

25.04.2025 0 Read More

Unlocking Efficiency: The Power of Kong AI Gateway

In today’s rapidly evolving digital landscape, organizations increasingly rely on APIs to drive innovation, enhance connectivity, and streamline operations. However, as the complexity of managing th...

26.04.2025 0 Read More

Vibe Coding Is Fun—But Vibe Refactoring Pays the Bills

There’s a lot of hype about vibe coding—that moment when caffeine hits, your playlist slaps, and you hammer out code like a jazz drummer sprinting through a solo. It’s exhilarating, but relyi...

26.04.2025 0 Read More

How Proxies Boost the Performance of Training Large Language Models

Large Language Models (LLMs) are revolutionizing AI by powering everything from chatbots to real-time translation systems. However, these models don’t learn from just any data; they thrive on massiv...

27.04.2025 0 Read More

The Mistakes I Made While Using Open-Source LLMs — and What I Wish I Knew Earlier

I'm almost embarrassed to admit this, but for the longest time, I was using open-source LLMs completely wrong. It wasn’t until I started working on projects and diving into real-world deployments th...

27.04.2025 0 Read More

How run LLM in local using Docker.

Self-hosted LLMs are gaining a lot of momentum. They offer advantages such as improved performance, lower costs, and better data privacy. You don't need to rely on third-party APIs, which means no une...

27.04.2025 0 Read More

How to train LLM faster

RAG is an architecture where an LLM (Large Language Model) is not asked to answer purely from its own parameters but is given external information at runtime to use while answering.✅ Goal: Reduce ...

28.04.2025 0 Read More

MCP: Is It Really Worth Its Hype?

The technology community cannot stop talking about MCP, short for Model Context Protocol, developed by the Claude-maker Anthropic ,open-sourced in November 2024, MCP addresses the complexities of conn...

28.04.2025 0 Read More

Invoice Data Extraction using IBM Granite LLM locally (not from watsonx!)

Adapting Granite use-case to execute locally. Introduction The Granite family of foundation models span an increasing variety of modalities, including language, code, time series, and science ...

28.04.2025 0 Read More

I thought you’d be more skeptical

The Rise of Agentic AI in Software Development

Unlocking Efficiency: The Power of Kong AI Gateway

Vibe Coding Is Fun—But Vibe Refactoring Pays the Bills

How Proxies Boost the Performance of Training Large Language Models

The Mistakes I Made While Using Open-Source LLMs — and What I Wish I Knew Earlier

How run LLM in local using Docker.

How to train LLM faster

MCP: Is It Really Worth Its Hype?

Invoice Data Extraction using IBM Granite LLM locally (not from watsonx!)

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