blog-writing

name	blog-writing
description	Technical blog post writing for the OpenShift AI fine-tuning platform

Write technical blog posts targeting ML engineers and platform operators using OpenShift AI for model fine-tuning.

Article Structure

1. Hook: Start with the problem being solved or the capability being demonstrated (e.g., fine-tuning a 70B model with QLoRA, achieving 2x throughput with Liger Kernels)
2. Context: Brief background on the relevant technology (PyTorch, Transformers, TRL, PEFT, InstructLab, Liger Kernels, etc.)
3. Content: Step-by-step walkthrough with code samples, model configurations, or benchmark results
4. Results: What the reader achieves, performance numbers, model quality metrics, or key takeaways
5. Next steps: Links to documentation, notebooks, or related articles

Writing Guidelines

• Use clear, concise language. Avoid jargon without explanation.
• Include complete, runnable code samples (not snippets that won't work alone)
• Add diagrams for architecture, data flow, or distributed training topology
• Include benchmark numbers with methodology when discussing performance
• Keep articles focused: one topic per post, 1000-2000 words
• Use consistent terminology: "fine-tuning" not "finetuning" interchangeably; "LoRA" not "Lora"

Review Process

1. Domain agent drafts the article
2. Technical Editor reviews for clarity, consistency, and polish
3. Revisions if needed
4. Final publish