Blog
Insights, technical guides, and product thinking from the Tanok Tech team.
RAG vs Fine-Tuning: When to Use Each Approach in Production
Choosing between Retrieval-Augmented Generation and fine-tuning can make or break your LLM application. This guide compares both approaches and helps you decide.
Read more →How AI Agents Are Automating Software Development
Explore how AI agents are transforming software development by automating coding, testing, and deployment, boosting productivity and reducing errors.
Read more →Vibe Coding: Programming with AI Without Understanding the Code
Vibe coding lets you build software by describing what you want, with AI generating the code. Explore how it works, its risks, and practical tips for success.
Read more →GPT-5 vs Claude 4: Comparing the Most Advanced AI Models in 2026
GPT-5 and Claude 4 redefine AI capabilities in 2026. Compare their reasoning, coding, multimodal abilities, and pricing to choose the right model.
Read more →PostgreSQL Performance Tuning for High-Throughput Applications
Optimize PostgreSQL for high-throughput applications with practical tuning on connections, memory, I/O, vacuuming, and query performance.
Read more →Cursor Becomes the Dominant AI IDE in 2026
In 2026, Cursor has emerged as the leading AI-powered IDE, revolutionizing software development with deep codebase understanding and intelligent automation.
Read more →Preventing LLM Hallucinations in Real-World Applications
Discover practical strategies to reduce LLM hallucinations in production—from prompt engineering to retrieval-augmented generation—and ensure your AI delivers accurate, trustworthy outputs.
Read more →Preventing LLM Hallucinations in Real-World Applications: A Practical Guide
Learn actionable strategies to reduce LLM hallucinations: retrieval augmentation, prompt engineering, fine-tuning, and validation techniques with code examples.
Read more →Advanced Prompt Engineering: CoT, ReAct, and Tree-of-Thoughts
Explore advanced prompt engineering techniques like chain-of-thought, ReAct, and tree-of-thoughts to enhance LLM reasoning and problem-solving.
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