8 posts
What is chain of thought? Chain of thought is a reasoning method where a language model answers a question by thinking step by step. When it helps, when it doesn't, and how reasoning models changed it.
What is prompt engineering? The deliberate design of the instruction that gets the output you want from a language model: role, task, context, constraint, and output format.
As Gartner puts it, context engineering is in, prompt out. How the role evolved, patterns that still work (CoT, few-shot), and managing context at enterprise scale.
What is prompt engineering and how is it applied at enterprise scale? Prompt patterns, system prompts, few-shot, chain of thought, prompt management and evaluation guide.
What is chain of thought? Chain of Thought is a prompting technique that makes a language model reason through intermediate steps before giving the final answer. This guide: a clear definition, why it works, how it works, few-shot and zero-shot CoT, its link to reasoning models, complex problem-solving examples, limits, and FAQs.
What is prompt engineering? Prompt engineering is the systematic design of inputs to reliably get the desired output from a language model. This guide: a clear definition, core techniques, few-shot and chain of thought, the system prompt, enterprise use, limits, and FAQs.
Most comprehensive Turkish technical guide for Chain-of-Thought (CoT) prompting: academic foundations (Wei et al. 2022 NeurIPS paper, Kojima et al. 'Let's think step by step'), 6 CoT variants (Zero-shot CoT, Few-shot CoT, Self-Consistency, Tree-of-Thoughts, Graph-of-Thoughts, Auto-CoT), benchmark performance (GSM8K 18% → 78%), 35+ Turkish practical examples, model-specific CoT behavior, when NOT to use, hallucination control, multi-step task design, agentic system integration, Turkish-specific pitfalls, cost impact.
A comprehensive Turkish guide that takes prompt engineering from zero to advanced. Covers the 6 components of a prompt, 14 core techniques (zero-shot, few-shot, CoT, ToT, ReAct, self-consistency, meta-prompting), Turkish-specific notes, 20+ ready templates, model-specific differences (GPT-5, Claude Opus 4.7, Gemini 3), prompt injection defenses, DSPy-based automatic optimization, and A/B testing.