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Prompt engineering playbook details 5 key patterns for reliable AI agents

By PulseAugur Editorial · [1 sources] ·

Kunal Ganglani has developed a prompt playbook containing over 100 reusable prompts, categorized into five key patterns that significantly improve AI output quality and reliability. These patterns include Chain-of-Thought for complex reasoning, few-shot prompting for style and format, prompt chaining for breaking down tasks, meta-prompting for AI-assisted prompt refinement, and constrained output prompting for deterministic results. Ganglani emphasizes treating prompts as version-controlled software artifacts rather than ad-hoc notes to build robust AI agents. AI

IMPACT Provides practical strategies for improving AI model output and reliability through structured prompt engineering.

RANK_REASON The item is a blog post detailing prompt engineering techniques and best practices, rather than a release of new technology or a significant industry event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Prompt engineering playbook details 5 key patterns for reliable AI agents

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Commentary
The item is a blog post detailing prompt engineering techniques and best practices, rather than a release of new technology or a significant industry event.
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High
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47 days old
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Kunal ·

    5 Prompt Patterns From My 100+ Prompt Playbook [2026]

    <blockquote> <p>Originally published at <a href="https://www.kunalganglani.com/blog/prompt-engineering-patterns-that-changed-how-i-ship" rel="noopener noreferrer">kunalganglani.com</a> — read it there for inline code, hero image, and live links.</p> </blockquote> <h1> 5 Prompt Pa…

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