Prompting Guides
A curated collection of 10 prompting guides for building with AI coding agents.
AI Coding Agents in 2026: The Open-Source & CLI Edition
Cursor and Windsurf vs the open-source agents — OpenCode, Cline, Aider, Codex CLI, and more. Who should bring their own model, and when to stay in the terminal.
Claude vs GPT vs Gemini for Coding in 2026
The three frontier model families compared for real coding work — agentic depth, ecosystem fit, context, and cost shape — plus how to actually choose.
Context Engineering
Treating the context window as a finite budget — what to load, what to leave out, and when to reset.
Cursor vs Claude Code vs GitHub Copilot vs Windsurf in 2026
A practical, opinionated comparison of the four mainstream AI coding tools — form factor, agentic depth, model choice, and who each one is for.
Designing System Prompts for LLM Apps and Agents
How to write system prompts that hold up in production: what belongs there vs. the user turn, structure that survives long context, and format/refusal rules.
Programmatic Prompt Optimization with DSPy: Stop Hand-Tuning Prompts
Hand-tuning prompts doesn't scale. DSPy treats prompting as programming — declare tasks as typed signatures and let an optimizer compile the prompts for you.
Effective Tool Use: Scoping an Agent's Toolset
How to scope tools and permissions so an agent reaches for the right one and can't do damage.
Prompt Patterns for Coding Agents
Practical prompting patterns: chaining, few-shot, context management, tool use, and output structuring.
Few-Shot vs Chain-of-Thought vs Structured Prompting: What to Use When (2026)
When to reach for few-shot examples, chain-of-thought reasoning, or structured/output-constrained prompting — a 2026 decision guide to the core techniques.
Vibe Coding in 2026: What It Is, When It Works, When It Bites
An honest guide to vibe coding — where prompt-and-accept development genuinely pays, where it accumulates risk, and the guardrails that make it professional.