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Issue 51 · July 2026Prompt engineering, quietly

Writing about the craft of prompting, the shape of agents, and the small engineering decisions that make models useful in real work.

№ 01 · Featuredtutorials8 min read

How to Build an Open Coding Agent Stack

Learn how to combine Codex CLI, Goose, and smolagents into one practical coding agent stack for 2026. See what each layer does best. Try free.

RephraseApril 19, 2026Read the essay →
Recently  ·  July 2026
  1. № 02

    How to Write Better CLAUDE.md Files

    Learn how to write CLAUDE.md files that improve coding agents with less drift, lower cost, and sharper project context. See examples inside.

    prompt engineering
    RephraseApril 19, 2026  ·  8 min read
  2. № 03

    Cursor vs Claude Code vs Codex CLI

    Discover which coding agent ships faster in real workflows, and how Cursor, Claude Code, and Codex CLI differ on speed, control, and fit. Read on.

    ai tools
    RephraseApril 19, 2026  ·  8 min read
  3. № 04

    How to Hedge AI Workflow Capabilities

    Learn how to build AI workflows that survive model delays, drift, and outages with capability hedging patterns, prompts, and fallbacks. Try free.

    prompt engineering
    RephraseApril 18, 2026  ·  7 min read
  4. № 05

    How to Design Lean Tool Sets for AI Agents

    Learn how to design minimal tool sets for AI agents that stay accurate, reduce tool confusion, and scale better in production. Try free.

    prompt engineering
    RephraseApril 18, 2026  ·  8 min read
  5. № 06

    How LLM Agent Memory Should Work

    Learn how episodic, semantic, and procedural memory fit together in LLM agents, and how to design a memory architecture that scales. Try free.

    prompt engineering
    RephraseApril 18, 2026  ·  8 min read
  6. № 07

    How to Apply Anthropic's Context Guide

    Learn how to apply Anthropic's context engineering guide in real workflows, with decoded tactics, examples, and mistakes to avoid. Try free.

    prompt engineering
    RephraseApril 18, 2026  ·  8 min read
  7. № 08

    How to Build a 12-Factor AI Agent

    Learn how to apply 12-factor software principles to AI agents for safer, testable, and scalable LLM systems. See practical examples inside.

    prompt engineering
    RephraseApril 18, 2026  ·  8 min read
  8. № 09

    Why Agents Must Keep Their Wrong Turns

    Learn how to design AI agents that preserve failed steps, recover from errors, and use context better after mistakes. See examples inside.

    prompt engineering
    RephraseApril 17, 2026  ·  8 min read
  9. № 10

    Why Dynamic Tool Loading Breaks AI Agents

    Learn why dynamic tool loading hurts AI agent reliability, bloats context, and causes bad routing decisions-and what to build instead. Try free.

    prompt engineering
    RephraseApril 17, 2026  ·  7 min read
  10. № 11

    Why KV-Cache Hit Rate Matters Most

    Learn why KV-cache hit rate drives latency and cost for AI agents, and how stable prefixes turn cache reuse into a real production edge. Try free.

    prompt engineering
    RephraseApril 17, 2026  ·  8 min read
  11. № 12

    How the 4 Moves of Context Engineering Work

    Learn how to use the 4 moves of context engineering-offloading, retrieval, isolation, and reduction-to build better AI systems. Try free.

    prompt engineering
    RephraseApril 17, 2026  ·  8 min read
Page 19 of 51
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