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Field notes.

Issue 44 · May 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 · Featuredprompt engineering7 min read

Why Codex Was Told Not to Mention Goblins

Discover why the Codex system prompt leak matters, what the goblin rule signals about AI control, and how hidden prompts really work. Read on.

Opening

The weirdest thing about a system prompt leak is never the weird line itself. It's what that line reveals about how brittle modern AI systems still are.

Continue reading →
RephraseMay 5, 2026Read the essay →
Recently  ·  May 2026
  1. № 02

    GPT-5.5 Models: Which One Should You Use?

    Learn how to choose GPT-5.5 Instant, Pro, or Thinking with a simple decision matrix for speed, cost, and complexity. See examples inside.

    ai tools
    RephraseMay 5, 2026  ·  7 min read
  2. № 03

    Why GPT-5.5 Codex Uses Fewer Tokens

    Discover why GPT-5.5 Codex token efficiency matters more than raw pricing, and how fewer tokens can lower real coding costs. Read the full guide.

    prompt engineering
    RephraseMay 25, 2026  ·  7 min read
  3. № 04

    How Moonshot Kimi Reached GPT-5.5 Level

    Discover how Moonshot pushed Kimi from top open-source to GPT-5.5-level performance in 18 months, and what that means for AI teams. Read on.

    ai tools
    RephraseMay 25, 2026  ·  7 min read
  4. № 05

    Why DeepSeek Model Aliases Can Bite You

    Learn how to choose between deepseek-chat aliases and explicit V4 models before July deprecation hits production. Read the full guide.

    ai tools
    RephraseMay 26, 2026  ·  7 min read
  5. № 06

    Why DeepSeek V4 Flash Is So Cheap

    Discover why DeepSeek V4 Flash costs 25x less than Pro yet gives up just 1.6 SWE-Bench points. Learn the tradeoffs and when to use it. Try free.

    ai tools
    RephraseMay 24, 2026  ·  7 min read
  6. № 07

    How to Fix DeepSeek V4 reasoning_content Error

    Learn how to fix the DeepSeek V4 reasoning_content 400 error during migration, especially in multi-turn tool chats. See examples inside.

    tutorials
    RephraseMay 24, 2026  ·  8 min read
  7. № 08

    Why AI Labs Are Leaving Apache 2.0

    Discover why Mistral, Kimi, and Qwen are drifting from Apache 2.0 to modified MIT-style licenses, and what that means for builders. Read on.

    ai news
    RephraseMay 24, 2026  ·  7 min read
  8. № 09

    Why Mistral Killed Three Models at Once

    Discover what Mistral Medium 3.5, Devstral 2, and Magistral reveal about model consolidation, tradeoffs, and product strategy. Read the full guide.

    ai tools
    RephraseMay 24, 2026  ·  8 min read
  9. № 10

    How to Prompt Mistral Medium 3.5

    Learn how to write better prompts for Mistral Medium 3.5 and why its merged 128B design changes prompting for coding and reasoning. Try free.

    prompt tips
    RephraseMay 24, 2026  ·  8 min read
  10. № 11

    Why Cost Per Task Beats Cost Per Token

    Discover why cost per completed task is a better AI metric than cost per token in 2026, with research-backed examples and practical guidance. Try free.

    prompt engineering
    RephraseMay 23, 2026  ·  8 min read
  11. № 12

    Why AI Routing Is Now a Product Layer

    Learn why AI routing is now core infrastructure, not optional plumbing, and how multi-model gateways cut cost, latency, and risk. Read the full guide.

    prompt engineering
    RephraseMay 23, 2026  ·  7 min read
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