Prompt Tip of the Day

Trent Creal
Aug 4
3 min read

Prompt tip of the day

Mastering AI Prompts: A Proven Framework That Works

If you’ve been exploring AI tools like Claude, you’ve probably hit that wall where the outputs feel hit-or-miss. One day it’s genius, the next it’s a head-scratcher. That inconsistency usually points back to one thing: your prompts.

Anthropic’s applied AI team recently laid out a sharp, step-by-step framework for creating production-ready prompts—and it’s one of the most structured approaches out there. Unlike the usual trial-and-error advice, this method gives you a repeatable system that works in high-stakes environments like insurance claims or legal review.

The Five-Part Prompting Blueprint

Their framework is simple but surgical:

Task Description – Be crystal clear on what you want.
Content – Provide all the relevant context or data.
Detailed Instructions – Lay out the logic Claude should follow, step by step.
Examples – Include tricky, real-world edge cases to teach good judgment.
Reminders – Reinforce tone, accuracy, and key constraints.

Now, let’s break down the tactical gold inside each step.

Why XML Beats Markdown

Instead of using markdown or plain text, use XML-style tags to structure your prompt. This lets you clearly define different sections like <context>, <instructions>, or <examples>. Claude handles this format with precision and can better distinguish between input types, reducing confusion.

Lock in Static Information Early

Anything that stays consistent—like the format of a form, industry-specific rules, or organizational policies—should go in the system prompt. That keeps Claude from relearning the same things every time. This is prompt caching in action, and it’s a major time-saver.

Control the Flow

Don’t assume Claude knows what order to tackle your task in. Spell out the exact steps. For example:

First, summarize the incident. Then, identify all involved parties. Finally, match each party to their policy details.

This tells the model what to do and when to do it—cutting down on irrelevant or out-of-sequence replies.

Use Edge Cases to Teach Judgment

Got examples where human judgment is key? Add them. Like this one: a form shows both drivers saying they had the right-of-way. A human knows the backing driver usually yields. That kind of nuance, shown in example format, trains the model to avoid bad assumptions.

Set the Tone and Guardrails

You need to manage more than just logic—you need to steer tone. Tell Claude to keep its answers factual, avoid speculation, and only assess claims when it’s confident.

And to reduce hallucination risk, require it to quote the input source when making factual claims. That way, you can verify its statements with a simple search.

Start With Your Desired Format

Want Claude’s output to begin a certain way? Seed it. Kick off the expected format with something like { for JSON or a specific XML tag. Claude will follow that structure without extra filler.

Go Deep with Extended Thinking Mode

Anthropic recommends using Claude’s extended thinking capabilities to generate deeper analysis. Then, study those responses to fine-tune your system prompt even further. This feedback loop helps you evolve from good prompts to bulletproof ones.

The Bottom Line

This framework took Claude from hallucinating ski accidents to delivering clear, confident, and compliant insurance assessments. The real takeaway? Don’t leave things to chance. Be extremely specific with what you want—context, sequence, format, and tone.

Get this right, and your AI stops guessing and starts performing.

Prompt tip of the day.

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