I’m lazy about prompting. Typing out long, detailed instructions sucks, so I started doing the obvious thing: asking the chatbot to write the good prompt for me. It’s pretty effective, and chatbots tell me that it is a common technique. You give a short, half-baked request like “help me write a prompt for X”, and the AI spits out a strong, structured one ready to go. Minimal typing, much better results.

Get Better AI Results Without Typing a Novel

Here are three real examples of how I actually use it.

1. Getting Latest Info Without Doing Research Yourself

Your rough input:

“Help me write a prompt about the latest ways to reduce hallucinations in LLMs.”

The strong prompt the AI generates:

You are an expert AI researcher and technical writer. Provide the latest practical developments (as of April 2026) on reducing hallucinations in chatbots and LLMs.

Focus on production-relevant techniques. Structure the response with:

  • Key methods and their real-world effectiveness (include numbers where possible)
  • Easy prompting tricks and system-level fixes
  • What’s reliably deployed vs still experimental

Be concise, evidence-based, and useful for everyday users. Any questions or clarifications needed before you answer?

You just copy that and run it (or tell the AI to execute it directly). Way better than writing it yourself.

2. Get the Chatbot to ask questions

Your rough input:

"Help me create a Grok task. I want a weekly summary of AI news, primarily from the major players US and International, but including significant new releases on hugging face and github. It should include references on where to read on the web or watch on YouTube. Ask questions if you have them.”

Grok responds with:

A few questions to make it perfect for you

  • Preferred day/time? (e.g., Monday morning, Sunday evening, etc.)
  • Any specific players or topics to emphasize or de-emphasize? (e.g., more on multimodal/agents/robotics/hardware, or less on certain companies)
  • Detail level? (The prompt above is concise; want longer explanations or more items?)
  • Extra sections? (e.g., research papers/arXiv, ethics/regulations, or hardware announcements?)
  • Anything else? (tone, length, specific YouTube channels, newsletters like Ben’s Bites, etc.)

Ignore any questions that are not meaningful. In this case I'm using Grok tasks, which has its own scheduler in the UI. Definitely don't go into more details than you have to in answering the questions, and you can certainly follow up with "Any more questions?"

I've noticed that Grok will create the prompt as presented, and then ask its questions. You can use that as a benchmark on its current thinking.

I respond with:

"Let's start with detailed, since I'll only read it once a week. Papers, ethics, and hardware definitely. I'm especially interested in xAI, since they don't seem to speak publicly much. Models, tools, workflows, even installation instructions for open-source items."

The strong prompt the AI generates:

Generate a detailed weekly AI news summary covering the most significant developments from the past 7 days (or since the last summary). Aim for depth since this is read once per week — provide context, implications, and practical details where relevant. Be factual, objective, and neutral.

Primary focus areas:

  • Major US players (OpenAI, Anthropic, Google DeepMind, Meta, Microsoft, xAI, NVIDIA, etc.), especially highlight any xAI news, Grok updates, or related announcements (search X heavily for @xai, @grok, Elon Musk, and team members since they communicate less via traditional channels)
  • International players (Mistral, DeepSeek, Alibaba, Baidu, other Chinese labs, European/Asian efforts)
  • Significant new models, datasets, tools, demos on Hugging Face
  • Notable AI-related open-source releases, libraries, major updates on GitHub
  • Key research papers (arXiv, NeurIPS, etc.)
  • Hardware announcements and infrastructure
  • Ethics, safety, regulations, policy developments

Structure the output in clean Markdown:

Top Headlines

(4–7 biggest stories overall, with 2–4 sentence descriptions each)

US Major Players

(Especially detailed on xAI/Grok)

International Developments

Research Papers & Breakthroughs

(Highlight 3–6 notable papers with titles, authors, key findings, why they matter, and arXiv links)

Hardware & Infrastructure

Ethics, Safety & Regulations

Hugging Face Highlights

(New models, spaces, datasets — include quick usage notes)

GitHub Open-Source Drops

(For each major release: short description, why it matters, key features, installation/run instructions or one-liner commands if available, GitHub link)

For every item:

  • 3–6 sentence description with context and real-world impact
  • Why it matters (technical, business, societal)
  • Direct references: official blogs, papers (arXiv), news articles, announcement tweets, or relevant YouTube videos/talks
  • For open-source tools/models: practical details like installation commands (pip/git clone + requirements), quick start workflows, or Colab links when available

Use all tools aggressively:

  • web_search for general news
  • x_keyword_search and x_semantic_search (especially for xAI, recent from:@xai OR from:grok etc.)
  • browse_page on huggingface.co/blog, github.com/trending/ai, arxiv.org
  • Follow up on promising links for details

Keep the full summary comprehensive but readable in 15–25 minutes. Prioritize substance over quantity.

Again, you barely typed anything.

3. Coding Tasks (The “Another Agent” Trick)

Your rough input:

“Help me write a prompt to review and fix some code another agent wrote.”

The strong prompt the AI generates:

You are a senior software engineer reviewing code written by another AI programming agent. That agent is decent but commonly makes typical LLM mistakes: hallucinated APIs, ignored edge cases, overly complex solutions, weak error handling, or poor naming.

Here is the current code and my goal: [paste code + goal].

First, list any issues you spot. Then provide a clean, improved, well-commented version using best practices. Think step-by-step. Any questions before you start?

I've been using this with Claude and Codex recently and consistently gets sharper code reviews because of the “another agent” framing. Not sure why. Maybe they're in competition, but using one agent to review the work of another has solved problems that I'd been ready to research myself out of frustration.

Bottom Line

Stop trying to write perfect prompts yourself. Just start your message with “Help me write a prompt for…” (or “Turn this rough idea into a strong prompt…”), add your 1-2 sentence goal, and let the AI do the rest. Throw in “Any questions?” at the end if you want even cleaner results.

It feels like cheating — because it kind of is. Less typing, better outputs. Try it on whatever you’re working on next.