7 costly mistakes to avoid

Prompt Mistakes That Cost You Hours

These mistakes slow you down, waste your time, and produce mediocre outputs. Learn what goes wrong, why it happens, and how to fix it with before/after examples.

1

Not Declaring Constraints Upfront

Problem: You get generic, unfocused answers that miss the mark.

Solution: Define boundaries first: word count, tone, format, audience.

💡 Law #2: Constraints = Clarity
❌ Before
"Write an article about AI."
✓ After
"Write a 500-word article about AI for marketing professionals. Use a conversational tone. Include 3 actionable tips."

Key Improvements

  • Specific word count (500)
  • Target audience (marketing professionals)
  • Tone specified (conversational)
  • 3 actionable tips required
2

Using the Same Temperature for All Tasks

Problem: Creative tasks get boring outputs; analytical tasks get unreliable answers.

Solution: Use higher temperature (0.7-1.0) for creative work, lower (0.1-0.3) for factual/analytical tasks.

💡 Law #12: Temperature Controls Creativity
❌ Before
Using default temperature for everything
✓ After
Temperature 0.9 for brainstorming ideas
Temperature 0.2 for code debugging
Temperature 0.5 for balanced content

Key Improvements

  • Creative tasks: higher randomness
  • Analytical tasks: more deterministic
  • Balanced tasks: medium temperature
3

Accepting the First Output Without Iteration

Problem: You settle for mediocre results instead of excellence.

Solution: Always follow up with refinement prompts: "Make it more concise", "Add specific examples", "Improve the opening".

💡 Law #7: Iteration Beats Perfection
❌ Before
Taking the first response as final
✓ After
1st prompt: Get the draft
2nd: "Make it 30% shorter"
3rd: "Add a compelling hook"
4th: "Include 2 data points"

Key Improvements

  • Multiple refinement rounds
  • Progressive improvement
  • Specific enhancement requests
4

Not Using Follow-Up Prompts

Problem: You lose context and start over, wasting time on repeated setup.

Solution: Build on previous outputs: "Expand on point 2", "Now create an email version", "Turn this into bullet points".

💡 Law #15: Context is Memory
❌ Before
Starting fresh prompts for related tasks
✓ After
Initial: [Get analysis]
Follow-up 1: "Expand the risks section"
Follow-up 2: "Create an exec summary"
Follow-up 3: "Add mitigation strategies"

Key Improvements

  • Maintains conversation context
  • Builds on previous work
  • Saves setup time
5

Ignoring Hallucination Warnings

Problem: You publish false information that damages credibility.

Solution: Verify facts, ask for sources, cross-check critical claims, use lower temperature for factual content.

💡 Law #9: Facts Need Verification
❌ Before
Trusting all output blindly
✓ After
"Provide sources for each claim."
"Double-check this data."
"Flag any uncertain information."
Manual fact-checking for critical content

Key Improvements

  • Request sources explicitly
  • Flag uncertainties
  • Manual verification for key facts
6

Copying Prompts Without Adapting Them

Problem: Generic templates give generic results that don't fit your specific use case.

Solution: Customize every prompt: add your context, specific constraints, desired format, and examples.

💡 Law #4: Examples Guide Output
❌ Before
Using template: "Act as a marketing expert and write copy"
✓ After
Adapted: "Act as a B2B SaaS marketing expert. Write email copy for enterprise CTOs. Tone: authoritative but approachable. Format: 150 words max. Include: problem, solution, CTA. Example style: [paste sample]"

Key Improvements

  • Specific industry context (B2B SaaS)
  • Target audience (enterprise CTOs)
  • Precise constraints
  • Example provided
7

Not Building a Prompt Library

Problem: You waste hours recreating prompts you've already perfected.

Solution: Save successful prompts with notes on when to use them. Build a personal prompt database.

💡 Law #18: Reuse Beats Reinvention
❌ Before
Recreating prompts from scratch each time
✓ After
Library with categories:
- Email templates (cold outreach, nurture, conversion)
- Content creation (blog, social, newsletters)
- Analysis (SWOT, competitive, market)
- Code review (debugging, optimization, documentation)

Key Improvements

  • Organized by use case
  • Documented variations
  • Quick access to proven prompts

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