The PromptEngineering Edge

“Cut Through the Hype: AI Tactics for Seasoned IT Pros.”

  • Prompt Engineering Blueprint

    Prompt Engineering Cheat Sheet Core Commands & Techniques

    1. Role AssignmentCommand: “Act as a [role]” Use Case: Establishes expertise context and response style

    Example: “Act as a marketing strategist with 10 years of experience”

    2. Step-by-Step Reasoning Command: “Think step by step” or “Break this down step by step” Use Case: Complex problem solving, analysis, calculations

    Example: “Calculate the ROI step by step for this marketing campaign”

    3. Format Specification

    Command: “Format your response as [format]”

    Use Case: Structured outputs, specific document types

    Example: “Format your response as a bulleted executive summary”

    4. Context Setting Command: “Given the context that [context], please…

    “Use Case: Providing background information for better responses

    Example:

    “Given that this is for a B2B SaaS company, create a content strategy”

    5. Output Constraints Command: “In exactly [number] words/sentences/paragraphs”

    Use Case: Meeting specific length requirements

    Example: “Summarise this in exactly 50 words”

    Advanced Techniques

    6. Few-Shot Learning Command: Provide 2-3 examples before asking

    Use Case: Pattern recognition, consistent formatting Example: Show examples of good headlines, then ask for more

    7. Chain of Thought Command: “Show your reasoning process”

    Use Case: Transparent decision-making, learning from AI logic

    Example: “Show your reasoning for ranking these marketing channels”

    8. Perspective Taking

    Command: “From the perspective of [persona]” Use Case: Targeted content, audience-specific responses

    Example: “From the perspective of a busy CEO, what are the key points?”

    9. Iterative Refinement

    Command: “Improve this by focusing on [aspect]” Use Case: Content optimisation, progressive enhancement

    Example: “Make this more persuasive by adding emotional appeals”

    10. Constraint Addition Command: “While avoiding [constraint]”

    Use Case: Filtering unwanted elements, focusing approach

    Example: “Create a pitch while avoiding technical jargon”

    Specialised Applications

    11. Content Creation Command: “Create [content type] for [audience] about [topic]”

    Use Case: Marketing materials, educational content

    Example: “Create a LinkedIn post for marketers about AI tools”

    12. Analysis & Critique Command: “Analyse [item] for [criteria]” Use Case: Content review, strategic evaluation

    Example: “Analyse this email for conversion potential”

    13. Comparison Frameworks Command: “Compare [A] vs [B] across [dimensions]” Use Case: Decision-making, feature analysis

    Example: “Compare these two strategies across cost, time, and impact”

    14. Scenario Planning Command: “What would happen if [scenario]?” Use Case: Risk assessment, strategic planning

    Example: “What would happen if we doubled our content output?”

    15. Template Generation Command: “Create a template for [use case]” Use Case: Scalable processes, consistency

    Example: “Create a template for customer onboarding emails”

    Quality Enhancement

    16. Specificity Boosters Command: “Be specific about [aspect]” Use Case: Detailed, actionable responses

    Example: “Be specific about implementation timelines”

    17. Evidence Requests Command: “Support your recommendations with reasoning “Use Case: Credible, well-reasoned outputs

    Example: “Explain why you recommend this approach over alternatives”

    18. Multi-Angle Analysis Command: “Consider this from multiple angles” Use Case: Comprehensive evaluation, risk mitigation

    Example: “Analyse this decision from financial, operational, and customer angles”

    19. Assumption Checking Command: “What assumptions are you making?”

    Use Case: Identifying blind spots, clarifying context

    Example: “What assumptions about our target market are you making?”

    20. Output Validation Command: “Double-check this for [criteria]” Use Case: Quality assurance, error reduction

    Example: “Double-check this calculation for accuracy”

    Quick Reference Commands Goal Command Structure Example

    Get specific format” Format as [type]”

    “Format as a table”

    Add constraints”

    While ensuring [requirement]”

    “While keeping it under 100 words”

    Target audience”

    For [audience]”

    “For technical professionals”

    Set tone” Use a [tone] tone”

    “Use a conversational tone”

    Request examples”

    Include [number] examples”

    “Include 3 specific examples” Add urgency” This is for [timeline]”

    “This is for tomorrow’s meeting”

    Pro Tips for Better Prompts

    Be Specific: Vague prompts get vague responses

    Provide Context: Background information improves relevance

    Use Examples: Show don’t just tell what you wantIterate:

    Refine prompts based on initial outputs

    Combine Techniques: Stack multiple commands for complex tasks

    Test Variations: Try different phrasings for better results

    Set Clear Expectations: Define success criteria upfront.

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  • Ai + DevOps is Game-Changer
    Enter the Prompt Vault

    Here is a guide and workflow for deploying Terraform changes to AWS via GitHub Actions, incorporating secure credential management via GitHub Secrets. It is formatted for direct copy-pasting into Notion and WordPress.


    Automated Terraform Deployment Pipeline with GitHub Actions & Secrets Management

    Automating infrastructure deployments requires a balance between speed and security. This guide details how to build a continuous deployment (CD) pipeline using GitHub Actions to automatically run terraform plan on pull requests and apply changes upon merging, using GitHub Encrypted Secrets to safely manage cloud access keys.


    Architecture Overview

    1. Pull Request Trigger: Automatically executes terraform plan and posts/logs the dry-run output.
    2. Push to Main Branch: Automatically runs terraform apply to provision or update infrastructure.
    3. Secrets Management: Cloud provider credentials (AWS Access Keys) are securely retrieved from GitHub Repository Secrets at runtime without exposing sensitive data.

    Step 1: Configure GitHub Repository Secrets

    Before writing the deployment workflow, securely store your Cloud Credentials in your GitHub repository.

    1. Navigate to your repository on GitHub.
    2. Click Settings in the top navigation bar.
    3. In the left sidebar, expand Secrets and variables and select Actions.
    4. Click New repository secret and create the following two secrets:
      • Name:AWS_ACCESS_KEY_ID
        • Value: Your AWS IAM Access Key ID
      • Name:AWS_SECRET_ACCESS_KEY
        • Value: Your AWS IAM Secret Access Key

    Security Tip: For production environments, consider using OpenID Connect (OIDC) to authenticate with cloud providers without storing long-lived credentials.


    Step 2: Create the Deployment Workflow File

    1. Navigate to the Actions tab in your repository.
    2. Click New workflow $\rightarrow$ Set up a workflow yourself.
    3. Name the file .github/workflows/terraform-deploy.yml.

    Step 3: Workflow Definition

    Paste the following YAML file into the GitHub Web Editor:name: Terraform Automated Deployment on: push: branches: - main pull_request: branches: - main workflow_dispatch: jobs: terraform-cd: name: Plan and Apply Terraform runs-on: ubuntu-latest env: AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} AWS_REGION: 'us-east-1' steps: - name: Checkout Codebase uses: actions/checkout@v4 - name: Setup Terraform CLI uses: hashicorp/setup-terraform@v3 with: terraform_version: "1.6.0" - name: Initialize Terraform run: terraform init - name: Generate Terraform Plan (Pull Request) if: github.event_name == 'pull_request' run: terraform plan -no-color - name: Apply Terraform Changes (Main Branch) if: github.ref == 'refs/heads/main' && github.event_name == 'push' run: terraform apply -auto-approve


    Step 4: Commit & Test the Pipeline

    1. Click Commit changes… in the upper right.
    2. Enter a commit message: ci: add terraform deployment workflow with secret management.
    3. Select Commit directly to the main branch and save.
    4. Go to the Actions tab to inspect the execution under Terraform Automated Deployment.

    Pipeline Execution Breakdown

    Event Execution Step Outcome Pull Requestterraform plan Generates a preview of resources to be added, changed, or destroyed. Merge to Mainterraform apply Automatically applies infrastructure modifications to the AWS environment. Manual Triggerworkflow_dispatch Allows manual pipeline execution directly from the GitHub UI.


    Would you like me to create an environment protection step to require manual approvals before terraform apply runs?

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The PromptEngineering Edge

“Cut Through the Hype: AI Tactics for Seasoned IT Pros.”

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