Code to Slides: AI-Powered Presentation Generation

Overview of the Method

The core idea of this method is simple:

Use LLMs to understand and structure code logic, then use visuals to communicate that logic effectively.

Instead of manually translating code into slides, the workflow leverages:
– LLMs for reasoning and abstraction
– Visual generation for diagrams and flow explanations
– Fast iteration to improve clarity

This approach significantly reduces the time and effort required to create high-quality technical slides.

Why This Approach Is Effective

Traditional technical slides often fail because they:
– Contain too much raw code
– Overload slides with text
– Use visuals as decoration rather than explanation

This method solves those problems by:
– Prioritizing logical flow over syntax
– Making visuals the primary communication tool
– Treating slide creation as an iterative process assisted by LLMs

Summarize the Step-by-Step Process of This Method

Step 1: Select and Prepare the Code

Choose the algorithm or code segment you want to explain.
Clarify:
– Target audience
– Presentation goal
– Desired level of abstraction

Step 2: Use an LLM to Understand the Code

Provide the code to an LLM and request:
– A structured, high-level explanation
– Identification of key components
– Clear descriptions of data flow and control flow

This step converts code into **human-readable reasoning**.

Step 3: Design the Slide Structure

Based on the explanation:
– Break the logic into discrete concepts
– Assign one main idea per slide
– Arrange slides to tell a coherent story

At this stage, focus on *structure*, not visuals.

Step 4: Generate Visual Prompts

Ask the LLM to generate prompts for diagrams that explain:
– Processing steps
– Data transformations
– State transitions or decision points

The goal is functional clarity, not artistic design.

Step 5: Generate and Refine Visuals

Use an image generation model to create diagrams.
Iterate until:
– Each visual clearly explains a concept on its own
– Labels and relationships are easy to understand
– Visual style remains consistent across slides

Step 6: Assemble the Slides

Combine:
– Short, precise text
– Strong diagrams
– Descriptive slide titles

Slides should be understandable even without spoken explanation.

Step 7: Iterate and Optimize

Review the slides and refine:
– Remove unnecessary text
– Simplify diagrams
– Adjust explanations for the audience

Fast iteration is a key advantage of this workflow.

Key Principles to Remember

– Slides should explain **logic**, not raw code
– Visuals should carry most of the explanation
– LLMs are collaborators in thinking and structuring
– Iteration speed matters more than perfection

Demo

Step 1: Generate an initial prompt using Claude Code

Step 2: Receive the prompt output from Claude Code

Create a clean, modern infographic showing a PDF document processing pipeline with 7 steps flowing from top to bottom or left to right. Use a friendly color palette (blues, greens, purples) with icons for each step. The style should be minimalist and professional, suitable for a business presentation.

 

TITLE AT TOP: “How Your PDF Becomes Searchable Knowledge”

 

STEP 1: “Upload Your Document”

– Icon: PDF file with upload arrow

– Text: “You provide a PDF document to the system”

– Visual: Simple PDF icon

 

STEP 2: “Break Down the Pages”

– Icon: PDF splitting into multiple page sheets

– Text: “The system separates pages and extracts images”

– Visual: One PDF becoming multiple page thumbnails

 

STEP 3: “AI Reading & Understanding”

– Icon: Robot/AI brain reading a document

– Text: “Azure AI reads every word, table, and figure like a human would”

– Visual: AI character with magnifying glass over document

 

STEP 4: “Smart Chunking”

– Icon: Document breaking into puzzle pieces

– Text: “Content is organized into meaningful sections: paragraphs, tables, and figures”

– Visual: Document transforming into labeled chunks (P, T, F badges)

 

STEP 5: “Create Search Index”

– Icon: Filing cabinet or database

– Text: “A dedicated search library is created for your document”

– Visual: Clean database/index structure

 

STEP 6: “AI Understanding”

– Icon: Brain with network connections

– Text: “Each section is converted into AI language (embeddings) for smart search”

– Visual: Text transforming into glowing neural network pattern

 

STEP 7: “Ready to Answer Questions”

– Icon: Checkmark with chat bubble

– Text: “Your document is now ready to answer questions instantly!”

– Visual: Document with sparkles and a chat interface

 

BOTTOM FOOTER: “Powered by Azure AI Services”

 

Design notes:

– Use arrows or connecting lines between steps to show flow

– Each step should have equal visual weight

– Include small decorative elements (dots, lines) to make it modern

– Use 2-3 primary colors maximum for clarity

– Add subtle shadows or depth to make it pop

– Icons should be simple and universally understood

– Text should be large enough to read on a slide presentation

Step 4: Test the prompt with NotebookLM

PDF_to_Knowledge_Transformation

Step 5: Create a second improved prompt

Create a presentation series showing how a PDF becomes an AI-powered Q&A system. This is Part 1 containing infographics 1-3. Use modern, clean design with blues, greens, and purples. Professional and minimalist style suitable for business presentations.

—

INFOGRAPHIC 1/6: “Overview – From PDF to Smart Answers”

 

TITLE: “Turn Any PDF Into an AI-Powered Knowledge Assistant”

 

LAYOUT: Left-to-right comparison

 

LEFT SIDE – “Before”:

– Icon: Stack of static PDF documents

– Text: “Traditional PDFs”

– Bullet points:

• Hard to search

• Manual reading required

• Information locked away

– Visual: Gray/muted colors, dusty file cabinet

 

CENTER – “Transformation”:

– Icon: Magical wand or transformation arrows with sparkles

– Text: “AI Processing Pipeline”

– Visual: Flowing arrows with AI symbols

 

RIGHT SIDE – “After”:

– Icon: PDF with chat bubble and sparkles

– Text: “Intelligent Document”

– Bullet points:

• Instant answers

• Natural language search

• Context-aware responses

– Visual: Bright colors, modern interface mockup

 

BOTTOM TAGLINE: “Ask questions in plain English, get accurate answers with page references”

 

—

 

INFOGRAPHIC 2/6: “Document Processing – Steps 1 & 2”

 

TITLE: “Phase 1: Document Preparation”

SUBTITLE: “Breaking down your PDF for AI processing”

 

VISUAL FLOW (Top to Bottom):

 

STEP 1: “Upload Your Document”

– Icon: Hand holding/uploading a PDF file

-Visual:PDFfileflyingintoacloudorsystem

-Text:”SimplyprovideyourPDF-anysize,anylanguage”

-Statsbadge:”Supportsmulti-pagedocuments”

 

↓ (Flowing arrow)

 

STEP 2: “Intelligent Extraction”

– Icon: PDF exploding/splitting into components

– Visual: One PDF becoming:

• Individual pages (shown as small thumbnails)

• Extracted images (photo icons)

• Text content (document lines)

– Text: “The system separates your document into processable pieces”

– Small labels on extracted items: “Pages”, “Images”, “Content”

 

BOTTOM SECTION: “What Happens Behind the Scenes”

– Small icon boxes showing:

• “Each page isolated” (page icon)

• “Images preserved” (image icon)

• “Structure maintained” (layout icon)

 

—

 

INFOGRAPHIC 3/6: “AI Intelligence – Steps 3 & 4”

 

TITLE: “Phase 2: AI Understanding”

SUBTITLE: “Teaching AI to read like a human”

 

VISUAL FLOW (Left to Right):

 

STEP 3: “Azure AI Reads Everything”

-Icon:AIrobot/brainwitheyesscanningadocument

– Visual: Document with highlighted sections (paragraphs, tables, charts)

– Text: “Advanced AI identifies and understands:”

-Bulletbadges:

• “Paragraphs” (P badge)

• “Tables” (T badge with grid)

• “Figures & Charts” (F badge with graph)

– Tech badge: “Powered by Azure Document Intelligence”

 

↓ (Transformation arrow)

 

STEP 4: “Smart Organization”

-Icon:Organizedfilingsystemorlabeledboxes

-Visual:Documentcontentsortedintothreecolor-codedcategories:

• BLUE boxes: “Paragraphs” (showing text lines)

• GREEN boxes: “Tables”(showinggridstructure)

• PURPLE boxes: “Figures”(showingcharticon)

-Text:”Contentorganizedintomeaningful,searchablesections”

-Eachboxlabeledwithpagenumbertags

 

BOTTOM CALLOUT BOX:

“Why This Matters: Like a librarian who knows exactly where every piece of information lives”

 

—

 

DESIGN SPECIFICATIONS:

– Color palette: Blues, greens, purples (Microsoft Azure brand compatible)

– Style: Modern, minimalist, professional

– Icons: Simple, universally understood

– Typography: Large, readable fonts for presentation slides

– Arrows: Smooth, flowing connections between steps

– Include subtle shadows or depth effects

– Use 2-3 primary colors maximum per infographic

– Number each as X/6 to show series progression

Create a presentation series showing how a PDF becomes an AI-powered Q&A system. This is Part 2 containing infographics 4-6. Use modern, clean design with blues, greens, and purples. Professional and minimalist style suitable for business presentations.

 

—

 

INFOGRAPHIC 4/6: “Search Intelligence – Steps 5 & 6”

 

TITLE: “Phase 3: Creating Search Intelligence”

SUBTITLE: “Making your document searchable by meaning, not just keywords”

 

VISUAL FLOW (Top to Bottom with Side-by-Side Comparison):

 

STEP 5: “Build Your Document Library”

– Icon: Modern search index/database with document inside

– Visual: All chunks flowing into organized library structure

-Text:”Adedicatedsearchindexcreatedforyourdocument”

– Feature badges:

• “Fast retrieval” (lightning icon)

• “Organized storage” (filing icon)

• “Isolated & secure” (lock icon)

 

↓ (Processing arrow)

 

STEP 6: “AI Language Translation”

 

LEFT SIDE:

– Label: “Traditional Search”

– Icon: Text with exact word matching

– Example: “cat” matches “cat” only

– Visual: Simple text matching with = sign

– Text: “Keyword matching only”

 

VS. (versus indicator in center)

 

RIGHT SIDE:

– Label: “AI-Powered Search”

– Icon: Brain/neural network pattern

– Example: “cat”matches”feline”,”kitten”,”pet”

– Visual: Text transforming into glowing neural network vectors

– Text: “Understands meaning & context”

– Tech detail: “3,072-dimension understanding”

 

BOTTOM EXPLANATION BOX:

“Each section is converted into a unique ‘AI fingerprint’ that captures its meaning, enabling smart semantic search”

 

—

 

INFOGRAPHIC 5/6: “Question Answering – Step 7 + Chat Flow”

 

TITLE: “Phase 4: Your Document Answers Questions”

SUBTITLE: “Ask anything in natural language”

 

VISUAL FLOW (Left-to-Right):

 

STARTING POINT: “User Asks a Question”

– Icon: Person with speech bubble

– Example question: “What are the main findings about customer satisfaction?”

– Visual: Chat interface mockup

 

↓

 

STEP 1: “Smart Search”

– Icon: Magnifying glass with AI sparkles

– Text: “AI finds the most relevant sections”

-Visual:Searchbeamshighlightingspecificchunksintheindex

-Badge:”Semanticsearch-understandscontext”

 

↓

 

STEP 2: “Context Assembly”

– Icon: Puzzle pieces coming together

-Text:”Relevantinformationgatheredfromacrossthedocument”

– Visual: Multiple chunks (from different pages) assembling

-Showpagenumbers:”Page3,Page7,Page12″

 

↓

 

STEP 3: “AI Generates Answer”

-Icon:AIbrainwriting/generatingtext

– Text: “Azure OpenAI creates a clear, accurate answer”

– Visual: Answer being written with context sources

 

↓

 

FINAL OUTPUT: “Smart Answer Delivered”

-Icon:Chatbubblewithcheckmark

-Visual:Cleananswercardshowing:

• “Answer: [example answer text]”

• “Sources: Pages 3, 7, 12”

• “Confidence: 94%”

• “Language: Auto-detected”

– Badge: “Includes page references for verification”

 

BOTTOM FEATURE HIGHLIGHTS (Icon Row):

• “Multi-language support” (globe icon)

• “Source citations” (bookmark icon)

• “Confidence scores” (meter icon)

• “Instant responses” (lightning icon)

 

—

 

INFOGRAPHIC 6/6: “Technical Architecture”

 

TITLE: “Powered by Microsoft Azure AI”

SUBTITLE: “Enterprise-grade AI infrastructure”

 

LAYOUT: Hub-and-spoke architecture

 

CENTER: “Your PDF Document”(hubicon)

 

SURROUNDING SERVICES (spokes with icons and descriptions):

 

1. “Azure Document Intelligence”

– Icon: Document with AI chip

– Description: “Reads and understands document structure”

– Badge: “99%+ accuracy”

 

2. “Azure OpenAI”

– Icon: Brain/neural network

– Description: “Creates embeddings and generates answers”

– Badge: “GPT-4 powered”

 

3. “Azure AI Search”

– Icon: Search database

– Description: “Vector search with HNSW algorithm”

– Badge: “Millisecond response”

 

4. “FastAPI Backend”

– Icon: Server/API

– Description: “Orchestrates the entire pipeline”

– Badge: “REST API”

 

BOTTOM LAYER: “Security & Compliance”

– Icon row: Shield, Lock, Checkmark

-Text:”Enterprisesecurity•Dataprivacy•Scalableinfrastructure”

 

STATS PANEL (Side or Bottom):

– “3,072 dimensions” (embedding size)

– “Sub-second search” (speed)

– “Multi-language” (capability)

– “Page-level tracking” (precision)

 

—

 

DESIGN SPECIFICATIONS:

– Color palette: Blues, greens, purples (Microsoft Azure brand compatible)

– Style: Modern, minimalist, professional

– Icons: Simple, universally understood

– Typography: Large, readable fonts for presentation slides

– Arrows: Smooth, flowing connections between steps

– Include subtle shadows or depth effects

– Use 2-3 primary colors maximum per infographic

– Number each as X/6 to show series progression

Conclusion

By combining code understanding, structured reasoning, and visual explanation, this workflow transforms slide creation into a systematic and scalable process.

Instead of struggling to explain complex code manually, you can let LLMs help uncover the logic and communicate it clearly.

This method is especially useful for:
– Algorithm explanations
– Machine learning models
– System design presentations
– Educational and internal knowledge sharing

References