Studio Founder

Converting a Markdown Brief Into a Polished PPTX — With Charts

25 min vs 90 minDesign & Content4 min read

Converting a Markdown Brief Into a Polished PPTX — With Charts

Key Takeaway

Write your investor update in markdown, run one command, and get a branded PowerPoint deck with charts, proper layouts, and slide numbers.

The Problem

Every Monday at PyratzLabs, we send LP updates. Here's what that used to look like:

Write the update in a Google Doc (because that's where the thinking happens)
Open PowerPoint
Manually create 8-12 slides
Copy-paste text from the doc
Rebuild the metrics table as a chart (again)
Adjust fonts, alignment, colors (again)
Export as PDF
Total time: 90 minutes

Ninety minutes. Every week. For a document where the content takes 20 minutes to write and the formatting takes 70.

The formatting is the tax. And it's a regressive tax — the simpler the update, the more absurd it feels to spend an hour in PowerPoint making it look professional.

I write in markdown. My team writes in markdown. Our docs, our READMEs, our specs — all markdown. The only reason we touch PowerPoint is because LPs expect PowerPoint.

The Solution

Write the brief in markdown. Let the agent convert it to a branded PPTX with proper slide layouts, chart visualizations, and consistent formatting.

The input is a markdown file. The output is a .pptx file. The middle is python-pptx and a brand template.

The Process (with code/config snippets)

The markdown input follows a simple convention — headings become slides, code blocks with chart metadata become visualizations:

markdownShow code

---
template: pyratzlabs-brand
date: 2026-03-09
title: Weekly LP Update — Week 10
footer: PyratzLabs | Confidential
---

# Portfolio Performance

## AUM Summary

| Metric | This Week | Last Week | Delta |
|--------|-----------|-----------|-------|
| Total AUM | $4.2M | $4.1M | +2.4% |
| Active Positions | 12 | 11 | +1 |
| Cash Position | $380K | $420K | -9.5% |

## Returns by Strategy

\`\`\`chart
type: bar
title: "Weekly Returns by Strategy"
data:
  labels: ["DeFi Yield", "L2 Infra", "AI Tokens", "Stablecoins"]
  values: [3.2, -1.1, 5.8, 0.4]
  colors: ["#6366F1", "#6366F1", "#6366F1", "#6366F1"]
y_axis: "Return (%)"
\`\`\`

## Key Decisions This Week

- **Entered** Arbitrum ecosystem position (ARB + GMX)
- **Exited** Solana meme token basket (realized +12%)
- **Held** DeFi yield positions — stable returns

## Next Week Focus

1. Evaluate Ethereum restaking protocols
2. Rebalance AI token exposure post-earnings
3. Review Q1 performance for quarterly report

The conversion pipeline:

pythonShow code

# Simplified conversion logic
from pptx import Presentation
from pptx.util import Inches, Pt
from pptx.chart.data import CategoryChartData
from pptx.enum.chart import XL_CHART_TYPE

def markdown_to_pptx(md_path, output_path):
    # 1. Parse markdown into slide blocks
    slides = parse_markdown_slides(md_path)
    meta = extract_frontmatter(md_path)

    # 2. Load brand template
    prs = Presentation(f"templates/{meta['template']}.pptx")

    # 3. Add title slide
    add_title_slide(prs, meta['title'], meta['date'])

    # 4. Convert each section to a slide
    for slide_data in slides:
        if slide_data.has_chart:
            add_chart_slide(prs, slide_data)
        elif slide_data.has_table:
            add_table_slide(prs, slide_data)
        else:
            add_content_slide(prs, slide_data)

    # 5. Apply footer to all slides
    for slide in prs.slides:
        add_footer(slide, meta['footer'], meta['date'])

    prs.save(output_path)

def add_chart_slide(prs, slide_data):
    slide = prs.slides.add_slide(prs.slide_layouts[5])  # Blank layout

    # Title
    add_text_box(slide, slide_data.heading, Inches(0.5), Inches(0.3), Pt(24))

    # Chart
    chart_spec = slide_data.chart
    chart_data = CategoryChartData()
    chart_data.categories = chart_spec['data']['labels']
    chart_data.add_series('Values', chart_spec['data']['values'])

    chart_type_map = {
        'bar': XL_CHART_TYPE.COLUMN_CLUSTERED,
        'pie': XL_CHART_TYPE.PIE,
        'line': XL_CHART_TYPE.LINE,
    }

    chart = slide.shapes.add_chart(
        chart_type_map[chart_spec['type']],
        Inches(1), Inches(1.5), Inches(8), Inches(5),
        chart_data
    ).chart

    # Apply brand colors
    for i, point in enumerate(chart.series[0].points):
        point.format.fill.solid()
        point.format.fill.fore_color.rgb = RGBColor.from_string(
            chart_spec['data']['colors'][i].lstrip('#')
        )

The template system handles brand consistency:

View details

templates/
├── pyratzlabs-brand.pptx   # Master template with layouts
├── artificial-lab.pptx      # Product-specific template
└── minimal.pptx             # Clean, no-brand template

The Results

Metric	Manual PowerPoint	Markdown → PPTX
Total time (content + formatting)	90 minutes	25 minutes (20 writing + 5 conversion)
Formatting time only	70 minutes	0 (automated)
Brand consistency	Varies by week	100% (template-driven)
Chart accuracy	Manual entry (error-prone)	Data-driven (exact)
Version control	File_v3_final_FINAL.pptx	Git-tracked markdown
Reuse	Copy last week's deck, update	Write fresh, same template

We cut LP update production from 90 minutes to 25 minutes. Every week. That's over 50 hours per year recovered from PowerPoint formatting.

Try It Yourself

Write your content in markdown with the frontmatter convention shown above. Use chart code blocks for visualizations. The agent handles the rest — template application, chart rendering, table formatting, footer/header, and slide numbering.

Keep a templates/ folder with your branded .pptx masters. The agent applies your layouts, fonts, and colors automatically.

Start free on Mr.Chief →

Write where you think best. Deliver where they expect it. The format translation is the machine's job, not yours.

PowerPointmarkdownautomationinvestor update

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Studio Founder

Converting a Markdown Brief Into a Polished PPTX — With Charts

25 min vs 90 minDesign & Content4 min read

Converting a Markdown Brief Into a Polished PPTX — With Charts

Key Takeaway

Write your investor update in markdown, run one command, and get a branded PowerPoint deck with charts, proper layouts, and slide numbers.

The Problem

Every Monday at PyratzLabs, we send LP updates. Here's what that used to look like:

Write the update in a Google Doc (because that's where the thinking happens)
Open PowerPoint
Manually create 8-12 slides
Copy-paste text from the doc
Rebuild the metrics table as a chart (again)
Adjust fonts, alignment, colors (again)
Export as PDF
Total time: 90 minutes

Ninety minutes. Every week. For a document where the content takes 20 minutes to write and the formatting takes 70.

The formatting is the tax. And it's a regressive tax — the simpler the update, the more absurd it feels to spend an hour in PowerPoint making it look professional.

I write in markdown. My team writes in markdown. Our docs, our READMEs, our specs — all markdown. The only reason we touch PowerPoint is because LPs expect PowerPoint.

The Solution

Write the brief in markdown. Let the agent convert it to a branded PPTX with proper slide layouts, chart visualizations, and consistent formatting.

The input is a markdown file. The output is a .pptx file. The middle is python-pptx and a brand template.

The Process (with code/config snippets)

The markdown input follows a simple convention — headings become slides, code blocks with chart metadata become visualizations:

markdownShow code

---
template: pyratzlabs-brand
date: 2026-03-09
title: Weekly LP Update — Week 10
footer: PyratzLabs | Confidential
---

# Portfolio Performance

## AUM Summary

| Metric | This Week | Last Week | Delta |
|--------|-----------|-----------|-------|
| Total AUM | $4.2M | $4.1M | +2.4% |
| Active Positions | 12 | 11 | +1 |
| Cash Position | $380K | $420K | -9.5% |

## Returns by Strategy

\`\`\`chart
type: bar
title: "Weekly Returns by Strategy"
data:
  labels: ["DeFi Yield", "L2 Infra", "AI Tokens", "Stablecoins"]
  values: [3.2, -1.1, 5.8, 0.4]
  colors: ["#6366F1", "#6366F1", "#6366F1", "#6366F1"]
y_axis: "Return (%)"
\`\`\`

## Key Decisions This Week

- **Entered** Arbitrum ecosystem position (ARB + GMX)
- **Exited** Solana meme token basket (realized +12%)
- **Held** DeFi yield positions — stable returns

## Next Week Focus

1. Evaluate Ethereum restaking protocols
2. Rebalance AI token exposure post-earnings
3. Review Q1 performance for quarterly report

The conversion pipeline:

pythonShow code

# Simplified conversion logic
from pptx import Presentation
from pptx.util import Inches, Pt
from pptx.chart.data import CategoryChartData
from pptx.enum.chart import XL_CHART_TYPE

def markdown_to_pptx(md_path, output_path):
    # 1. Parse markdown into slide blocks
    slides = parse_markdown_slides(md_path)
    meta = extract_frontmatter(md_path)

    # 2. Load brand template
    prs = Presentation(f"templates/{meta['template']}.pptx")

    # 3. Add title slide
    add_title_slide(prs, meta['title'], meta['date'])

    # 4. Convert each section to a slide
    for slide_data in slides:
        if slide_data.has_chart:
            add_chart_slide(prs, slide_data)
        elif slide_data.has_table:
            add_table_slide(prs, slide_data)
        else:
            add_content_slide(prs, slide_data)

    # 5. Apply footer to all slides
    for slide in prs.slides:
        add_footer(slide, meta['footer'], meta['date'])

    prs.save(output_path)

def add_chart_slide(prs, slide_data):
    slide = prs.slides.add_slide(prs.slide_layouts[5])  # Blank layout

    # Title
    add_text_box(slide, slide_data.heading, Inches(0.5), Inches(0.3), Pt(24))

    # Chart
    chart_spec = slide_data.chart
    chart_data = CategoryChartData()
    chart_data.categories = chart_spec['data']['labels']
    chart_data.add_series('Values', chart_spec['data']['values'])

    chart_type_map = {
        'bar': XL_CHART_TYPE.COLUMN_CLUSTERED,
        'pie': XL_CHART_TYPE.PIE,
        'line': XL_CHART_TYPE.LINE,
    }

    chart = slide.shapes.add_chart(
        chart_type_map[chart_spec['type']],
        Inches(1), Inches(1.5), Inches(8), Inches(5),
        chart_data
    ).chart

    # Apply brand colors
    for i, point in enumerate(chart.series[0].points):
        point.format.fill.solid()
        point.format.fill.fore_color.rgb = RGBColor.from_string(
            chart_spec['data']['colors'][i].lstrip('#')
        )

The template system handles brand consistency:

View details

templates/
├── pyratzlabs-brand.pptx   # Master template with layouts
├── artificial-lab.pptx      # Product-specific template
└── minimal.pptx             # Clean, no-brand template

The Results

Metric	Manual PowerPoint	Markdown → PPTX
Total time (content + formatting)	90 minutes	25 minutes (20 writing + 5 conversion)
Formatting time only	70 minutes	0 (automated)
Brand consistency	Varies by week	100% (template-driven)
Chart accuracy	Manual entry (error-prone)	Data-driven (exact)
Version control	File_v3_final_FINAL.pptx	Git-tracked markdown
Reuse	Copy last week's deck, update	Write fresh, same template

We cut LP update production from 90 minutes to 25 minutes. Every week. That's over 50 hours per year recovered from PowerPoint formatting.

Try It Yourself

Keep a templates/ folder with your branded .pptx masters. The agent applies your layouts, fonts, and colors automatically.

Start free on Mr.Chief →

Write where you think best. Deliver where they expect it. The format translation is the machine's job, not yours.

PowerPointmarkdownautomationinvestor update

Related case studies

Studio Founder

Batch-Editing 50 Slides Across 3 Decks — In One Command

We updated fonts, colors, logos, and footer text across 50 slides in 3 different PowerPoint decks — in one batch command instead of opening each file manually.

50 slides in 2 min4 min read

Studio Founder

Extracting Data From 5 Investor Decks Into Structured JSON

Feed 5 competitor pitch decks to an AI agent and get structured JSON with every slide's text, tables, chart data, and images — 30 seconds per deck instead of 2 hours.

5 decks in 2.5 min vs 10 hrs5 min read

Studio Founder

Converting Our PowerPoint to an Interactive Web Presentation

We converted a static PowerPoint deck to an interactive web presentation with animated transitions, embedded video, and click-through interactions — resulting in 3x more engagement from investors.

3x more engagement4 min read

Want results like these?

Start free with your own AI team. No credit card required.

Start Free →Browse agents