# One-Shot Prompt

**Topic**: The Future of AI Agents
**Theme**: Neon Tech
**Generated**: 2026-04-05
**Model**: Claude claude-4.6-opus (via Cursor)

## Prompt

Write a complete Node.js ES module script (`generate.mjs`) using only the `pptxgenjs` package that generates a professional 15-slide presentation about "The Future of AI Agents" with a Neon Tech visual theme.

Theme specs — Neon Tech:
- Background: dark (#0D0D1A, #1A1A2E)
- Primary: electric cyan (#00E5FF)
- Secondary: magenta (#FF00E5)
- Accent: lime green (#76FF03)
- Text: white (#FFFFFF)
- Light text: light grey (#B0B0C0)
- Chart palette: cyan, magenta, lime, amber (#FFD600), coral (#FF6E40)

Typography: Arial throughout. Title 32pt bold, subtitle 20pt, body 14-16pt, footnotes 9pt.

No external images — all visuals are programmatic shapes, charts, and gradients. Every slide must include speaker notes with 2-3 talking points and a transition phrase.

### Slide-by-slide content:

1. **Title** — "The Future of AI Agents" / subtitle "From Automation to Autonomous Intelligence" / date April 2026 / "Prepared by Claude"
2. **Agenda** — 6 sections: landscape, market data, agent taxonomy, trends, risks, outlook
3. **Context: Why This Matters** — key stat: "87% of Fortune 500 companies plan to deploy AI agents by 2028" with supporting context about the shift from chatbots to autonomous multi-step agents
4. **Key Data Point** — "$47.1 billion" projected AI agent market by 2030 (CAGR 43.8%), large display number with supporting text
5. **Market Landscape** — bar chart: AI agent market by sector (Enterprise $14.2B, Healthcare $8.7B, Finance $7.3B, Manufacturing $6.1B, Retail $5.4B, Other $5.4B)
6. **Agent Taxonomy** — pie chart: agent types by deployment (Task Automation 35%, Conversational 25%, Decision Support 20%, Creative/Generative 12%, Autonomous Research 8%)
7. **Timeline** — milestones: 2022 ChatGPT launch, 2023 GPT-4 + plugins, 2024 multi-agent frameworks, 2025 enterprise agent platforms, 2026 autonomous agent networks, 2027 agent-to-agent economies
8. **Comparison Table** — comparing Single Agent vs Multi-Agent vs Swarm architectures across complexity, reliability, scalability, cost, and best use case
9. **Trend Analysis** — line chart: agent capability growth 2023-2027 across three series (task completion rate, autonomous decision accuracy, multi-step reasoning)
10. **Case Study** — a realistic enterprise deployment: "GlobalBank's Agent-First Strategy" — 340% ROI, 68% reduction in processing time, 12 agents handling loan origination
11. **Challenges & Risks** — colour-coded risk matrix: hallucination/reliability (high), security/prompt injection (high), regulatory compliance (medium), job displacement (medium), cost management (low-medium)
12. **Opportunities** — four opportunity cards: Agent Marketplaces, Vertical Agent Specialists, Agent Observability Tools, Human-Agent Collaboration Platforms
13. **Future Outlook** — 2027-2030 projections with three forecast scenarios (conservative, base, aggressive)
14. **Key Takeaways** — 5 numbered takeaways with icon-like circular shapes
15. **Thank You / Q&A** — closing with "Questions?" and subtle branding

### Data constants at top of script. All 15 slides fully coded — no truncation or placeholders.

## Notes

- Theme: Neon Tech — dark backgrounds with electric cyan/magenta accents
- All data is realistic but generated, not sourced from specific reports
- Shapes used for cards, timeline nodes, risk indicators, and icon placeholders
- How to run: `npm install pptxgenjs && node generate.mjs`
- Output: `presentation.pptx`