# Pitch Email to VentureBeat
**To:** guestposts@venturebeat.com
**Subject:** Guest Post Pitch: How AI Agents Are Transforming AWS Cloud Operations
---
Hi Taryn,
I've been following your coverage of AI agents in the enterprise—particularly your recent piece on Atlassian, Intuit, and AWS planning for a world where agents call APIs. It aligns perfectly with something I've been building.
**The pitch:** A hands-on technical article about AWS Sage, an open-source tool that gives AI assistants like Claude intelligent access to AWS infrastructure. Instead of 15 separate MCP servers (AWS Labs' current approach), it provides one unified connection with cross-service intelligence—dependency mapping, impact analysis, and automated incident investigation.
**Why this matters for VentureBeat readers:**
- **Practical AI agent implementation**: Real code, real architecture decisions, not theoretical
- **Enterprise cloud operations**: The 97M monthly MCP SDK downloads show this space is exploding
- **AWS-specific insights**: Dependency mapping and impact analysis that prevents "delete the wrong thing" disasters
- **Open source**: MIT licensed, 145 tests, production-ready (github.com/arunsanna/aws-sage)
**The angle:** "The future of cloud management isn't about learning more commands—it's about asking better questions." Engineers are spending hours clicking through dashboards. AI agents that actually understand infrastructure relationships can compress 30-minute investigations into 30 seconds.
I have two versions ready:
1. **Technical deep-dive** (for practitioners): Architecture comparisons, code examples, safety systems
2. **Executive summary** (for decision-makers): Business value, ROI scenarios, adoption patterns
Both include original diagrams showing architecture comparisons, feature matrices, and workflow visualizations.
Happy to share a Google Doc draft or adjust the angle based on what resonates with your editorial calendar.
Best,
Arun Sanna
arun.sanna@outlook.com
github.com/arunsanna/aws-sage
---
**Attachments to prepare:**
- Google Doc version of article (editable, comments enabled)
- Featured image (2000x1000 recommended)
