Open knowledge platform

Built Together

StackAhead.ai is an open knowledge platform. Submit your architecture for expert review, contribute guest posts, or share case studies — all editorially reviewed by Sandeep Reddy Kaidhapuram.

Ways to Participate

Multiple paths to contribute, learn, and grow with the community.

Contribute Patterns

Share your architecture patterns, implementation guides, and lessons learned. Published under your name with full attribution.

Architecture Reviews

Submit your agentic architecture for expert review and structured feedback from our Editor-in-Chief.

Case Studies

Document how your organization is implementing agentic systems. Anonymous submissions accepted.

Weekly Stack Signal

Our curated newsletter covering protocol updates, framework releases, governance developments, and community highlights.

Architecture Reviews

Expert architecture review

Submit your agentic architecture for a detailed expert review by Sandeep Reddy Kaidhapuram. Each submission receives a structured evaluation covering patterns, security, governance, scalability, and actionable recommendations.

1

Submit Your Architecture

Send your architecture diagrams, design documents, and context via email. Include system scope, agent roles, data flows, and any specific concerns.

2

Editorial Review

Sandeep Reddy Kaidhapuram personally reviews each submission, evaluating architecture patterns, security posture, governance compliance, and scalability.

3

Detailed Feedback Report

Receive a structured review with findings, risk assessment, recommendations, and suggested improvements — delivered within 2 weeks.

4

Publication (Optional)

Exemplary architectures are featured on StackAhead.ai as case studies with full attribution, showcasing innovative patterns to the community.

Recent Reviews

Examples of architecture reviews conducted by the Editor-in-Chief.

Approved with RecommendationsInsurance · Submitted by Enterprise Architecture Team

Multi-Agent RAG Pipeline for Insurance Claims

Reviewed a multi-agent RAG pipeline designed for automated insurance claims processing. The architecture used a supervisor-worker pattern with four specialized agents handling document ingestion, policy matching, fraud detection, and settlement calculation.

Review Findings & Recommendations
  • Strong separation of concerns across agent responsibilities
  • Missing circuit breaker between fraud detection agent and downstream settlement agent
  • Recommended adding a human-in-the-loop checkpoint before settlements exceeding $50K
  • Suggested replacing synchronous agent-to-agent calls with event-driven messaging for resilience
Multi-AgentRAGInsuranceSupervisor-Worker
ApprovedHealthcare · Submitted by Health IT Solutions Team

MCP-Based Healthcare Data Exchange Architecture

Evaluated an MCP-based architecture for exchanging patient data between EHR systems, payer APIs, and AI diagnostic agents. The design leveraged MCP servers to expose FHIR resources as agent-consumable tools.

Review Findings & Recommendations
  • Excellent use of MCP server abstraction to normalize heterogeneous FHIR endpoints
  • PHI access controls were well-implemented with dynamic scoping per agent session
  • Recommended adding audit logging at the MCP transport layer for HIPAA compliance
  • Suggested implementing agent identity propagation to maintain chain-of-custody for PHI access
MCPHealthcareFHIRHIPAA
Revisions RequestedRetail · Submitted by Digital Transformation Team

Agentic Customer Service Platform with LangGraph

Assessed a LangGraph-based customer service platform with agents for order tracking, returns processing, product recommendations, and escalation routing. The architecture handled 50K+ daily interactions.

Review Findings & Recommendations
  • Good use of LangGraph state machines for conversation flow management
  • Agent memory management lacked TTL policies — risk of context window overflow at scale
  • Escalation routing relied solely on sentiment analysis; recommended adding business rule triggers
  • Missing observability layer — suggested integrating LangSmith or custom tracing for agent decision auditing
LangGraphCustomer ServiceRetailObservability
Guest Post Submissions

Write for StackAhead.ai

We accept guest contributions from architects, engineers, and researchers working on agentic systems. Every submission is personally reviewed by Editor-in-Chief Sandeep Reddy Kaidhapuram for technical accuracy, originality, and architectural rigor.

Sandeep Reddy Kaidhapuram

Editor-in-Chief

Principal Specialist Solution Engineer at Salesforce. Published author in IJCT, IRJMETS, and Amazon Kindle. Speaker at Dreamforce, Salesforce World Tour, and HIMSS. Every guest submission is personally evaluated against StackAhead.ai's editorial standards before publication.

1

Submit a Proposal

Email a 200-word abstract with your proposed topic, key takeaways, and your background. We prioritize original technical content with architecture depth.

2

Editorial Review by Editor-in-Chief

Sandeep Reddy Kaidhapuram, Editor-in-Chief, reviews every submission for technical accuracy, originality, architectural rigor, and alignment with the platform's standards.

3

Feedback & Revision

Receive detailed editorial feedback. We work collaboratively to strengthen the piece — improving clarity, adding diagrams, and ensuring technical precision.

4

Publication with Attribution

Approved posts are published under your name with full byline, bio, and links. Featured on the StackAhead.ai blog and promoted across our channels.

Editorial Standards

What we look for in every submission. These standards are enforced by the Editor-in-Chief.

Technical Accuracy

All claims must be substantiated. We verify protocol specifications, framework behavior, and architectural trade-offs.

Vendor Neutrality

Mention tools and platforms, but don't pitch. Content must serve the reader, not a sales agenda.

Real-World Grounding

We favor patterns from real implementations over theoretical exercises. Show what you've built or deployed.

Visual Architecture

Diagrams, decision matrices, and flow charts are strongly preferred. Architecture is visual by nature.

Honest Trade-offs

No silver bullets. Every pattern has limitations — acknowledge them. This is what separates thought leadership from marketing.

Actionable Guidance

Readers should leave with something they can apply. Include implementation hints, code snippets, or decision frameworks.

Who this is for

Whether you're building, governing, or evangelizing agentic systems — there's a place for you here.

Enterprise Architects
Designing agentic systems
Platform Engineers
Building agent infrastructure
Security Architects
Tackling agent governance
Developer Advocates
Exploring new protocols
CTOs
Evaluating agentic transformation
Researchers
Pushing multi-agent capabilities