Generative AI and Agentic AI for Solution Architects

Objective: Build autonomous agents that validate solutions and optimize architectures.

SOLUTION VALIDATION AGENTS

Content

Solution Architecture Validation Agent

• Trigger: Architecture document uploaded
• What it does:
  1. Review architecture against best practices
  2. Identify single points of failure
  3. Assess security posture
  4. Validate scalability assumptions
  5. Generate risk assessment
  6. Recommend improvements

Outcome: Architecture validated before proposal

Hands-on Lab

• Deploy validation agent
• Upload your architecture
• Review recommendations

COST OPTIMIZATION & RISK ANALYSIS

Content

Cost Optimization Agent

• Trigger: Architecture defined
• What it does:
  1. Analyze infrastructure costs
  2. Identify optimization opportunities
  3. Compare vendor pricing
  4. Generate cost model (TCO)
  5. Calculate ROI scenarios
  6. Create financial business case

Outcome: Data-driven financial recommendations

Risk Analysis Agent

• Trigger: Architecture review
• What it does:
  1. Identify technical risks
  2. Assess compliance requirements
  3. Evaluate vendor lock-in risks
  4. Score risks by severity
  5. Generate mitigation strategies
  6. Create risk register

Outcome: Comprehensive risk assessment ready for stakeholders

Hands-on Lab

• Deploy cost optimization agent
• Generate TCO model
• Create risk register

Objective: Integrate agents with stakeholder management and proposal tools.

EXECUTIVE PRESENTATION AUTOMATION 

Content

Executive Summary Generator

• Trigger: Architecture + financials defined
• What it does:
  1. Create executive summary
  2. Build business case
  3. Generate timeline
  4. Develop success metrics
  5. Create presentation outline
• Outcome: Ready-to-present materials

Hands-on Lab

• Generate executive summary
• Create presentation deck outline
• Build success metrics

STAKEHOLDER & VENDOR INTEGRATION

Content

Stakeholder Management Agent

• Integrate with: Email, Slack, Jira
• What it does:
  1. Track stakeholder requirements
  2. Manage RFP responses
  3. Update architecture based on feedback
  4. Generate status reports
  5. Notify stakeholders of changes
• Outcome: Automated stakeholder communication

Proposal Generation Agent

• What it does:
  1. Combine all components (architecture, financials, risks)
  2. Generate professional proposal document
  3. Create appendices and supporting docs
  4. Format for client presentation
• Outcome: Complete proposal ready to send

Hands-on Lab

• Connect stakeholder management
• Generate complete proposal
• Set up multi-stakeholder communication

Objective: Build complete solution for a real engagement.

PROJECT DESIGN

Requirements

• Real client engagement or opportunity
• Uses ≥2 agents (validation + optimization, or costing + risk)
• Generates client-ready deliverables
• Deployable by end of day

Example Projects

Complete Solution Proposal

• Input: Client requirements + opportunity
• Process: Gen AI requirements → Agent validation → Costing → Risk → Proposal
• Output: Professional proposal ready to send to client
• Impact: Reduce proposal time from 40 hours to 8 hours

Architecture Review & Optimization

• Input: Existing architecture
• Process: Validation agent → Cost agent → Risk agent
• Output: Optimization recommendations + business case
• Impact: Improve existing solutions before delivery

Multi-Vendor Evaluation & Selection

• Input: RFP + vendor options
• Process: Gen AI comparison → Validation → Cost analysis
• Output: Vendor selection recommendation with business case
• Impact: Data-driven vendor decisions

BUILD, TEST & DEPLOY 

Hands-on

• Step 1: Code & Setup
• Step 2: Generate Deliverables 
• Step 3: Deploy
• Step 4: Present 

Deliverables

• Complete solution proposal
• Architecture documentation
• Financial model and ROI
• Risk assessment
• Client presentation