Use Cases by Role
Real problems, real solutions. See how ACE3 helps each role on your team.
The Problem:
CI/CD pipelines are complex. GCP Workload Identity, Secret Manager, multi-environment deployments - it takes days to set up, and the knowledge is lost when you start the next project.
The Solution:
Store complete CI/CD patterns in ACE3. GitHub Actions workflows, GCP configurations, troubleshooting steps - all searchable. Next project? Query ACE3 and have your pipeline running in hours, not days.
What We Store:
- Complete CI/CD setup guide (GitHub Actions + GCP)
- Secrets management with Workload Identity Federation
- Terraform multi-environment patterns
- AWS cost optimization strategies
Full CI/CD knowledge transfers between projects. No more starting from scratch.
The Problem:
UX research takes time. You investigate best practices for navigation, content hierarchy, page structure - then forget it all by the next project.
The Solution:
Store research findings as best practices in ACE3. Navigation patterns, content strategies, component guidelines. Any AI assistant can recall them instantly.
What We Store:
- SaaS website navigation best practices
- Solutions page structure guidelines
- Content hierarchy patterns
- Progressive disclosure principles
Design decisions backed by documented research. Consistent UX across projects.
The Problem:
Every project reinvents testing approaches. How should unit tests be structured? What's the component testing strategy? How do you organize API tests?
The Solution:
Store testing patterns and strategies in ACE3. Unit test organization, component testing approaches, API test structures, E2E patterns - all searchable for your next project.
What We Store:
- Unit test organization patterns
- Component testing strategies
- API testing approaches
- E2E test structure guidelines
Testing knowledge compounds. New projects start with proven patterns.
The Problem:
Why did we choose PostgreSQL over MongoDB? What's our API versioning strategy? Six months later, nobody remembers - and you make the same mistakes again.
The Solution:
Track every architecture decision in ACE3 with rationale, alternatives considered, and trade-offs. Store API patterns, database designs, security practices.
What We Store:
- Database architecture & multi-tenancy patterns
- API design (REST, rate limiting, pagination)
- Authentication & session management
- Performance optimization strategies
New team members understand why. Decisions don't get relitigated.
The Problem:
Turning requirements into actionable plans takes hours. Writing decisions, breaking down architecture, creating issues, linking everything together - it's tedious manual work.
The Solution:
Use AI Builder to generate complete plans from natural language. Describe what you want to build, get structured decisions, architecture, issues, and relationships - all linked in the knowledge graph.
What We Store:
- AI Builder generates plans from requirements
- Automatic decision + architecture + issue creation
- Knowledge graph relationships built automatically
- Templates for common project types
Hours of planning work done in minutes. Plans are structured and searchable.
The ACE3 Difference
What changes when your AI has persistent memory
- Start every conversation from scratch
- Repeat context across AI platforms
- Lose decisions between sessions
- No team knowledge sharing
- Context limited by token windows
- Vendor lock-in to one AI
- Perfect context in every conversation
- Use any AI with the same memory
- Automatic decision tracking
- Team-wide shared knowledge
- Unlimited context with semantic search
- Complete platform independence