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CloudThinker’s five AI agents replace the fragmented stack of cloud management tools with specialized experts that communicate, coordinate, and act on your behalf. Each agent has deep domain expertise, persistent memory of your environment, and access to the tools it needs to get work done.

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The Agent Team

AgentRoleWhen to Use
AlexCloud EngineerCost analysis, infrastructure optimization, multi-cloud architecture, reserved capacity
OliverSecurity ProfessionalCompliance audits, vulnerability assessment, IAM reviews, threat detection
TonyDatabase AdministratorQuery optimization, performance tuning, index recommendations, capacity planning
KaiKubernetes AdministratorCluster health, pod right-sizing, autoscaling, RBAC audits, troubleshooting
AnnaTechnology LeaderMulti-agent coordination, cross-domain projects, executive reporting

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Choosing the Right Agent

NeedUse
Cloud cost is too high@alex
Security audit or compliance report@oliver
Database is slow@tony
Kubernetes cluster issues@kai
Problem spans multiple domains@anna
Don’t know where to start@anna

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Quick Reference: Prompt Patterns

# Single agent — cost analysis
@alex identify EC2 instances with <20% CPU over 30 days

# Single agent — security
@oliver audit security groups for public access on ports 22, 3306, 5432

# Single agent — database
@tony analyze slow queries on production PostgreSQL

# Single agent — Kubernetes
@kai check pod resource utilization in the payments namespace

# Multi-agent — coordinated by Anna
@anna coordinate quarterly infrastructure review:
  - @alex: cost trends and savings opportunities
  - @oliver: security posture and compliance gaps
  - @tony: database performance health
  - @kai: Kubernetes efficiency

# Multi-agent — incident investigation
@anna parallel investigation:
  @alex check infrastructure and load balancers
  @tony analyze database performance
  @kai review pod health and networking

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How Agents Work

1

Receive your prompt

You mention an agent with @agent and describe what you need in natural language. Add #tool to specify the output format (dashboard, report, recommendations, alert).
2

Access your connections

The agent reads your connected infrastructure — AWS, GCP, Azure, Kubernetes clusters, databases — using the read-access credentials you’ve configured.
3

Analyze with context

Agents correlate data across multiple sources. Alex cross-references CloudWatch utilization with Cost Explorer data. Oliver maps IAM policies against security group configurations. Tony reads execution plans alongside query frequency.
4

Generate output

Results are delivered in the format you requested — interactive dashboards, detailed reports, prioritized recommendations, or configured alerts.
5

Act with approval

If you need implementation, agents propose specific changes and wait for your approval before executing. All actions are logged with an audit trail.

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Agent Autonomy Levels

You control how independently agents operate. Each level is configurable per agent:
LevelModeWhat Happens
L1 — NotifyReport onlyAgent surfaces findings, takes no action
L2 — SuggestRecommendAgent creates actionable recommendations for your review
L3 — ApproveAct with confirmationAgent proposes specific changes and waits for approval
L4 — AutonomousSelf-directedAgent implements approved operations automatically

Configure Agent Autonomy

Set approval requirements per agent and per tool type

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Memory and Context

Each agent maintains persistent memory of your environment:
  • Episodic memory: remembers past analyses and decisions (e.g., which resources you’ve chosen to exempt from recommendations)
  • Working memory: carries context within a conversation thread
  • Semantic memory: stores patterns learned about your infrastructure over time
  • File memory: retains documents, runbooks, and knowledge base entries
This means agents get more accurate and useful over time as they learn your environment.

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Connection Requirements

Agents activate as you add the relevant connections:
AgentActivates When
AnnaAlways available — no connections required
AlexAWS, GCP, or Azure connection added
OliverAWS, GCP, or Azure connection added
TonyPostgreSQL, MySQL, or other database connection added
KaiKubernetes cluster connection added

Set Up Connections

Connect your cloud providers, databases, and Kubernetes clusters

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What’s Next

Alex — Cloud Engineer

Cost optimization, infrastructure analysis, multi-cloud

Oliver — Security

Compliance, vulnerability assessment, IAM, threat detection

Tony — Database

Query optimization, performance tuning, analytics

Kai — Kubernetes

Cluster management, workload optimization, troubleshooting

Anna — Coordinator

Multi-agent coordination, executive reporting, complex ops

CloudThinker Language

Complete @agent #tool syntax reference