AI Agents
Cursor for DevOps
A coordinated system of specialized AI agents, each mastering a specific domain of DevOps operations. From pipeline troubleshooting to database provisioning—expert-level assistance on every screen, 24/7.
Planton
Cloud
Pipeline
AWS RDS
K8s
Database
Security
Drift
Logs
Compliance
19+
Specialized Agents
10x
Faster Resolution
24/7
Always Available
The Journey to Agents
From a single copilot dream to a specialized fleet of DevOps experts. Here's how we evolved our thinking.
2023 - Early 2024
The Single Copilot Vision
Started with a ChatGPT-style interface—a single AI copilot handling all DevOps requests through natural language.
The Problem
DevOps is too broad. Pipelines, databases, Kubernetes, security—different domains with different tools. One AI couldn't master it all.
Mid 2024
The Realization
A single generalist AI becomes mediocre at everything. Knowledge buried in the copilot. DevOps engineers struggled to identify the right use cases.
The Insight
If DevOps requires a team of specialists, why expect a single AI to handle it all?
Late 2024
The Pivot to Microagents
Power is in specialization. Create micro agents for specific tasks—Tekton pipelines, AWS RDS, Kubernetes troubleshooting.
Achievement
Made agent creation incredibly simple: instructions + MCP tools + backend. No boilerplate.
Q4 2024
Graphton Framework
Built a declarative framework for agent creation. 3-10 lines of code instead of 100+ with raw LangGraph.
Key Features
Automatic MCP authentication, loop detection, prompt enhancement. Production-ready agents in minutes.
Current
Context-Aware Integration
Agents embedded in specific screens—not a separate copilot interface. Full context, automatically.
Benefit
Users stay in workflow. No context switching. Agent knows exactly what you're working on.
Vision
Autonomous Future
Agents by nature are autonomous—small units of work that can be scheduled and rerun automatically.
The Vision
Continuous optimization. Self-healing infrastructure. DevOps that improves itself overnight.
The Problem We Solve
DevOps doesn't need a single superhero. It needs a team of specialists who are always available.
X
Traditional DevOps
Single overworked DevOps team handling hundreds of requests
Ticket queues and 3-5 day delays for simple infrastructure needs
Constant context switching between pipelines, databases, clusters
Knowledge siloed in a few senior engineers' heads
Developers blocked waiting for infrastructure approval
2 AM wake-up calls when pipelines fail
The Bottleneck
No matter how talented your DevOps team, they can't scale linearly. Every new developer, service, and environment adds to the queue.
*
With Agents
+
Specialized AI agents available 24/7, no tickets, no queues
+
Instant responses—databases in 20 minutes, not 3 days
+
Each agent is an expert in its specific domain
+
Knowledge democratized—every developer has access
+
Developers self-serve infrastructure without leaving workflow
+
Pipeline failures diagnosed and fixed in minutes, autonomously
The Multiplier
Agents scale infinitely. Every developer gets instant access to specialized DevOps expertise, without adding headcount.
The Technology Behind It
We didn't reinvent the wheel. We built on proven foundations and added AI magic—just like Cursor did.
The Cursor Analogy
Cursor didn't build a code editor from scratch. It forked VS Code and added AI magic.
E
VS Code Foundation
File system management
Syntax highlighting
Extension ecosystem
Decades of UX refinement
*
Cursor's AI Layer
Code completion
Natural language edits
Codebase understanding
10x developer productivity
Same Playbook for DevOps
Agent Fleet builds AI on top of Planton Cloud's battle-tested platform.
P
Planton Cloud Foundation
150+ deployment components
Multi-cloud infrastructure APIs
InfraHub and ServiceHub
Standardized validation
A
Agent Fleet AI Layer
Specialized domain agents
Context-aware integration
Graphton framework
10x faster infrastructure
The Secret Sauce
Graphton Framework
Declarative agent creation. 3-10 lines instead of 100+.
tekton_pipeline_agent.py
agent = create_deep_agent(
# Model selection
model="claude-sonnet-4.5",
# Agent instructions
system_prompt="""You troubleshoot Tekton pipelines,
analyze build logs, and suggest fixes...""",
# MCP tools for Planton Cloud integration
mcp_tools={
"planton-cloud": [
"get_pipeline_logs",
"analyze_failure",
"update_pipeline_config"
]
},
# Sandbox backend for CLI commands
backend="daytona",
)You Provide
Graphton Handles
3-10
Lines of code
Minutes
To production-ready
Zero
Boilerplate code
Meet the Fleet
Each agent is a specialist with deep expertise in its domain. Available 24/7, never forgets, always improving.
Tekton Pipeline Manager
Creates, troubleshoots, and modifies CI/CD pipelines
Capabilities
Analyzes build logs and identifies root causes
Suggests and applies fixes automatically
Optimizes pipeline performance
Handles Docker and Kubernetes deployments
AWS RDS Agent
Provisions production-ready databases
Capabilities
Security hardening and best practices
Multi-AZ setup for high availability
Backup and recovery configuration
Performance tuning recommendations
Kubernetes Troubleshooter
Diagnoses pod scheduling and cluster issues
Capabilities
Resource optimization and limits
Network debugging and DNS resolution
PVC and storage troubleshooting
Cluster autoscaling configuration
Database Performance Tuner
Query optimization and database tuning
Capabilities
Slow query analysis and optimization
Index recommendations
Connection pooling configuration
Query plan analysis and improvements
Security Hardening Agent
Configuration audits and compliance
Capabilities
SOC2 and HIPAA compliance checks
Secret rotation automation
IAM policy optimization
Security group and firewall rules
Infrastructure Drift Detector
Detects drift between desired and actual state
Capabilities
Continuous drift monitoring
Recommends reconciliation actions
Automated drift remediation
Change tracking and audit logs
And that's just the beginning...
We're continuously adding specialized agents for Helm charts, container security, log analysis, metrics, compliance, and more. Have a specific need? Create your own custom agent in minutes.
Before & After
Real scenarios that show how agents transform time-consuming DevOps tasks into instant solutions.
!
Pipeline Failure at 2 AM
Before
2-4 hours
1
Pipeline fails, pager wakes DevOps engineer
2
Engineer logs in, starts debugging logs
3
Scrolls through cryptic error messages
4
Googles error codes, tries random fixes
5
After 2-4 hours, identifies Node version mismatch
6
Updates Dockerfile, pushes fix
Outcome: Exhausted engineer, delayed deployment
With Agent
15 minutes
1
Pipeline fails, agent automatically triggered
2
Agent analyzes Tekton task logs in seconds
3
Identifies root cause: Node 16 vs Node 18
4
Suggests Dockerfile update with exact changes
5
Developer approves fix
6
Pipeline re-runs successfully
Outcome: Problem solved autonomously
2-4 hours
->
15 minutes
D
Need Production Database
Before
3-5 days
1
Developer submits ticket to DevOps
2
Ticket sits in queue for 1-2 days
3
DevOps researches instance types, security
4
Writes Terraform, tests in staging
5
Reviews encryption, backups, IAM
6
Deploys, hands credentials back
Outcome: Developer blocked, delivery delayed
With Agent
20 minutes
1
"I need PostgreSQL for payments, ~1000 TPS"
2
Agent identifies optimal instance (db.r6g.large)
3
Configures Multi-AZ, encryption, backups
4
Sets up security groups automatically
5
Generates Planton Cloud manifest
6
Developer approves, deployment executes
Outcome: Production-ready with best practices
3-5 days
->
20 minutes
K
Pod Failing to Schedule
Before
3-6 hours
1
Pod stuck in Pending, app won't start
2
Developer escalates to DevOps team
3
DevOps runs kubectl describe pod
4
Investigates resources, node selectors
5
Hours debugging cluster state
6
Identifies: memory request > capacity
Outcome: Deployment blocked, team frustrated
With Agent
10 minutes
1
Developer clicks "Troubleshoot" in dashboard
2
Agent analyzes pod spec and cluster state
3
Identifies: memory request (8Gi) > available
4
Recommends: reduce to 4Gi or add nodes
5
Developer adjusts request
6
Pod schedules immediately
Outcome: Problem diagnosed instantly
3-6 hours
->
10 minutes
The Vision: Where We're Going
This is just the beginning. Agents are evolving into an autonomous DevOps system.
@
Current Focus
Context-Aware Agents
Agents embedded exactly where you need them—not a separate copilot screen you have to switch to.
How It Works
+
Click "Pipeline Manager" in your Service screen
+
Agent receives full context automatically
+
No manual copying of URLs or IDs
+
Agent starts with complete information
The Benefit
+
Users stay in their workflow
+
No screen switching or context loss
+
Faster, more accurate assistance
+
Seamless UX integration
A
Next Step
Autonomous Agents
Agents by nature are autonomous—small units of work that can be scheduled, monitored, and rerun automatically.
Scheduled Execution
Drift detection nightly, security audits weekly, optimization monthly
Continuous Optimization
Improve database indexes, container resources, cache hit rates
Self-Healing Systems
Detect, diagnose, and fix routine issues without human intervention
+
Future
Expandable Fleet
Create new specialized agents as needs emerge. Your organization's unique workflows become automated expertise.
Organization-Specific Agents
Build agents that understand your deployment patterns, compliance requirements, and tooling
Custom Workflow Automation
Agent that handles your Friday deployment freeze, or your security review workflow
Agent Marketplace
Share agents with the community. Discover agents built by others. A GitHub Actions marketplace for DevOps agents.
Ready to Transform Your DevOps?
Join organizations using specialized AI agents to accelerate infrastructure work, eliminate bottlenecks, and democratize DevOps expertise.
19+
Specialized Agents
10x
Faster Resolution
24/7
Always Available
Want to build your own agents?
Explore Graphton Framework ->Questions about Agents?
Contact Our Team ->
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