cto.do
Autonomous CTO Agents That Run Engineering Operations
Deploy intelligent CTO agents that monitor production health, triage incidents, coordinate deployments, and manage engineering workflows autonomously. Execute complex operations with natural language commands.
import { CTO } from 'cto.do' // Daily engineering reviewsCTO.every.day($ => { const metrics = $.Analytics.query.ErrorRates({ since: '24h' }) if (metrics.errorRate > 0.01) { $.Slack.send.Alert({ channel: '#engineering', metrics }) $.Jira.create.Incident({ severity: 'high' }) }}) // React to production issuesCTO.on.Exception.in.Production($ => $.PagerDuty.create.Incident($))
Frequently asked questions
CTO agents make independent decisions based on configured thresholds and business rules, execute multi-step operational workflows, and adapt to changing production conditions without constant oversight. They monitor systems 24/7, triage incidents automatically, coordinate deployments, and escalate critical issues. Configure operational boundaries (e.g., never deploy on Fridays, always require approval for database migrations), set approval gates for high-stakes actions, and let agents handle routine engineering operations autonomously. Agents learn from historical incidents and improve decision-making accuracy over time.
CTO agents can monitor production health metrics across 100+ data points, analyze error patterns and anomaly detection, triage and route incidents to appropriate team members, coordinate deployment workflows with rollback capabilities, manage on-call schedules and escalations, review pull requests and code quality metrics, track sprint progress and velocity trends, generate executive reports and engineering KPIs, interact with teams via Slack/email/Jira, and orchestrate complex multi-system operations. They understand engineering semantics, interpret technical context, and execute tasks across your entire DevOps stack autonomously.
Set explicit operational boundaries via configuration (e.g., never auto-deploy to production, require approval for any database schema changes, only restart services during maintenance windows). Require human approval for high-stakes actions like deployments, database migrations, infrastructure changes, or spending over thresholds. Monitor all agent decisions in real-time dashboards with full audit logs showing reasoning chains. Agents operate within strictly defined constraints and automatically escalate edge cases or ambiguous situations. Dry-run mode lets you test agent behavior safely before enabling live operations. Full rollback capabilities with one-click revert for any agent action.
Yes. CTO agents communicate via semantic protocols and delegate tasks to specialist agents using $.Agent.delegate.Task patterns. For example, a CTO agent delegates deployment tasks to DevOps agents, code review to QA agents, and performance analysis to SRE agents. Build multi-agent systems where each agent handles their domain expertise—CTO provides strategic oversight while specialist agents execute tactical operations. Agents negotiate priorities, resolve conflicts autonomously, and maintain shared context across the organization.
Choose from GPT-4 Turbo, Claude Sonnet 4.5, Gemini 2.0 Pro, Llama 4, or bring your own models via API. CTO agents intelligently route tasks to the best model for each operation based on cost (<$0.01 per task), latency requirements (streaming responses in <100ms), and capability needs (code analysis vs natural language understanding). Automatic fallbacks ensure reliability if primary models are unavailable. Streaming responses for real-time monitoring and cost optimization with intelligent prompt caching reduce costs by 80% for repeated operations.