AI Dev Command
Your AI product manager, from feedback to deployment
An autonomous AI product manager for software teams that listens to feedback from WhatsApp, Telegram, Slack, and email, understands reported issues and feature requests, searches your codebase for context, creates GitHub issues, analyzes team capabilities from commit history, assigns tasks to the best-suited developer, reviews PRs, approves merges, and oversees the full DevOps pipeline to AWS -- end to end, without human bottlenecks.
Core Capabilities
Each capability is purpose-built to deliver measurable value across your operations.
Multi-Channel Feedback Ingestion
Listens to WhatsApp groups, Telegram channels, Slack threads, and email for bug reports, feature requests, and user feedback. AI classifies, deduplicates, and prioritizes incoming signals in real-time.
Listens to WhatsApp groups, Telegram channels, Slack threads, and email for bug reports, feature requests, and user feedback. AI classifies, deduplicates, and prioritizes incoming signals in real-time.
Converts raw feedback into structured GitHub issues with reproduction steps, severity classification, affected components, and relevant code references -- automatically searched from your codebase.
Analyzes every developer's commit history, PR contributions, and code areas of expertise to build skill profiles. Assigns issues to the engineer best suited for each task based on proven capability.
Reviews every pull request for bugs, security issues, architectural violations, and style consistency. Provides actionable feedback, tracks issue resolution across iterations, and approves when quality gates are met.
Full repository mapping with architecture analysis, dependency graphs, and pattern detection. When feedback arrives, AI searches the codebase to identify affected files and suggest implementation approaches.
Manages the full deployment lifecycle to AWS: Elastic Beanstalk, RDS, CloudFront, Route53, and more. Push-to-deploy with health monitoring, automatic rollback, and infrastructure scaling.
See It In Action
A quick walkthrough of AI Dev Command capabilities.
Real conversation examples with the AI agent
Quick walkthrough of CRM and platform connections
Overview of call metrics and insights
Industry Applications
Real-world applications across multiple industries and sectors.
Software Development Companies
Replace manual triage, assignment, and review workflows with an AI that handles the entire feedback-to-deployment pipeline autonomously.
- Automated triage
- Smart assignment
- Continuous deployment
Product Teams
Capture user feedback from every channel without missing signals. AI prioritizes based on frequency, severity, and business impact.
- Feedback aggregation
- Priority scoring
- Roadmap signals
Engineering Managers
Understand team capacity and strengths through data-driven skill profiles built from actual commit history, not self-reported surveys.
- Skill mapping
- Workload balancing
- Capacity planning
Startup CTOs
Run a full development operation with a small team. AI acts as PM, code reviewer, and DevOps engineer -- scaling your engineering output without scaling headcount.
- One-person PM
- Automated code review
- Self-managed infra
Agency & Consulting Firms
Manage multiple client projects with consistent code quality, automated deployments, and client-facing feedback channels that feed directly into development.
- Multi-project oversight
- Client feedback loops
- Quality gates
Open Source Maintainers
Triage community-reported issues, review contributor PRs, and maintain code quality at scale without burning out maintainers.
- Issue triage
- Contributor PR review
- Release management
Technical Specifications
Enterprise-grade infrastructure built for scale and security.
See It in Action
Read how this technology works under the hood, with real output from production systems.
Commit-Based Skill Profiling: How AI Dev Command Knows Your Team Better Than You Do
We analyze Git commit history to build developer skill profiles -- mapping language proficiency, domain expertise, code quality, and collaboration patterns. Teams use skill-based task routing to eliminate misassignment and move faster.
Product Roadmap
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Best suited for: Software development companies with 5-100 engineers, startup CTOs running lean teams, agencies managing multiple client codebases, and engineering managers who want data-driven team allocation.
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