Integration
Build faster with AI-powered development.
AI-augmented dev environments that ship working code faster, onboard developers in days instead of weeks, and eliminate the friction of inconsistent tooling.
The problem
Your developers are fighting their tools instead of building.
Slow onboarding
Every new hire spends days or weeks configuring their environment, hunting for setup instructions, and troubleshooting machine-specific inconsistencies.
Inconsistent setups
One dev runs Docker on macOS while another uses WSL on Windows. AI tools are installed but poorly configured, offering generic completions instead of context-aware suggestions tuned to your codebase.
AI productivity left on the table
Cursor, Copilot, and Claude Code can dramatically accelerate development, but only when configured with the right context, project rules, and team conventions.
What Kobol builds
Reproducible environments with the AI context layer baked in.
Kobol architects and deploys complete AI-augmented dev environments tailored to your stack. Containerised, reproducible infrastructure (Docker, dev containers, WSL) ensures every developer works in an identical environment regardless of OS. Project-specific AI configuration files, custom prompt libraries, and `.aiignore` rules keep AI assistants tuned to your architecture and your sensitive code out of prompts.
Key deliverables
- Configured AI environments: fully wired Claude Code, Cursor, Copilot ready for day-one use
- AI context files & prompt libraries: project-specific configs, custom prompts, and .aiignore rules for security boundaries
- Onboarding docs & CI/CD templates: team onboarding documentation, AI-generated code review pipelines, and instant provisioning scripts
- Reproducible infrastructure: Docker, dev containers, WSL configurations that work identically across all developer machines
Process
From stack assessment to deployed team.
- Step 01
Stack Assessment
We audit your current dev environment, language stack, AI tool usage, and team workflow preferences.
- Step 02
Environment Design
We design the containerized environment, AI tool configuration, and project-specific context layer.
- Step 03
Build & Configure
We build the environment, configure AI assistants with your codebase context, and write the onboarding scripts.
- Step 04
Train & Hand Off
We train your team on the environment and AI workflows, then hand off with full documentation and 30-day support.
Engagement
Project-based
- ·Complete environment architecture and deployment
- ·AI tool selection and configuration
- ·Custom context files and prompt libraries
- ·Team onboarding and training
- ·30-day post-setup support
Engagement
Retainer
- ·Ongoing environment optimization
- ·New tool evaluation and integration
- ·Team coaching on AI-assisted workflows
- ·Monthly AI productivity reviews
- ·Priority technical support
Ready to see what's actually worth automating?
Book a free discovery call. 30 minutes, no strings, no pitch deck. We'll talk through your operations and tell you what's worth building before we send a single proposal.