EasyEnv Engineering
Stay sharp in the age of AI.
Practice on real environments, take graded challenges, and keep the judgment AI cannot hand you.
FAQ
EasyEnv Engineering
Practice on real environments, take graded challenges, and keep the judgment AI cannot hand you.
FAQ
Practice on real environments, take graded challenges, and keep the judgment AI cannot hand you.
Your team builds here, on machines that already have the stack.
Cloud development environments that boot in seconds.
Real Linux machines, not containers
Every lab is a full VM with root. Run Docker, Kubernetes, systemd and anything else that needs a real kernel.
Multi-machine workspaces
A workspace can hold several boxes networked over a private mesh VPN, so you can model a real topology, not one container.
VS Code in the browser
Full editor, terminal and port forwarding with nothing to install. Share a live session with a teammate from the same URL.
Recipes for the stack you need
Pick from pre-built machine recipes covering languages, databases, CI/CD and infrastructure, or bring a custom image.
Hands-on courses that run on the machine you are learning about.
Every lesson runs on a real box
No sandboxed snippets. Each lesson opens a machine with the tools already installed and the exercise already staged.
An AI tutor that reads your code
The tutor sees the files you are working in and the commands you ran, so it answers about your work rather than in general.
Roadmaps, not just courses
Courses are grouped into role-based roadmaps so a learner has an ordered path rather than a catalog to guess at.
Checkpoints that actually run
Progress is gated on graded checkpoints executed on the box, so finishing a lesson means the work passed.
Auto-graded challenges on a real, deliberately broken machine.
Diagnose and fix, not multiple choice
Each challenge hands over a machine in a broken state. The task is to work out what is wrong and repair it.
Graded by running the system
A judge runs against the box after the attempt, so the score reflects whether the thing works, not how it was written.
Tracks across the stack
Challenges span AI and agents, languages and frameworks, DevOps and cloud, and data.
A public profile of what you fixed
Completed challenges build a shareable profile, which is evidence a candidate can point a hiring team at.
Claude, open models and coding agents, on the machine itself.
Included on every Engineering plan
AI is part of the product rather than a separate subscription. Every tier includes a monthly token allowance.
Agents that operate the whole box
An agent runs inside the machine with the same access you have, so it can install, configure and debug, not just write text.
Bring your own account, or use ours
Sign in with your own Claude account, or run an open model locally on the box when the work cannot leave the machine.
One plan covers Lab, Courses and Challenge. Hiring rather than building? EasyEnv Interview runs assessments on these same machines.
workspace / payments-api
3 boxesnode 22
16.2
7.2
private mesh network, no public IPs
python / lesson 7 of 14
50%Line 7 of counter.py uses return where the generator needs yield.
nginx / broken upload
12:04 left