Our Approach
Ground your team in AI fundamentals
AI is rewriting how work gets done. Change is happening so quickly, it’s hard any one person to keep up, much less share skills or perspectives in a team.
Terminal’s AI training is built around your company’s actual workflows. Your team follows role-specific learning paths and builds practical use cases to create a shared AI language.
What teams receive
Role-specific learning paths
Practical curricula for each function, from operations to engineering.
A growing playbook library
Working patterns your teams can copy, adapt, and reuse.
Guided onboarding and live coaching
Real humans, not a video queue.
Workflow discovery exercises
Structured sessions tht surface where AI creates value in your operation.
Shared experiment tracking
Structured sessions tht surface where AI creates value in your operation.
A shared foundation
Technical and non-technical teams learn the same language and build together.
Leadership sees adoption as it happens.
The platform tracks participation, experiments, and playbook reuse by team. Leadership sees where fluency is building, where momentum stalls, and which use cases are ready for deployment.
Give the AI your team’s context so everything after is relevant.
Ship real wins from real work—the receipts that AI is worth it.
Turn the strongest wins into playbooks the whole team can rerun.
Keep every teammate shipping weekly on the system you built.
The Engagement Model
Training and deployment run together.
Fluent teams spot better opportunities, and they operate the systems our engineers build. The two capabilities feed each other: workflow discovery in training becomes the deployment backlog, and live systems give teams something real to learn against.
Do we need to begin with training?
No. Companies can start with training, a deployment engagement, or a specific hiring need. For many organizations the two happen together: teams build AI fluency while Terminal engineers work with leadership to put the first high-value workflows into production.
