+ Agentic AI adoption ladder
Forge helps teams build practical AI fluency by doing real work, not generic training. Work that repeats becomes approved skills, with budgets, receipts, and evidence.
Example first mission: the marketing team turns product briefings into launch drafts — with an approved model, a governed budget, and a receipt for every run.
Start with one motivated team, 5-15 users, and 30-45 days to prove whether AI work becomes repeatable capability, not another tool rollout.
Buying AI features gives people access. Building AI fluency changes how the company works.
First mission
Users learn agents by doing real work with a clear goal, context, and boundary.
Approved skill
Repeated work becomes a reusable pattern with owners, inputs, and review rules.
Governed run
Model, budget, connector, and permission checks happen before execution.
Receipt
The run leaves metadata-first evidence users and sponsors can inspect.
Workflow decision
Sponsors decide what to expand, continue, improve, or stop.
Onboard a team into useful agentic work, then move repeated usage into governed operation when the patterns are worth scaling.
Use one live workflow to build practical fluency: first missions, starter skills, and literacy around models, costs, permissions, and receipts.
When a pattern earns repetition, move it into Forge's control plane: approved workflows, model routes, virtual keys, budget checks, and audit evidence.
A 30-45 day proof path delivers the ladder in a bounded way: build team fluency, prove governed usage, and decide whether to expand, continue, improve, or stop.
Sponsor, team, workflow, budget, data, connector, and review boundaries.
Build practical fluency by doing useful work with approved starter skills.
Configure control-plane scope and turn repeated work into approved workflows.
Review activation, reuse, cost, blocks, receipts, and workflow candidates.
Teams learn agents by doing real work without guessing which model, key, permission, or workflow pattern to use.
Sponsors and admins see which workflows are becoming capability, where risk appears, and what deserves investment next.
The review is about team workflows and operating patterns, not employee surveillance.
These modules use illustrative demo or sample pilot data until real screenshots are approved and redacted.
Team, users, virtual keys, model aliases, and budget caps.
Approved starter skill with a user-facing receipt explanation.
Model alias, status, cost/policy decision, evidence metadata, and review status.
Activation, usage, spend, blocked reasons, skill reuse, and workflow candidates.
Broad connector access, production writes, regulated data, and raw-provider control.
Weekly receipts summarize approved runs, review pauses, blocked requests, spend, and workflow candidates. Illustrative numbers from a 30-day, 10-user pilot.
| Workflow | Role | Model alias | Status | Evidence |
|---|---|---|---|---|
| Launch Brief Draft | Pilot user | approved-fast-draft | Approved | Receipt |
| Customer Summary | Pilot user | approved-deep-review | Approved | Receipt |
| Implementation Handoff | Sponsor | approved-deep-review | Needs review | Pause reason |
| Connector Request | Admin | approved-fast-draft | Blocked | Blocked reason |
+ Book a quick chat
Book a 20-minute conversation. We'll learn what kind of company you are, where AI is already showing up in the work, which team needs fluency first, and whether Forge is the right way to help.
Pick a slot directly in the calendar. The conversation is for fit qualification and next-step guidance; do not include sensitive work content in the booking.