AI Pathways: Lab

Build repeatable AI patterns your team can keep using.

Lab is a deeper AI implementation workshop for teams ready to move beyond ideas. Teric helps the team build, test, refine, and document practical AI workflow patterns using realistic or sanitized examples from the business.

FormatOne day or two half-days
AudienceUp to 15 participants
Investment$12,500

Best fit

For teams that already know the opportunities and need repeatable patterns.

Use Lab when the team has priority use cases and wants to turn them into working patterns, review rules, and a short adoption plan.

Use cases are already known

The team has several AI opportunities and needs help turning them into usable patterns.

Workflows need structure

The group needs to break each workflow into triggers, sources, prompts, outputs, review, and ownership.

Source context matters

The team needs to understand which information AI should use and how it should be reviewed.

Behavior change is the goal

Training needs to become an operating pattern the team can keep improving after the session.

What you get

A workflow library, operating rules, and a 30-day AI implementation path.

Lab turns priority use cases into documented AI-assisted workflows so the team can repeat them, review them, and decide which ones deserve implementation work later.

3-5 tested workflow patterns

Documented patterns with trigger, inputs, context, prompt or instruction, output, review step, and owner.

Prompt and instruction library

Reusable prompts, instructions, and output formats the team can return to after the lab.

Workflow QA checklist

Criteria for deciding whether AI-assisted output is useful, accurate, and reviewable.

30-day adoption plan

Owners, next steps, and implementation opportunities for the patterns worth advancing.

Session flow

A working session that turns priority use cases into reusable team patterns.

01

Confirm workflows

Select the 3-5 candidate workflows most likely to work inside the package.

02

Break down the pattern

Map trigger, source, action, output, review, and owner for each workflow.

03

Draft and test

Build prompts or instructions and test them against realistic or sanitized examples.

04

Refine standards

Improve output formats, source strategy, human review, and acceptance criteria.

05

Document the operating path

Finalize the workflow library, QA checklist, owners, adoption steps, and implementation opportunities.

Boundaries

Lab is scoped training and advisory, not open-ended implementation.

Each package keeps the work focused so buyers understand what they are getting, what is outside the fixed fee, and where the right follow-on path begins.

IncludedWorkflow selection, live lab session, tested patterns, prompt library, QA checklist, and 30-day adoption plan.
Not includedProduction system buildout, custom agents, custom integrations, IT remediation, or ongoing managed support.
Best next moveMove into implementation when one of the patterns is ready for automation, Optic, or agent buildout.

After Lab

Use Lab to find what is ready for implementation.

Lab gives the team usable AI patterns and gives leadership a clearer view of which workflows should stay human-assisted, which need more adoption time, and which are ready for automation or agent work.

FAQ

Common Lab questions.

Is this an AI implementation workshop?

Yes. Lab is a working session for turning priority use cases into repeatable AI workflows, prompt patterns, review steps, and adoption next steps.

Do we use real company data?

We can use realistic or sanitized examples. Sensitive information and data rules are confirmed during prep.

Is this implementation?

No. Lab builds and documents reusable patterns. Production automation or agent buildout is scoped separately.

Who should attend?

Power users, managers, operators, and department leads who understand the work and can help shape the pattern.

AI Pathways: Lab

Turn priority AI use cases into repeatable patterns.

Tell us about the team, the workflows you want to test, and what examples are available.