AI Training & Consulting
AI training and consulting is a fixed-package engagement of workshops, playbooks, and decision frameworks run against a team's own tools, data, and constraints. Sessions are split between leadership briefings and hands-on practitioner workshops, remote or on-site. It is a fit for teams that keep starting AI pilots without a shared way to decide which ones are worth finishing.
Workshops, playbooks, and decision frameworks that give your team a shared language for AI and the judgment to tell a real opportunity from a good demo.
Pricing Fixed packages or day rates, scoped to the audience and depth required. See full pricing →
Why this service exists
The bottleneck is rarely the model. It is a team with no shared way to decide.
Teams get stuck in two directions. Some treat every AI suggestion as a threat and stall out; others say yes to everything and end up with nine pilots and nothing in production. Both are decision problems wearing a technology costume.
We run hands-on sessions against your actual work: your tools, your data, your constraints. We leave behind the playbooks and decision frameworks your team keeps using after we are gone. The measure of success is that you need us less.
What’s Included
- ☽ Capability assessment across the roles that will actually use this
- ☽ Hands-on workshops built on your own tools and workflows
- ☽ Decision frameworks for build, buy, or leave it alone
- ☽ Playbooks and prompt patterns your team keeps and edits
- ☽ Guidance on where a human has to stay in the loop
- ☽ Optional office hours or coaching after the sessions end
The engagement is supposed to end
Capability rises while reliance on us falls, and the handover is the point where they cross
Everything we leave behind (the playbooks, the decision frameworks, the patterns) exists to move that crossing point earlier.
Common Engagements
How this work usually shows up
Example scopes that turn this service into something tangible inside the business.
Leadership Briefing
Engagement · 01
Give decision-makers the vocabulary and the judgment to evaluate proposals without a translator.
AI Training & Consulting
Practitioner Workshops
Engagement · 02
Hands-on sessions for the people doing the work, using the systems they already run every day.
AI Training & Consulting
Standing Office Hours
Engagement · 03
Recurring time for a team mid-adoption to bring real problems to someone who has shipped them before.
AI Training & Consulting
FAQ
AI Training & Consulting questions
The questions that come up most on intro calls, answered before you have to ask.
Who is the AI training for — engineers or non-technical staff?
Both, in separate sessions. MagicPill Labs runs leadership briefings that give decision-makers the vocabulary and judgment to evaluate AI proposals without a translator, and practitioner workshops for the people doing the work, built on the tools and workflows they already run. The capability assessment at the start of an engagement decides which roles need which sessions.
How long is a typical AI training engagement?
Engagements are sold as fixed packages scoped to the audience and depth required, ranging from a single leadership briefing to a series of hands-on workshops spread across several weeks, with optional office hours afterwards. The measure of success is that the client needs MagicPill Labs less over time, so engagements are scoped to end rather than to renew.
Is the training remote or on-site?
Both are available. MagicPill Labs is based in Ridgefield, Washington and runs on-site sessions throughout the Portland–Vancouver metro area; teams elsewhere in the United States are served remotely, which is how most workshops run. Hands-on sessions work equally well remotely because they are conducted against the client's own tools and data.
What does the team keep after the training ends?
Teams keep the playbooks, prompt patterns, and decision frameworks produced during the sessions, written so they can be edited and extended internally rather than treated as fixed artifacts. That includes a build-buy-or-leave-it-alone framework for evaluating future AI proposals and written guidance on where a human has to stay in the loop.