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Enterprise Custom · 3-day studio

From business scene to
AI tool MVP
AI 工具 MVP

Start from a real enterprise need, and finish high-value scene selection, AI workflow design, MVP build, and business validation in three days.

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Duration
3days
Spine
1real business case
Outcome
1AI MVP
Audience
Business leads

Positioning

Don't start from tools.Start from a real problem.

Built for business leads and internal AI talent. Learners practice on their own business; cases only help explain the method.

  1. 01 Identify and define

    Choose the right business scene

    Day 1
  2. 02 Break down and design

    Form a workflow plan

    Day 2
  3. 03 Build and verify

    Ship an AI tool MVP

    Day 3

3-Day Curriculum

Finish one realbusiness AI path in three days

Each day advances the same enterprise case; yesterday's output becomes today's input.

DAY01

Day 1

Scene discovery and AI task definition

Move from “want AI” to “know which business problem to solve.”

Core content

  • Understand the capability bounds of AI, LLMs, workflows, and agents.
  • Inventory high-frequency, repetitive, verifiable tasks in your business.
  • Screen scenes by value, data readiness, risk, and feasibility.
  • Clarify the problem, target users, and current way of working.
  • Define inputs, processing rules, expected outcomes, and human ownership.
  • Converge a minimal business loop and MVP goal.

DAY02

Day 2

AI workflow and MVP plan

Turn the business need into a runnable, testable AI plan.

Core content

  • Break the selected need into trigger, steps, decisions, and end conditions.
  • Separate fixed rules, model judgment, tool calls, and human handling.
  • Define tool inputs, returns, permissions, and write-back.
  • Design confirmation, pause, takeover, and review points.
  • Add exception paths for missing data, failed calls, and duplicates.
  • Lock MVP scope, run flow, and an initial prototype.

DAY03

Day 3

Build and verify the AI tool MVP

Prove with real cases that the tool can finish the intended work.

Core content

  • Build the AI tool against the confirmed workflow and scope.
  • Connect business input, AI processing, output, and human confirmation.
  • Test with normal, edge, and failure business cases.
  • Locate failure points and business-rule gaps from run records.
  • Fix key issues and re-run the original tests.
  • Do a final check against the problem, MVP goal, and enterprise need.

Delivery Principles

You leave with more than knowledge —you leave with a business outcome you can keep pushing

01Real businessUse an actual enterprise problem as the course project

02Minimal loopProve core value first, then expand scope

03Human-AI teamworkKeep human confirmation and ownership on critical judgments

04Tested proofUse business cases to prove whether the tool works

Start from one real problem

If your company already has a clear pain point, talk with us about whether the three-day custom course fits.

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