July 17-18, 2026 | Shanghai · Goger Office Space
On July 17-18, 2026, MindsLeap conducted a two-day enterprise AI engagement for Goger Office Space. The project combined interviews with core managers, AI training and hands-on work, and AI consulting informed by existing business materials. Together, these activities helped the management team build shared language around Agents, second-brain practices, and workflow design while identifying transformation scenarios and conditions for future pilots.
Combining training and consulting in one engagement allowed the team to first establish a shared understanding of AI capabilities and boundaries, then apply that understanding to Goger's own customer, sales, operations, space-service, and management processes.
The Training Component: Building Shared AI Language Through Real Tasks
The training moved from what AI can do to how a team can work with it. Participants explored an entrepreneur's second brain, AI Agent role design, Context management, workflow decomposition, and human checkpoints, then worked through exercises on their own computers.
The program emphasized that an Agent is not simply a chat window expected to answer every question. An Agent entering a business process needs a defined responsibility, source material, steps, permissions, output format, acceptance criteria, and exception path. The management team also needs to turn its judgment, examples, and rules into organizational Context that can be maintained over time.
The objective of the training component was not an immediate system rollout. It was to establish shared language for the project: what qualifies as a high-value use case, what can become a reusable Skill, which Workflow should be redesigned, and where human approval must remain.
The Interview and Consulting Component: Moving from Business Evidence to an AI Diagnostic
During the interview and consulting component, MindsLeap used six core-management interviews and available business materials to examine customer engagement, sales coordination, space operations, service delivery, and the way data and knowledge are retained.
The diagnostic did not begin with a list of popular AI products. It began with frequent work, information gaps, repetitive actions, judgment points, and accountability. Understanding the current process is necessary before deciding whether a problem calls for a knowledge base, an automated Workflow, a business Agent, or improvements to data and management practice.
From an Opportunity List to Pilot Priorities
The AI consulting phase converted the discussion into a comparable list of scenarios. Prioritization considers business value, data availability, implementation complexity, frequency, risk boundaries, and the presence of an internal owner. This moves the conversation from a broad ambition to a testable question: which workflow should be validated first, who owns it, and what review criteria should be used?
For an office-space service business, possible directions may include customer research, sales preparation, content and event operations, service knowledge, and meeting-action management. Whether any direction enters a pilot still depends on company data, system permissions, and confirmation from the people who will use it.
Why Training and Consulting Need to Connect
Consulting without shared understanding can remain inside a report. Training without a business diagnostic can leave employees experimenting separately. The two-day structure connected the two:
- Training established a shared view of AI capability, boundaries, and methods
- Interviews surfaced tacit knowledge and process constraints
- The diagnostic organized issues into scenarios, conditions, and priorities
- A future pilot can be designed around a named owner and acceptance criteria
This reflects a core MindsLeap enterprise AI path: use AI training to establish common language, use AI consulting and transformation diagnostics to determine direction, and then decide whether validated scenarios should proceed to an FDE pilot and production implementation.
Work Products from the Engagement
The two-day engagement produced shared management understanding, a structured view of interview and operating issues, an AI opportunity list, prioritization criteria, and a discussion of next-stage direction. These are diagnostic and design-stage work products. They are not claims that a production system has already launched or that business results have already been realized.
Frequently Asked Questions
How is enterprise AI consulting different from a tool recommendation?
AI consulting begins with business objectives, processes, data, roles, and governance conditions. Technology is selected only after the problem and operating context are understood.
What makes a scenario suitable for an FDE pilot?
It normally needs a clear business owner, available inputs, reviewable outputs, acceptable permission boundaries, and a baseline for evaluation. The organization still decides whether to proceed.
Was a production system launched during this engagement?
This public record covers the training, interview, consulting, and diagnostic stages. Any later system pilot or FDE implementation would require separate prioritization and company approval.
About MindsLeap
MindsLeap is an enterprise AI transformation and AI-native startup acceleration platform. Through the MindsLeap Founders AI Club, AI training and strategic advisory, FDE implementation, startup acceleration, and global growth services, MindsLeap helps traditional enterprises embed AI into real business workflows and helps AI-native ventures connect with industry use cases and global markets. MindsLeap is a global partner of Founders Space.
This article was translated and adapted from the Chinese original with AI assistance.