Share & Learn #17: Professional AI Orchestrator – When Each Individual Can Build Their Own "AI Team"

Nearly 70 Techvifers participated in Share & Learn #17 to explore a new approach in the AI era: not only using AI as a support tool but designing systems and orchestrating their own "AI teams." The session provided practical examples, visual demos, and clear perspectives on the shifting role of humans in the new work environment. 

AI is no longer a trend – it is a capability that must be orchestrated 

On the afternoon of 02/27/2026, the Share & Learn session was led by Harry Tran (TECHVIFY.D14) – Senior Software Engineer. This was the fourth time Harry joined the Share & Learn series, continuing to bring practical and updated content on how to apply AI in work.

The session attracted participation from various positions ranging from Developers, Project Managers to non-tech members, showing that AI is no longer just a technical matter but is becoming a shared capability across the entire organization. 

Right from the beginning, the speaker posed a clear issue: AI is no longer a trend to discuss but has become a practical capability. When an individual effectively combines with AI, they can achieve productivity equivalent to a whole team previously; the important question is no longer "whether to use AI," but "how well we orchestrate AI." 

The program's focus revolves around two concepts: AI Agent and AI Orchestrator. If an AI Agent can understand context, reason, make decisions, and execute iterative optimizations, then the AI Orchestrator is the one who designs the system and coordinates those agents. The biggest shift in the AI era lies here: human value is not only in performing tasks but in the ability to design processes and organize their own "AI teams." 

From demo sprint to building a working system with AI 

The demo handling multiple tasks in a sprint using AI was a highlight of the program. From requirement analysis, planning, task breakdown to progress tracking, the entire flow was illustrated in a practically applicable way. 

For the technical team, AI can participate from the requirement analysis stage, architecture design, database, sprint planning to generating code following predefined coding conventions. When set up with the right rules and standards, AI not only supports autocomplete but can operate as a system of coordinated agents. 

For the non-tech team, AI can assist in building master plans, WBS, timelines, writing reports, or breaking down long-term goals into specific action plans. The core is not that AI completely replaces humans, but how people set the context, establish standards, and orchestrate AI to produce the desired results. 

The consistent message throughout the session is a mindset shift: from "coding manually" to designing systems for AI to code; from relying on tools to mastering the operation and coordination of agents.

New mindset on productivity and continuous learning culture 

After the program, Teku Tran – Project Manager D3 – shared that the Share & Learn session helped him better understand how to leverage and orchestrate AI in work. Previously, he had thoughts about working with AI after watching the R&D team's automated test tool demo, but this session helped him understand more clearly how to exploit AI's strengths and approach it more systematically. 

The demo handling a series of tasks in a sprint was the most impressive content for him, as it clearly showed AI's power when orchestrated properly. According to him, the important thing is not just using AI but learning how to control and orchestrate it to produce products that meet requirements. 

In the near future, he plans to build a small demo that can handle many tasks like planning, then gradually establish rules and processes for AI to participate from analysis, planning, task creation to progress tracking. This is also the practical value the program aims for: each individual proactively experiments and makes AI a part of their working system. 

As a regularly organized activity, Share & Learn not only updates knowledge but also contributes to building a continuous learning culture within the company. When the team regularly accesses and shares practical experience, work efficiency improves and the organization's competitive capability is strengthened. 

Concluding nearly two hours of sharing, Share & Learn #17 not only provided knowledge about AI Agents and AI Orchestrators but also set a clear requirement: in the AI era, the most important capability is no longer doing more tasks but knowing how to design systems and orchestrate resources – including AI resources.