AI Agent Orchestration Implementation - Day 2
Twenty-four hours into active usage, and we're already seeing early results. The client's primary goal—increasing productivity—is showing early improvements. More importantly, the team is starting to use the system.
The Goal Management Framework
Yesterday, we mentioned the four-tier goal management system at the heart of this implementation. The framework addresses a specific challenge: helping the team finish what they start whilst ensuring every action aligns with strategic objectives.
The system creates accountability through structure. Weekly goals must connect to quarterly objectives, which ladder up to the long-term vision. When someone begins a new task, the coaching agent asks a simple question: "Which goal does this support?"
That single question is already influencing behaviour, with the team openly discussing the most important tasks to complete right now, what needs to be finished, and what can wait.
Early Adoption Patterns
The most encouraging sign isn't the technology working—it's the team treating the agents as genuine resources rather than novelties. They're consulting agents for strategic guidance on positioning, prioritisation frameworks, and decision support. The personal coaching agent is proving particularly valuable for maintaining focus and validating that work aligns with stated goals.
Addressing the Three Goals
Recall the client's objectives: increase productivity, control costs, and establish the technology foundations and ‘AI culture’ needed for long-term competitive advantage.
On productivity, we're seeing the most early gains. The team is working more deliberately, with a clearer connection between daily actions and strategic objectives.
On cost control, the value proposition is straightforward—specialist expertise available on demand without the overhead of full-time hires, as highlighted by the early use of the personal coach.
Establishing the AI technology and AI culture will take more than a day or two.
Daily Refinements
We're making small adjustments based on real usage. Some agent responses needed recalibration for the appropriate detail level. The routing between agents required smoothing—helping the team understand which specialist to consult for specific questions. We adjusted how agents maintain context across conversations to avoid repetitive exchanges.
These refinements happened within 24 hours. By week's end, we expect many more. This is precisely why we designed for daily iteration rather than fixed deployment.
Tomorrow: Focus will be on improving agent routing and adding conversations from one of the major commercial LLMs to the system to enhance context.