A CEO overseeing 40 general managers replaced monthly operating reviews with 20-minute video updates. He feeds the transcripts into a custom AI agent trained on the company playbook to instantly identify key issues and revenue shortfalls. This transforms the review process from data gathering to rapid problem-solving.

Establish a powerful feedback loop where the AI agent analyzes your notes to find inefficiencies, proposes a solution as a new custom command, and then immediately writes the code for that command upon your approval. The system becomes self-improving, building its own upgrades.

WorkTrace AI addresses the bottleneck of identifying AI automation opportunities within enterprises. Instead of relying on expensive human consultants, its desktop app monitors employee workflows to automatically flag repetitive tasks, generating a prioritized roadmap of agent-based automation opportunities.

The greatest value of AI isn't just automating tasks within your current process. Leaders should use AI to fundamentally question the workflow itself, asking it to suggest entirely new, more efficient, and innovative ways to achieve business goals.

Detailed reports from AI workflow analysis tools may seem overwhelming, but they serve a crucial team function. They create a clear, shared understanding of how work currently happens, forcing alignment before a new, AI-driven process can be adopted successfully.

To find tasks ripe for AI automation, simply screen record yourself performing a repetitive, hour-long task. Then, upload the video to a multimodal LLM like Gemini 3 and ask it what parts can be automated and how much time you could save. This provides concrete, actionable suggestions.

To begin automating work with AI, record yourself performing a task on video (e.g., using Loom) while narrating the process. An AI can then analyze the transcript to identify the repeatable steps and logic, which forms the basis for building a custom, automated "skill" that mirrors your workflow.

Use AI on your own process to accelerate client work. Record discovery calls, generate transcripts, and feed them into an LLM. Ask it to identify the highest-value automation opportunities and map out the step-by-step workflow based on the client's own words.

Instead of pre-designing a complex AI system, first achieve your desired output through a manual, iterative conversation. Then, instruct the AI to review the entire session and convert that successful workflow into a reusable "skill." This reverse-engineers a perfect system from a proven process.