Agent Dashboard

See also: Model-Context Pipeline

• Overview

  • A custom-built tool I’ve engineered for rapidly experimenting with agentic workflows.
  • 
  • Python · fast-agent · LLM APIs · Textual (Terminal UI)
  • View the code on GitHub

• Problem

  • Consumer-facing AI products like ChatGPT, Zapier are useful but unsatisfactory for the needs of professionals in an ever evolving industry; they need solutions that are consistent, reliable, scalable, and pleasant to use.

• Solution

  • I use the Agent Dashboard to rapidly author, test, and manage powerful AI ‘agents’. These are a team of specialized AIs that work together to create solutions greater than the sum of their parts. This ‘agentic’ approach allows me to solve problems traditional automation can’t touch.

• Outcome

  • This project demonstrates the the value I provide to my clients; by implementing similar bespoke tools & workflows a business can:
    • Automate high complexity, low value tasks: Go beyond simple automation to solve multi-step, well-defined processes that currently require significant manual effort.
    • Increase team efficiency and focus: Free your skilled team from the subtly toxic drain of tedious work, allowing them to concentrate on high-impact, strategic initiatives.
    • Modernize operations: Create a reliable, scalable, intuitive system which turns such messy internal processes into a competitive advantage.

• Insight

  • Modern automation relieves people of tedious work and the need for perfect precision;
  • Thus freeing up people and resources;
  • Which means people have more time & attention for what really matters: The human element of work that gets us out of bed in the morning;
  • Free resources means freedom to choose where to direct them.