SELECTED WORK / 06
AI Agent Operations Console
Task tracking, lead research, review checkpoints and execution history in an operations console.
THE CHALLENGE
Useful agents. Visible decisions.
An agent workflow needs more than a chat window. Operators need to see the task, understand the proposed action and review what happens next.
Separate the control interface, integration workflows and agent runtime. Represent review checkpoints as task states and surface execution history alongside the work.
EXPLORE THE PRODUCT
See the product in action.
Explore a working portfolio edition based on the project’s functionality, or open it at full size.
Portfolio interface based on reviewed project functionality, using anonymous content and sample data. Explore the screens and try the controls. Changes stay in this preview and reset on reload.
WHAT WAS BUILT
The pieces that
make it useful.
Selected work by our founder.
Agent control-plane and orchestration prototype.
- Task and lead-workflow interfaces
- Approval endpoints and runtime interrupts
- Execution history and cost-analysis code
- Integration workflows and an agent runtime
- 01Research & draft
- 02Review the action
- 03Record the decision
TOOLS & IMPLEMENTATION
Behind the work.
- Next.js
- Supabase
- n8n
- LangGraph
- Python
- Docker
Next.js
Supabase
n8n
LangGraph
Python
DockerBuild status
Source supports the described prototype. Current production use and complete enforcement of every approval and spending boundary have not been verified.
The case study describes reviewed implementation work. No measured savings, revenue gains or performance improvements are claimed.HAVE A SIMILAR CHALLENGE?