OpenPraxis FAQs

Question 1

What kind of auditing and quality control does OpenPraxis offer for agent output?

Accepted Answer

An independent 'Watcher' auditor automatically enforces Git commits, successful builds (e.g., `go build`), and spec compliance post-task execution. Agents cannot self-grade; the Watcher ensures deliverables are met and code quality standards are upheld.

Question 2

What is OpenPraxis and what problem does it solve?

Accepted Answer

OpenPraxis is a spec-driven development platform that orchestrates autonomous coding agents, managing their full lifecycle from idea to audited execution. It solves the challenge of agent observability, cost control, and compliance by providing real-time tracking, independent auditing, and persistent memory.

Question 3

How does OpenPraxis help manage development costs with AI agents?

Accepted Answer

OpenPraxis provides a real-time dashboard with live cost tracking, daily budget adherence, and task-specific spend analysis. Costs are aggregated hierarchically (Product → Manifest → Task), giving you granular financial oversight and preventing runaway agent expenses.

Question 4

Does OpenPraxis support persistent memory for AI agents across sessions?

Accepted Answer

Yes, OpenPraxis captures every agent conversation, decision, and tool call (bash, file ops) with detailed logs and searchable history. It provides persistent memory and semantic search capabilities, allowing agents to build on past knowledge across sessions and machines.

Question 5

How does OpenPraxis visualize the development process?

Accepted Answer

OpenPraxis renders products as interactive directed acyclic graphs (DAGs), showing manifest build orders and task execution chains with status-colored nodes. This provides a clear, shareable visual overview of the entire spec-driven development plan.

OpenPraxis

OpenPraxis

Key Features

Use Cases

Key Features

Use Cases