PromptisePromptise
Docs
GitHub
Promptise - AI Framework LogoPromptise

The foundation layer for agentic intelligence. Build, secure and operate autonomous AI systems with Promptise Foundry.

pip install promptise

[01] Foundry

  • MCPcast
  • The Promptise Agent
  • Reasoning Engine
  • MCP
  • Agent Runtime
  • Prompt Engineering
  • Execution Engine
  • Agent Identity

[02] Resources

  • Documentation
  • GitHub
  • Guides
  • Learning Paths
  • Questions

[03] Company

  • About
  • Terms of Service
  • Privacy Policy
  • Cookie Policy
  • Subprocessors

© 2026 Promptise by Manser Ventures. All rights reserved.

Open source · Python

← Learning paths> Enterprise AI· featured
Intermediate path

Enterprise AI Agents: Evaluate, Design and Govern

Start the pathAll paths

For IT, security, platform and architecture leads bringing AI agents into a large organization. You assess where you stand with a maturity model, learn a vendor-neutral reference architecture, evaluate platforms with a weighted scoring sheet, and set up operational governance: owners, approvals, limits, logging and reviews. The path ends with what an agent runtime is and what to check before an agent goes live.

7
Lessons
1.6 h
Reading time
Intermediate
Level
Free
Cost

The lessons

7 lessons

Read the lessons in order; they are arranged so each one prepares the next. Every lesson is a guide, so you can also open any of them on its own.

  1. [01]AI Maturity Model: 5 Stages from Experiments to AI AgentsAn AI maturity model for the agent era: five stages from first experiments to AI agents in production, what each stage needs, and a self-assessment.Beginner · 12 minOpen →
  2. [02]Enterprise AI Agent Architecture: Layers and Build OrderEnterprise AI agent architecture explained: a vendor-neutral reference architecture with eight layers, a diagram, example products and a build order.Intermediate · 14 minOpen →
  3. [03]AI Agent Platform Evaluation Checklist and Scoring SheetAn AI agent platform evaluation checklist for IT and security leads: nine weighted criteria, a 1-5 scoring sheet, vendor questions and a pilot plan.Intermediate · 14 minOpen →
  4. [04]AI Agent Governance: How to Govern AI Agents in PracticeAI agent governance in practice: owners, approvals, limits, logging, review cadence and incident steps for AI agents, with templates. Operational only.Intermediate · 13 minOpen →
  5. [05]What Is an Agentic Runtime? AI Agent Runtimes ExplainedAn agentic runtime runs AI agents as long-lived processes with triggers, state, crash recovery and budgets. See how it differs from frameworks and hosts.Beginner · 13 minOpen →
  6. [06]AI Agent Audit Logging: Tamper-Evident Logs in PythonLog every AI agent tool call to an HMAC-chained file, then catch edits, deletions and reordering with one command. Real tamper tests, real output.Intermediate · 15 minOpen →
  7. [07]AI Agent Production Checklist: What to Check Before LaunchAn AI agent production checklist: security, approvals, guardrails, limits, cost, observability, evals, deployment and incident response, with code.Intermediate · 17 minOpen →
Start lesson 01

Before you start

  • Familiarity with enterprise IT: identity, networking, logging and change management. No agent development experience needed.

Skills you build

  • Assessing AI agent maturity across an organization
  • Designing an enterprise AI agent architecture
  • Evaluating agent platforms with a weighted scoring sheet
  • Setting up operational governance for AI agents

By the end, you can

  1. 01Place your organization on a five-stage maturity model
  2. 02Review an agent design layer by layer
  3. 03Run a fair platform evaluation with a pilot
  4. 04Give every agent an owner, approvals, limits and an audit trail

Ready when you are.

7 lessons, in order. Each opens with the full list beside it, so you always know where you are and what comes next.

Start the pathThe guide library