# Beyond the CLI: Why Your AI Coding Agent Needs Enterprise-Grade Orchestration

*A practical guide for engineering leads evaluating orchestration tools for production teams.*

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You've got Claude Code running locally. Your team loves it. Productivity is up, code reviews are faster, and your junior devs are shipping like seniors.

Then someone asks: *"How do we run this in CI?"* And another asks: *"Who approved that production change?"* And your compliance team says: *"We need an audit trail for every AI-generated code change."*

That's the gap between "AI coding tool" and "production-ready AI coding infrastructure." And it's wider than most teams expect.

## The Orchestration Problem

AI coding agents are powerful in isolation. But teams don't work in isolation. They need:

- **Session management** — create, monitor, and manage multiple concurrent coding sessions
- **Access control** — not everyone should have the same permissions
- **Audit trails** — every action logged, traceable, and tamper-evident
- **Integration** — REST APIs, webhooks, and event streams that connect to existing tooling
- **Observability** — metrics, traces, and alerts when something goes wrong

Most orchestration tools solve the first problem (session management) and stop there. The others — access control, audit, compliance — are left as "future work" or "use a reverse proxy."

But "future work" has a way of becoming "the thing that blocks our enterprise deal."

## What Enterprise-Grade Actually Means

Let's be concrete. Here's what separates a weekend project from production infrastructure:

### 1. Authentication That Scales Beyond a Single Token

A shared API token works for one developer on one machine. It fails the moment you have:

- Multiple team members with different access levels
- CI/CD pipelines that need programmatic access
- Contractors who should see some projects but not others
- Automated alerts that need read-only access

Production systems need **role-based access control** with granular permissions — viewer, operator, admin — and per-key scoping so a CI bot can create sessions but can't rotate your auth tokens.

### 2. Session Ownership

When three developers and two CI pipelines are all creating sessions, you need to know **who owns what**. Session ownership means:

- An API key can only operate on sessions it created
- No accidental cross-contamination between team members
- Clear attribution for every action taken

Without ownership, you have shared state chaos. With it, you have accountability.

### 3. Tamper-Evident Audit Trails

Compliance frameworks (SOC 2, HIPAA, GDPR) don't care that your AI tool is "really useful." They care that you can answer:

- *Who* initiated this code change?
- *When* was it approved?
- *What* did the AI propose vs. what did the human accept?
- *Can you prove* this log hasn't been tampered with?

SHA-256 chained audit logs with daily rotation aren't optional for regulated industries. They're the baseline.

### 4. Observability Built In, Not Bolted On

When an AI coding session stalls at 2 AM, your on-call engineer needs:

- Prometheus metrics (`/metrics` endpoint, standard exposition format)
- OpenTelemetry traces for request flow
- Real-time event streams (SSE) for live monitoring
- Alert webhooks that integrate with PagerDuty, Opsgenie, or Slack

Not a log file someone has to SSH into a server to read.

### 5. Infrastructure That Fits Your Stack

Production means:

- **Kubernetes deployment** with proper health checks and graceful shutdown
- **PostgreSQL + Redis** for persistent state and session recovery
- **Reverse proxy ready** — TLS termination, CORS, security headers
- **SSRF protection** — blocklist for RFC 1918, loopback, link-local addresses
- **Input validation** on every endpoint (not "we'll add validation later")

These aren't nice-to-haves. They're the difference between "it works on my machine" and "it works in production."

## The Hidden Cost of "Simple"

Many orchestration tools pride themselves on simplicity. One command to install. Zero configuration. And that's great — for getting started.

But "zero configuration" often means "zero access control." "One command install" often means "one shared secret for everyone." And "it just works" often means "it just works until you need to prove to an auditor that it works correctly."

The engineering decision isn't "simple vs. complex." It's **"simple now, rebuild later" vs. "structured now, scale later."**

## The Compliance Checklist

If you're evaluating an orchestration tool for a team of more than five people, or for any organization with compliance requirements, here's what to check:

| Requirement | What to ask |
|---|---|
| Authentication | Can I create multiple API keys with different roles? |
| Authorization | Does each key have scoped permissions, or is it all-or-nothing? |
| Session ownership | Can I enforce that keys only access their own sessions? |
| Audit logging | Are logs tamper-evident? Chained? Rotated? |
| Encryption | Are secrets encrypted at rest? API keys hashed, not stored plaintext? |
| Network security | Does it listen on localhost only by default? SSRF protection? |
| Observability | Prometheus endpoint? OpenTelemetry? Alert webhooks? |
| Deployment | Can I run it in Kubernetes? Behind a reverse proxy? |
| Session recovery | What happens when the process restarts mid-session? |
| Rate limiting | Built-in, or do I need to add my own? |

If the answer to more than three of these is "not yet" or "use a reverse proxy," you're looking at a tool that will need significant hardening before production use.

## Why We Built Aegis This Way

Full disclosure: we're the team behind [Aegis](https://github.com/OneStepAt4time/aegis), an open-source orchestration server for Claude Code. We built it enterprise-first because we've been the engineering leads staring at compliance checklists.

Aegis ships with:

- **Multi-key RBAC** — viewer, operator, admin roles with per-key permissions
- **Session ownership enforcement** — keys scoped to their own sessions
- **Tamper-evident audit logs** — SHA-256 chained, daily rotation
- **Prometheus + OpenTelemetry** — metrics and traces out of the box
- **Kubernetes-ready** — health checks, graceful shutdown, state recovery
- **SSRF blocklist** — RFC 1918, loopback, link-local, CGNAT, multicast
- **AES-256-GCM secret encryption** — hook secrets, API key hashing
- **Multiple integration paths** — REST API, MCP server, CLI, Telegram, Slack, webhooks

It's not the simplest tool to set up. We know that. But "simple" and "production-ready" are different problems, and we chose to solve the second one first.

## The One-Command Future

We're working on making the enterprise path as smooth as the simple one. With `ag run`, you go from install to a running coding session in two steps — install, then run. No config file, no setup wizard, no token for local use.

But when your team grows, when compliance knocks, when you need to know who approved what and when — the structure is already there. No migration, no rebuild.

## The Bottom Line

If you're a solo developer experimenting with AI coding, use whatever's simplest. Seriously.

If you're an engineering lead building for a team — especially one with compliance requirements — look past the star count and check the access control model. The tool that gets you started fastest isn't always the one that gets you to production fastest.

The best time to think about audit trails is before the auditor asks.

---

*Getting started with Aegis:*
```bash
npm install -g @onestepat4time/aegis
ag run
```

*Read the docs:* [getting-started.md](../getting-started.md) | [enterprise.md](../enterprise.md) | [COMPLIANCE.md](../COMPLIANCE.md)

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*Published 2026-05-11 by the Aegis team. Aegis is open source (MIT) and available at [github.com/OneStepAt4time/aegis](https://github.com/OneStepAt4time/aegis).*
