DOIL · open concept
Level 4 autonomous network operations

Agentic design.
Deterministic operations.

DarkNOC is a Level 4 autonomous network operations platform built to fit existing telecom operations, not replace them.

It integrates with existing OSS and BSS, ticketing, CI/CD, governance, and operational workflows. Agentic intelligence is used for exploration, design, tuning, and orchestration, while production execution remains deterministic, governed, certified, and auditable.

Not a giant graph-first system.

DarkNOC does not require the operator to first build and maintain one massive perfect network graph. It starts from governed operational work: incidents, tickets, topology, alarms, evidence, approvals, rollback and audit. For each use case, the platform builds the scenario context needed for the decision and compiles the response into bounded workflows that fit existing enterprise tools such as Jira, Confluence, Git and change-control processes.

Telecom architecture fit

How DarkNOC fits

DarkNOC does not require a rip-and-replace transformation. It works as an autonomous execution and reasoning layer around existing operator systems, integrating with OSS and BSS platforms as well as ticketing, CI/CD, governance, and operational workflows.

  • Agents propose, explore, simulate, and improve workflows.
  • Certified deterministic automations execute in production.
  • Digital twins validate changes before promotion.
  • Ticketing and governance systems remain the operational source of truth.
  • Operator-specific workflows are layered on top without forking the platform.
The two ideas everything hangs on

The Reality Twin

Reality says what the network is. The digital twin says what it should be. The Reality Twin reasons across the two — with context from every operational app — and writes the situation down: "model says all-clear, RF says spoofed, SLA breaches in 18 minutes." That narrative is what the agents act on. Then it goes into the loop.

Read the idea →

Deterministic Autonomy

The only way you can actually build this. Put the intelligence where it matters — at build time, acting from experience and authority, reasoning hard while you can still verify it. Make operation the opposite — deterministic, secure, reliable, bounded; no runtime improvisation. A certification loop ties them: automations are synthesised, certified before they run, re-certified as they learn. Autonomy you can sign off on.

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More thinking

API-to-Agents

From APIs as integration points to agents as the operating layer.

Read

Persistent Context

Memory that accumulates institutional knowledge across operations.

Read

Developer Revolution

Context engineering and coordination between agent and human.

Read

All notes

The full set of essays.

Browse
The DarkNOC showcase

The ideas above are built, not slideware. Two surfaces show the machinery whole.

Simulators

10 network twins. Bidirectional sync. TMF v5.0 signal flows. Conversational query. Not a digital twin — a Reality Twin: signals in, models in the middle, agents acting back out.

Enter the constellation →

Cockpit

Hangar, Altimeter, Radar, Flight Deck. A cockpit view of the network — composite indexes, compartment models, agent and simulator feeds on one pane of glass.

Step into the cockpit →
The open toolchain

DOIL is a language, so it ships like one — $ doilgen compile incident_replayer.doil --target=twin. Also in the open repo: the agent registry and a full professional IDE on Monaco (stable, interconnected, built for production).

DOIL compiler

Compiles .doil to React/Next.js UIs, LangGraph agents, Docker/K8s.

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DOIL wizard

Concept wizard: Basics → Tasks → MCP → LLM → Generate.

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VSCode extension

Syntax, IntelliSense, MCP-aware completion, compile on Ctrl+Shift+C.

Read

Test environment

Jest + RTL + LangGraph + K8s validation before anything runs.

Read
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