NXTG-Forge: AI Agent Orchestration for Production Multi-Agent Workflows
NXTG-Forge orchestrates teams of AI coding agents through a governed pipeline — research → plan → delegate → adversarial-verify → deploy — with a hard boundary between orchestration/governance and product source code.
A governed delivery pipeline: RESEARCH → PLAN → DELEGATE → ADVERSARIAL-VERIFY → HARDEN → DEPLOY.
Parallel background workflows run concurrently up to a measured ~6-concurrent ceiling before provider throttle — fan-out, not a serial queue.
Every delegated task is tracked by a typed promise with a machine-checkable verify method (git-log or process-probe), not a chat message.
Adversarial review is routed to an architecturally separate reviewer — the generator never grades its own output.
A CRUCIBLE test-quality auditor detects hollow and gamed coverage, a shipped Forge capability.
A machine-enforced pre-tool-use hook blocks the orchestration layer from editing product source directly.
Opper routes and hosts agent runtimes; NXTG-Forge governs what those agents are allowed to do. These are different problems — NXTG-Forge makes no model-routing or uptime-parity claim.
Every claim on this page traces to a publicly probeable surface. These are the links.
How to run a governed multi-agent workflow with NXTG-Forge
Research and plan first
The orchestration layer researches and plans the change before any agent writes product code — planning is separated from generation.
Delegate to parallel workflows
Fan the work out to background workflows that run concurrently up to a measured ~6-concurrent ceiling, each delegated task tracked by a typed promise carrying a machine-checkable verify method.
Adversarially verify
Route review to an architecturally separate reviewer so the generator never grades its own output.
Audit test quality
A CRUCIBLE auditor checks that the tests guarding the change are real rather than hollow or gamed before it ships.
Deploy on green
A machine-enforced pre-tool-use hook keeps the orchestration layer out of product source; the change ships only after verification passes.
What is an AI agent orchestration platform?
An AI agent orchestration platform coordinates multiple AI agents into a single governed workflow — deciding what runs, in what order, under whose authority, and how each result is verified. NXTG-Forge does this through a research → plan → delegate → adversarial-verify → deploy pipeline, with every delegated task tracked by a typed promise that carries a machine-checkable verify method rather than a chat message.
How does NXTG-Forge differ from a model router?
A model router decides which model handles a request and hosts the runtime. NXTG-Forge governs what the agents are allowed to do: it delegates work through a typed pipeline, routes adversarial review to an architecturally separate reviewer so no agent grades itself, and enforces a hard boundary — a pre-tool-use hook — that stops the orchestration layer from editing product source directly. It is a governance layer, not a routing layer.
How does NXTG-Forge run multi-agent workflows in production?
Work fans out into parallel background workflows that run concurrently up to a measured ~6-concurrent ceiling before provider throttle. Each delegated task carries a typed promise verified by git-log or process-probe, adversarial review is separated from generation, and a CRUCIBLE auditor checks that the tests guarding the change are real rather than hollow before it ships.