Introduction to Agentic

Introduction to Agentic

Agentic is a polyglot toolkit for AI agent orchestration. It gives you the primitives to spawn, coordinate, and manage AI agents across TypeScript, Python, and Rust — without locking you into a single framework or provider.

The Problem

AI agent tooling is fragmented:

• Framework lock-in — CrewAI, LangGraph, and Strands each have different APIs for the same concepts. Switching frameworks means rewriting everything.
• Token complexity — Managing GitHub tokens across multiple organizations is manual and error-prone. One wrong token breaks CI, PRs, or agent spawns.
• No fleet coordination — Spawning one agent is easy. Coordinating ten across different repos, monitoring their progress, and handling failures? That requires infrastructure.
• Scattered tools — Your triage system is separate from your fleet manager which is separate from your 3D pipeline which is separate from your game generator. No shared patterns.

The Solution

Agentic is five packages that solve these problems independently or together:

@jbcom/agentic (Control)

TypeScript

The orchestration layer. Spawn AI agent fleets, route tokens per organization, execute tasks in sandboxed Docker containers, and hand off work between agents with full context preservation.

agentic fleet spawn "my-org/api" "Fix failing CI" --auto-pr
agentic sandbox run "Security audit" --workspace . --timeout 900

@jbcom/agentic (Triage)

TypeScript

Portable triage primitives built on the Vercel AI SDK. Issue management, PR review, sprint planning — as composable tools that work with any AI provider and any project tracker (GitHub, Jira, Linear, Beads).

const result = await generateText({
  model: anthropic('claude-sonnet-4-20250514'),
  tools: getTriageTools(),
  prompt: 'Triage all open critical bugs',
});

agentic-crew

Python

Framework-agnostic crew orchestration. Define agents and tasks in YAML, run them on CrewAI, LangGraph, or Strands — whichever is installed. Includes a universal CLI runner for aider, claude-code, ollama, and other single-agent tools.

from agentic_crew import run_crew

# Auto-detects best framework at runtime
result = run_crew("my-app", "reviewer", inputs={"pr": 42})

@agentic/meshy

TypeScript

Declarative 3D asset pipelines for Meshy AI. Define text-to-3D, rigging, and animation pipelines in JSON. Built-in 3D preview, VCR recording for CI, and manifest-based state that survives failures.

content-gen run character ./assets/characters/hero

game-generator

Rust

AI-powered retro RPG generation with Bevy. Procedural worlds, characters, quests, and assets. Multi-provider AI with intelligent caching. Part of the Strata gaming platform.

let game = QuickGenerator::new()
    .genre(Genre::Jrpg)
    .theme(Theme::Fantasy)
    .generate_and_run();

Key Principles

Provider agnostic — Every package works with multiple AI providers. Anthropic, OpenAI, Google, Mistral, Ollama, Azure. Swap providers by changing a config value.

Declarative over imperative — Crews in YAML. Pipelines in JSON. Fleet config in JSON. Token routing from environment variables. Configuration lives in version control.

Security first — Token sanitization everywhere. SHA-pinned GitHub Actions. OIDC publishing. Sandboxed execution with Docker resource limits. Zero hardcoded credentials.

Polyglot — TypeScript for orchestration and web tooling. Python for AI framework integration. Rust for performance-critical game generation. Each language where it’s strongest.

Who Is This For?

You are…	Agentic gives you…
A developer managing multiple GitHub orgs	Automatic token routing — one config, all orgs
A team standardizing AI workflows	Framework-agnostic crews — define once, run anywhere
A platform engineer coordinating agents	Fleet management — spawn, monitor, coordinate, hand off
A game developer using AI generation	Procedural RPG content with Bevy integration
A 3D artist building asset pipelines	Declarative Meshy pipelines with manifest state

Next Steps

1. Quick Start — Install and spawn your first agent in 5 minutes
2. Configuration — Set up tokens, providers, and fleet defaults
3. Packages — Deep dive into each package
4. Guides — Learn orchestration patterns and best practices