Future Roadmap

Learn about upcoming features and the future direction of Grid's conversation primitives.

Overview

Grid's architecture is designed to evolve. This document outlines planned features and future directions, helping you make informed architectural decisions today.

WorkflowLoop (Coming Soon)

The next major addition to Grid will be the WorkflowLoop layer, which will sit above ConversationLoop and provide different execution patterns.

Planned Architecture

┌─────────────────────────────────────────────────┐
│              workflowLoop                       │
│  ┌─────────────┬──────────────┬──────────────┐ │
│  │ Autonomous  │    Guided    │    Hybrid    │ │
│  │    Mode     │     Mode     │     Mode     │ │
│  └─────────────┴──────────────┴──────────────┘ │
└─────────────────────────────────────────────────┘
                       ↓
              conversationLoop

Execution Modes

Autonomous Mode

Full agent autonomy with minimal human intervention:

const workflow = createWorkflowLoop({
  mode: "autonomous",
  agent: researchAgent,
  config: {
    maxIterations: 20,
    goalCriteria: {
      completeness: 0.95,
      confidence: 0.90
    },
    fallbackBehavior: "escalate"
  }
});

// Agent works independently toward goal
const result = await workflow.execute({
  goal: "Research and create comprehensive report on renewable energy",
  constraints: ["Use only peer-reviewed sources", "Include cost analysis"]
});

Guided Mode

Step-by-step execution with human approval:

const workflow = createWorkflowLoop({
  mode: "guided",
  agent: implementationAgent,
  config: {
    requireApproval: ["before-execution", "after-planning"],
    allowedActions: ["read", "analyze", "propose"],
    prohibitedActions: ["write", "delete", "execute"]
  }
});

// Each step requires confirmation
workflow.on("approval-needed", async (step) => {
  const approved = await getUserApproval(step);
  return approved;
});

await workflow.execute({
  task: "Refactor the authentication system",
  reviewPoints: ["architecture", "security", "tests"]
});

Hybrid Mode

Autonomous within boundaries, escalates when needed:

const workflow = createWorkflowLoop({
  mode: "hybrid",
  agent: supportAgent,
  config: {
    autonomousTasks: ["gather-info", "search-kb", "draft-response"],
    guidedTasks: ["execute-refund", "modify-account", "escalate"],
    escalationTriggers: {
      sentiment: "negative",
      confidence: "< 0.7",
      topics: ["legal", "security", "payment"]
    }
  }
});

Workflow Features

1. Multi-Agent Orchestration

Coordinate multiple specialized agents:

const workflow = createWorkflowLoop({
  agents: {
    researcher: researchAgent,
    writer: writingAgent,
    reviewer: reviewAgent
  },
  flow: [
    { agent: "researcher", task: "gather-information" },
    { agent: "writer", task: "create-draft" },
    { agent: "reviewer", task: "review-and-edit" },
    { agent: "writer", task: "final-revision" }
  ]
});

2. Conditional Branching

Dynamic flow based on conditions:

const workflow = createWorkflowLoop({
  agent,
  flow: {
    start: {
      action: "analyze-request",
      next: (result) => {
        if (result.complexity === "high") return "detailed-analysis";
        if (result.urgency === "high") return "quick-response";
        return "standard-process";
      }
    },
    "detailed-analysis": {
      action: "deep-research",
      next: "create-report"
    },
    "quick-response": {
      action: "template-response",
      next: "end"
    }
  }
});

3. Parallel Execution

Run multiple tasks simultaneously:

const workflow = createWorkflowLoop({
  agent,
  flow: {
    "gather-data": {
      parallel: [
        { action: "search-web", agent: "researcher" },
        { action: "query-database", agent: "analyst" },
        { action: "check-cache", agent: "system" }
      ],
      merge: "combine-results",
      next: "process-data"
    }
  }
});

Enhanced Tool System

Planned Features

1. Tool Composition

Create complex tools from simpler ones:

const composedTool = composeTools({
  name: "research-and-summarize",
  tools: [searchTool, extractTool, summarizeTool],
  flow: (input) => ({
    search: { tool: "search", params: { query: input.topic } },
    extract: { tool: "extract", params: { data: "$search.results" } },
    summarize: { tool: "summarize", params: { content: "$extract.content" } }
  })
});

2. Tool Versioning

Manage tool versions and compatibility:

const toolRegistry = createToolRegistry({
  versioning: true,
  compatibility: "semver"
});

toolRegistry.register({
  tool: weatherTool,
  version: "2.0.0",
  deprecates: "1.x",
  migration: async (oldParams) => newParams
});

3. Tool Permissions

Fine-grained tool access control:

const toolExecutor = createToolExecutor({
  permissions: {
    weatherTool: ["read"],
    databaseTool: ["read", "write"],
    systemTool: ["read", "write", "admin"]
  },
  authorize: async (tool, action, context) => {
    return await checkUserPermissions(
      context.userId,
      tool,
      action
    );
  }
});

Advanced State Management

Planned Features

1. State Schemas

Type-safe state with validation:

const context = createConversationContext({
  schema: z.object({
    user: z.object({
      id: z.string(),
      preferences: z.object({
        language: z.enum(["en", "es", "fr"]),
        theme: z.enum(["light", "dark"])
      })
    }),
    session: z.object({
      startTime: z.number(),
      actions: z.array(z.string())
    })
  })
});

// Type-safe access
const language = context.state.user.preferences.language;

2. State Synchronization

Multi-instance state sync:

const context = createConversationContext({
  sync: {
    backend: "redis",
    channel: `conversation:${sessionId}`,
    conflictResolution: "last-write-wins"
  }
});

// Changes automatically sync across instances
context.on("remote-update", (changes) => {
  console.log("State updated from another instance:", changes);
});

3. State Transformers

Transform state on read/write:

const context = createConversationContext({
  transformers: {
    write: {
      "user.email": (email) => email.toLowerCase(),
      "user.phone": (phone) => normalizePhone(phone)
    },
    read: {
      "user.name": (name) => capitalize(name),
      "prices.*": (price) => formatCurrency(price)
    }
  }
});

Conversation Persistence

Planned Features

1. Built-in Adapters

Ready-to-use database adapters:

const persistence = createPersistenceAdapter({
  type: "postgresql",
  config: { connectionString: process.env.DATABASE_URL },
  schema: "conversations"
});

const manager = createConversationManager({
  persistence,
  autoSave: true,
  saveInterval: 5000
});

2. Conversation Branching

Save and restore conversation branches:

const branch = await conversation.createBranch("experiment-1");
await branch.sendMessage("What if we try this approach?");

// Later restore main branch
await conversation.switchBranch("main");

3. Conversation Templates

Reusable conversation patterns:

const template = createConversationTemplate({
  name: "customer-onboarding",
  steps: [
    { type: "greeting", personalized: true },
    { type: "collect-info", fields: ["name", "email", "company"] },
    { type: "product-demo", interactive: true },
    { type: "follow-up", schedule: "+1 day" }
  ]
});

const conversation = await createFromTemplate(template, { 
  userId: "user_123" 
});

Performance Optimizations

Planned Improvements

1. Message Streaming

Efficient handling of large conversations:

const history = createConversationHistory({
  streaming: true,
  chunkSize: 100
});

// Stream messages instead of loading all
for await (const chunk of history.streamMessages()) {
  await processChunk(chunk);
}

2. Lazy Loading

Load context data on demand:

const context = createConversationContext({
  lazy: true,
  preload: ["user.id", "session.id"],
  loadOn: "access"
});

// Data loads only when accessed
const preferences = await context.state.user.preferences;

3. Intelligent Caching

Smart caching strategies:

const manager = createConversationManager({
  cache: {
    strategy: "lru",
    maxSize: "100mb",
    ttl: 3600,
    predictor: "ml-based" // Predicts what to cache
  }
});

Integration Enhancements

Planned Integrations

1. Native LLM Providers

Expanded provider support:

const llmService = baseLLMService({
  provider: "cohere", // New providers
  fallback: ["openai", "anthropic"],
  loadBalancing: "round-robin"
});

2. Vector Database Integration

For semantic memory:

const memory = createSemanticMemory({
  vectorDB: "pinecone",
  embedding: "openai-ada-002",
  namespace: `user:${userId}`
});

const context = createConversationContext({
  extensions: { memory }
});

// Semantic search through conversation history
const relevant = await context.memory.search(
  "previous discussions about pricing"
);

3. Workflow Engines

Integration with existing workflow systems:

const workflow = createWorkflowLoop({
  engine: "temporal",
  workflowId: "customer-support-flow",
  activities: {
    "send-email": emailActivity,
    "create-ticket": ticketActivity
  }
});

Developer Experience

Planned Improvements

1. Visual Debugging

Browser-based conversation debugger:

const conversation = createConversationLoop({
  debug: {
    enabled: true,
    port: 9229,
    visualizer: true
  }
});

// Opens browser debugger at http://localhost:9229

2. Conversation Playground

Interactive testing environment:

// CLI command
grid playground --agent ./my-agent.ts --tools ./tools

// Opens interactive playground for testing

3. Migration Tools

Automated migration between versions:

// CLI command
grid migrate --from 1.0 --to 2.0 --path ./src

// Automatically updates code to new API

Timeline

Phase 1: WorkflowLoop (Q1 2025)

• Basic autonomous, guided, hybrid modes
• Simple branching and conditions
• Alpha release for testing

Phase 2: Enhanced Tools (Q2 2025)

• Tool composition
• Versioning system
• Permission framework

Phase 3: Advanced State (Q3 2025)

• State schemas
• Synchronization
• Transformers

Phase 4: Production Features (Q4 2025)

• Built-in persistence
• Performance optimizations
• Additional integrations

Contributing

Grid is open to community contributions! Areas where we especially welcome help:

1. Provider Integrations - Add support for new LLM providers
2. Tool Libraries - Create reusable tool packages
3. Persistence Adapters - Build adapters for different databases
4. Workflow Templates - Share common workflow patterns

See our Contributing Guide for details.

Staying Updated

• Follow our GitHub repository
• Join our Discord community
• Subscribe to our newsletter
• Read our blog for updates

Migration Promise

We commit to:

• Semantic versioning
• Clear migration paths
• Backward compatibility within major versions
• Comprehensive migration guides
• Automated migration tools where possible

Next Steps

• Architecture Overview - Current architecture
• Building Custom Flows - Prepare for workflows
• Contributing - Help shape the future