aiwg/docs/releases/v2026.2.3-announcement.md

Cognitive architecture for AI-augmented software development with structured memory, ensemble validation, and closed-loop correction. FAIR-aligned artifacts, 84% cost reduction via human-in-the-loop, standards adopted by 100+ organizations.

# v2026.2.3 - "Deep Context" Release

**Released**: February 9, 2026

This release adds the RLM addon for recursive context decomposition, a daemon subsystem for background automation, bidirectional messaging integration, and first-class CLI addon support. Together these features extend AIWG's reach from interactive coding sessions into continuous background operation and multi-platform chat interfaces.

## Highlights

| What Changed | Why You Care |
|--------------|--------------|
| **RLM addon** | Process 10M+ tokens through recursive sub-agent decomposition |
| **Daemon mode** | Background file watching, cron scheduling, IPC, tmux management |
| **Messaging subsystem** | Bidirectional Slack, Discord, and Telegram bot integration |
| **CLI addon support** | `aiwg use rlm` — addons are first-class CLI targets |
| **Copilot RLM artifacts** | RLM agents, skills, and rules deploy to GitHub Copilot |

## RLM Addon — Recursive Language Model Processing

The RLM addon implements recursive context decomposition based on REF-089 (Zhang et al., 2026). When a task exceeds comfortable context window limits — scanning hundreds of files, analyzing entire codebases, or batch-processing large directories — RLM decomposes the work into manageable chunks processed by focused sub-agents, then aggregates results.

### Architecture

```
User Request (e.g., "find all TODO comments across the codebase")
    │
    ├── rlm-orchestrator: decomposes into chunks
    │   ├── rlm-chunk-processor: processes src/auth/**
    │   ├── rlm-chunk-processor: processes src/api/**
    │   ├── rlm-chunk-processor: processes src/models/**
    │   └── rlm-chunk-processor: processes src/utils/**
    │
    ├── rlm-aggregator: combines chunk results
    └── rlm-quality-validator: validates completeness
```

### Usage

```bash
# Deploy the addon
aiwg use rlm

# Query across large file sets
/rlm-query "src/**/*.ts" "Extract all exported interfaces" --model haiku

# Batch process files in parallel
/rlm-batch "src/components/*.tsx" "Add TypeScript types" --parallel 4

# Check processing status
/rlm-status
```

### What's Included

| Type | Count | Examples |
|------|-------|---------|
| Agents | 4 | rlm-orchestrator, rlm-chunk-processor, rlm-aggregator, rlm-quality-validator |
| Commands | 3 | /rlm-query, /rlm-batch, /rlm-status |
| Skills | 1 | rlm-mode (detects large-scale operations) |
| Rules | 2 | rlm-context-management, rlm-subagent-scoping |
| Schemas | 5 | rlm-config, rlm-chunk, rlm-result, rlm-cost, rlm-manifest |
| Docs | 2 | README, rlm-patterns |

### GitHub Copilot Integration

RLM artifacts automatically deploy to GitHub Copilot:

- `.github/agents/rlm-agent.yaml`, `rlm-batch.yaml`, `rlm-query.yaml`, `rlm-status.yaml`
- `.github/skills/rlm-mode/SKILL.md`
- `.github/copilot-rules/rlm-context-management.md`

## Daemon Mode

The daemon subsystem enables AIWG to run as a background process, watching files for changes and executing scheduled tasks without user interaction.

### Components

| Component | Purpose |
|-----------|---------|
| `daemon-main` | Core daemon lifecycle and process management |
| `ipc-server` / `ipc-client` | Inter-process communication between daemon and CLI |
| `agent-supervisor` | Manages long-running agent processes |
| `task-store` | Persistent task queue with priority scheduling |
| `repl-chat` | Interactive REPL for daemon sessions |
| `tmux-manager` | Terminal multiplexing for parallel sessions |
| `automation-engine` | Event-driven workflow triggers |

### Documentation

Full guide: [docs/daemon-guide.md](../daemon-guide.md)

## Messaging Subsystem

Bidirectional chat integration enables AIWG agents to communicate through Slack, Discord, and Telegram.

### Components

| Component | Purpose |
|-----------|---------|
| `chat-handler` | Bidirectional message routing between adapters and agents |
| `base adapter` | Unified interface for all messaging platforms |
| `telegram adapter` | Telegram Bot API integration |
| Slack adapter | Slack Events API integration |
| Discord adapter | Discord.js bot integration |
| `types` | Structured message type system |
| Hub wiring | Routes messages between adapters and agents |

### Documentation

Full guide: [docs/messaging-guide.md](../messaging-guide.md)

## CLI Addon Support

Addons are now first-class targets in the AIWG CLI, alongside frameworks.

```bash
# Before (only frameworks)
aiwg use sdlc
aiwg use marketing

# Now (frameworks AND addons)
aiwg use sdlc
aiwg use marketing
aiwg use rlm              # Deploy RLM addon
```

The `use` handler auto-detects whether a target is a framework or addon and deploys accordingly. Error messages have been updated to reflect addon support.

## Install / Upgrade

```bash
npm install -g aiwg@2026.2.3
```

## Links

- [CHANGELOG](../../CHANGELOG.md)
- [RLM Addon README](../../agentic/code/addons/rlm/README.md)
- [Daemon Guide](../daemon-guide.md)
- [Messaging Guide](../messaging-guide.md)
- [CLI Reference](../cli-reference.md)