diff --git a/.env.example b/.env.example
index 0782e2a4..94ce0582 100644
--- a/.env.example
+++ b/.env.example
@@ -66,19 +66,27 @@ FORGE_REQUIRE_PROJECT_CONFIG=true
 
 # =============================================================================
 # LLM Configuration
-# Supports Claude (via Anthropic API or Vertex AI) and Gemini (via Vertex AI)
+# Forge passes LangChain chat model instances into Deep Agents. Built-in
+# configuration supports direct Anthropic API credentials and Vertex AI-backed
+# model access. Additional LangChain chat models can be wired in by extending
+# the model factory.
 # =============================================================================
 
-# Option 1: Direct Anthropic API (Claude models only)
+# Option 1: Direct Anthropic API.
+LLM_API_KEY=
+# Backwards-compatible name for Anthropic direct API deployments.
 ANTHROPIC_API_KEY=
-# Option 2: Google Vertex AI (supports both Claude and Gemini)
+
+# Option 2: Google Vertex AI.
+VERTEX_PROJECT_ID=your-gcp-project-id
+VERTEX_REGION=us-east5
+# Backwards-compatible names for existing deployments.
 ANTHROPIC_VERTEX_PROJECT_ID=your-gcp-project-id
 ANTHROPIC_VERTEX_REGION=us-east5
 
 # Model for orchestrator (PRD, spec, epic planning)
-# Claude models: claude-opus-4-5@20251101, claude-sonnet-4-5@20250929, claude-haiku-4-5@20251001
-# Gemini models: gemini-2.5-pro, gemini-2.5-flash, gemini-3.1-pro-preview
-LLM_MODEL=claude-opus-4-5@20251101
+# Examples: gemini-3.5-flash, gemini-2.5-pro, claude-opus-4-5@20251101
+LLM_MODEL=claude-sonnet-4-5@20250929
 
 # Model for container tasks (code implementation)
 # Can use a different model than orchestrator (e.g., for cost/rate limit reasons)
diff --git a/containers/README.md b/containers/README.md
index 1ecc0834..c6a97f9e 100644
--- a/containers/README.md
+++ b/containers/README.md
@@ -46,8 +46,8 @@ Based on `mcr.microsoft.com/devcontainers/universal:linux` which provides:
 
 Additional packages installed:
 - `deepagents` - AI agent framework
-- `anthropic`, `langchain-anthropic` - Claude API access
-- `langchain-google-vertexai` - Vertex AI support (Claude and Gemini)
+- `anthropic`, `langchain-anthropic` - direct Anthropic API access
+- `langchain-google-vertexai` - Vertex AI model access
 - `langchain-mcp-adapters` - MCP server integration
 
 ## Image Configuration
@@ -104,10 +104,11 @@ Passed automatically by the orchestrator:
 
 | Variable | Description |
 |----------|-------------|
-| `ANTHROPIC_API_KEY` | Claude API key (direct API) |
-| `ANTHROPIC_VERTEX_PROJECT_ID` | GCP project for Vertex AI |
-| `ANTHROPIC_VERTEX_REGION` | Vertex AI region |
-| `LLM_MODEL` | Model to use (e.g., `claude-opus-4-5@20251101`, `gemini-2.5-pro`) |
+| `LLM_API_KEY` | Direct Anthropic API key |
+| `VERTEX_PROJECT_ID` | GCP project for Vertex AI |
+| `VERTEX_REGION` | Vertex AI region |
+| `ANTHROPIC_*` | Backwards-compatible aliases for existing deployments |
+| `LLM_MODEL` | Model to use (default: `claude-sonnet-4-5@20250929`; examples: `gemini-3.5-flash`, `gemini-2.5-pro`, `claude-opus-4-5@20251101`) |
 | `FORGE_SYSTEM_PROMPT_TEMPLATE` | System prompt template (interpolated by entrypoint) |
 | `GOOGLE_APPLICATION_CREDENTIALS` | Path to mounted gcloud credentials |
 | `GIT_USER_NAME` | Git author name for commits (default: `Forge`) |
@@ -136,9 +137,10 @@ Example: `forge-AISOS-189-installer-12345`
 
 ## Task Execution
 
-The entrypoint runs a Deep Agent with `LocalShellBackend`. Supported models:
-- **Claude** (via Anthropic API or Vertex AI): `claude-opus-4-5@20251101`, `claude-sonnet-4-5@20250929`
-- **Gemini** (via Vertex AI): `gemini-2.5-pro`, `gemini-2.5-flash`, `gemini-3.1-pro-preview`
+The entrypoint runs a Deep Agent with `LocalShellBackend`. Built-in model
+factory support covers direct Anthropic API credentials and Vertex AI-backed
+models. Because the agent receives a LangChain chat model instance, additional
+providers can be added by extending the model factory.
 
 The agent:
 1. Reads and understands the codebase
diff --git a/containers/entrypoint.py b/containers/entrypoint.py
index 29022265..4cc7cc8e 100644
--- a/containers/entrypoint.py
+++ b/containers/entrypoint.py
@@ -35,6 +35,7 @@
 if os.environ.get("LANGCHAIN_VERBOSE", "").lower() in ("true", "1", "yes"):
     try:
         from langchain_core.globals import set_debug, set_verbose
+
         set_verbose(True)
         set_debug(True)
         logger.info("LangChain verbose/debug mode enabled")
@@ -303,8 +304,10 @@ async def run_agent_task(
         guardrails: Repository guidelines.
         previous_task_keys: List of previously implemented task keys for handoff context.
     """
-    # Support both new (LLM_MODEL) and legacy (CLAUDE_MODEL) env var names
-    model_name = os.environ.get("LLM_MODEL") or os.environ.get("CLAUDE_MODEL", "claude-sonnet-4-5@20250929")
+    # Support both generic (LLM_MODEL) and legacy (CLAUDE_MODEL) env var names.
+    model_name = os.environ.get("LLM_MODEL") or os.environ.get(
+        "CLAUDE_MODEL", "claude-sonnet-4-5@20250929"
+    )
     logger.info(f"Implementing task: {task_summary}")
     logger.info(f"Model: {model_name}")
 
@@ -312,14 +315,18 @@ async def run_agent_task(
         from deepagents import create_deep_agent
         from deepagents.backends import LocalShellBackend
 
-        # Check for API credentials
-        api_key = os.environ.get("ANTHROPIC_API_KEY")
-        vertex_project = os.environ.get("ANTHROPIC_VERTEX_PROJECT_ID")
+        # Check for API credentials. ANTHROPIC_* names are accepted for
+        # compatibility with existing deployments and LangChain integrations.
+        api_key = os.environ.get("LLM_API_KEY") or os.environ.get("ANTHROPIC_API_KEY")
+        vertex_project = os.environ.get("VERTEX_PROJECT_ID") or os.environ.get(
+            "ANTHROPIC_VERTEX_PROJECT_ID"
+        )
+        vertex_region = os.environ.get("VERTEX_REGION") or os.environ.get(
+            "ANTHROPIC_VERTEX_REGION", "us-east5"
+        )
 
         if not api_key and not vertex_project:
-            logger.error(
-                "No API credentials found (ANTHROPIC_API_KEY or ANTHROPIC_VERTEX_PROJECT_ID)"
-            )
+            logger.error("No model backend credentials found (LLM_API_KEY or VERTEX_PROJECT_ID)")
             return False
 
         # Create the agent with local shell backend (enables git commands)
@@ -337,7 +344,7 @@ async def run_agent_task(
             workspace, task_key, task_summary, task_description, guardrails, previous_task_keys
         )
 
-        # Determine model type (Gemini vs Claude)
+        # Determine model family for the built-in LangChain model factories.
         is_gemini = model_name.lower().startswith(("gemini", "models/gemini"))
 
         # Get max tokens from env (default 16384)
@@ -345,26 +352,28 @@ async def run_agent_task(
 
         if vertex_project:
             if is_gemini:
-                # Gemini models via ChatGoogleGenerativeAI with Vertex AI backend
                 from langchain_google_genai import ChatGoogleGenerativeAI
 
-                logger.info(f"Using Gemini model: {model_name}, max_output_tokens={max_tokens}")
+                logger.info(
+                    f"Using Vertex AI Gemini model: {model_name}, max_output_tokens={max_tokens}"
+                )
                 model = ChatGoogleGenerativeAI(
                     model=model_name,
                     project=vertex_project,
-                    location=os.environ.get("ANTHROPIC_VERTEX_REGION", "us-east5"),
+                    location=vertex_region,
                     vertexai=True,
                     max_output_tokens=max_tokens,
                 )
             else:
-                # Claude models via ChatAnthropicVertex
                 from langchain_google_vertexai.model_garden import ChatAnthropicVertex
 
-                logger.info(f"Using Claude model: {model_name}, max_tokens={max_tokens}")
+                logger.info(
+                    f"Using Vertex AI Anthropic model: {model_name}, max_tokens={max_tokens}"
+                )
                 model = ChatAnthropicVertex(
                     model_name=model_name,
                     project=vertex_project,
-                    location=os.environ.get("ANTHROPIC_VERTEX_REGION", "us-east5"),
+                    location=vertex_region,
                     max_tokens=max_tokens,
                 )
         else:
@@ -374,7 +383,7 @@ async def run_agent_task(
 
             from langchain_anthropic import ChatAnthropic
 
-            logger.info(f"Using Claude model: {model_name}, max_tokens={max_tokens}")
+            logger.info(f"Using direct Anthropic model: {model_name}, max_tokens={max_tokens}")
             model = ChatAnthropic(
                 model=model_name,
                 api_key=api_key,
@@ -442,9 +451,7 @@ async def run_agent_task(
 
         # Run the agent (with Langfuse session context if enabled)
         initial_message = {
-            "messages": [
-                {"role": "user", "content": f"Implement this task:\n\n{task_description}"}
-            ]
+            "messages": [{"role": "user", "content": f"Implement this task:\n\n{task_description}"}]
         }
 
         if langfuse_enabled:
@@ -592,13 +599,18 @@ def main():
     # Ensure changes are committed (agent should have done this, but as fallback).
     # Skip if workspace is not a git repo — analysis tasks (RCA, reflection) write
     # artifacts to .forge/ without needing a commit.
-    is_git_repo = subprocess.run(
-        ["git", "rev-parse", "--is-inside-work-tree"],
-        cwd=workspace,
-        capture_output=True,
-    ).returncode == 0
+    is_git_repo = (
+        subprocess.run(
+            ["git", "rev-parse", "--is-inside-work-tree"],
+            cwd=workspace,
+            capture_output=True,
+        ).returncode
+        == 0
+    )
     if is_git_repo:
-        fallback_message = f"[{task_key}] {task_summary}\n\nAuto-committed by Forge container fallback."
+        fallback_message = (
+            f"[{task_key}] {task_summary}\n\nAuto-committed by Forge container fallback."
+        )
         if not git_commit(workspace, fallback_message):
             logger.error("Failed to commit changes")
             sys.exit(EXIT_TASK_FAILED)
diff --git a/docs/dev/setup.md b/docs/dev/setup.md
index 6cf4d39c..8c44121b 100644
--- a/docs/dev/setup.md
+++ b/docs/dev/setup.md
@@ -11,7 +11,7 @@ This page is a condensed reference. For the full walkthrough including payload-b
 | Podman | `brew install podman` / `dnf install podman` |
 | Docker Compose | Included with Docker Desktop or `brew install docker-compose` |
 
-External accounts needed: Jira Cloud, GitHub, and Anthropic API key (or Vertex AI).
+External accounts needed: Jira Cloud, GitHub, and LLM backend access through a direct model provider API or Vertex AI.
 
 ## Installation
 
@@ -33,9 +33,9 @@ JIRA_API_TOKEN=your-jira-api-token
 
 GITHUB_TOKEN=github_pat_your_token
 
-ANTHROPIC_API_KEY=sk-ant-your-key   # or Vertex AI — see developer guide
+LLM_API_KEY=your-anthropic-api-key  # or Vertex AI — see developer guide
 
-LLM_MODEL=claude-opus-4-5@20251101
+LLM_MODEL=claude-sonnet-4-5@20250929
 REDIS_URL=redis://localhost:6380/0
 ```
 
diff --git a/docs/developer-guide.md b/docs/developer-guide.md
index 8259cdb3..efeb4e72 100644
--- a/docs/developer-guide.md
+++ b/docs/developer-guide.md
@@ -30,7 +30,7 @@ Everything you need to run Forge locally, test it, observe what it's doing, and
 - **Docker Compose** — for Redis and API gateway (`dnf install docker-compose` / included with Docker Desktop)
 - **Jira Cloud** account with API access
 - **GitHub** account with a Personal Access Token (scopes: `repo`, `read:org`)
-- **Claude API key** (Anthropic direct) OR Google Cloud project with Vertex AI enabled
+- **LLM backend access** through a direct model provider API OR Google Cloud project with Vertex AI enabled
 
 ---
 
@@ -69,15 +69,15 @@ GITHUB_TOKEN=github_pat_your_token
 
 # LLM — choose one backend
 
-# Option A: Anthropic direct
-ANTHROPIC_API_KEY=sk-ant-your-key
+# Option A: Direct Anthropic API
+LLM_API_KEY=your-anthropic-api-key
 
-# Option B: Google Vertex AI (supports Claude + Gemini)
-ANTHROPIC_VERTEX_PROJECT_ID=your-gcp-project
-ANTHROPIC_VERTEX_REGION=us-east5
+# Option B: Google Vertex AI
+VERTEX_PROJECT_ID=your-gcp-project
+VERTEX_REGION=us-east5
 
 # Which model to use
-LLM_MODEL=claude-opus-4-5@20251101
+LLM_MODEL=claude-sonnet-4-5@20250929
 ```
 
 ---
@@ -506,7 +506,7 @@ forge_webhooks_failed_total
 # External API latency
 forge_external_api_latency_seconds{service="jira"}
 forge_external_api_latency_seconds{service="github"}
-forge_external_api_latency_seconds{service="claude"}
+forge_external_api_latency_seconds{service="llm"}
 ```
 
 ### Adding worker metrics to Prometheus
diff --git a/docs/getting-started.md b/docs/getting-started.md
index 08694afe..40bed257 100644
--- a/docs/getting-started.md
+++ b/docs/getting-started.md
@@ -9,7 +9,7 @@ Get Forge running locally in about 10 minutes.
 - **Docker Compose** — for Redis (`brew install docker-compose` / included with Docker Desktop)
 - **Jira Cloud** account with API access
 - **GitHub** Personal Access Token (scopes: `repo`, `read:org`)
-- **Claude API key** (Anthropic direct) or Google Cloud project with Vertex AI enabled
+- **LLM backend access** through a direct model provider API or Google Cloud project with Vertex AI enabled
 
 ## 1. Install
 
@@ -36,12 +36,12 @@ JIRA_API_TOKEN=your-jira-api-token
 # GitHub
 GITHUB_TOKEN=github_pat_your_token
 
-# LLM — choose one
-ANTHROPIC_API_KEY=sk-ant-your-key       # Anthropic direct
-# ANTHROPIC_VERTEX_PROJECT_ID=my-proj  # OR Vertex AI
-# ANTHROPIC_VERTEX_REGION=us-east5
+# LLM backend — choose one
+LLM_API_KEY=your-anthropic-api-key      # Direct Anthropic API
+# VERTEX_PROJECT_ID=my-proj            # OR Vertex AI
+# VERTEX_REGION=us-east5
 
-LLM_MODEL=claude-opus-4-5@20251101
+LLM_MODEL=claude-sonnet-4-5@20250929
 ```
 
 ## 3. Build the Container Image
diff --git a/docs/guide/pr-commands.md b/docs/guide/pr-commands.md
index 691cfb44..7403e035 100644
--- a/docs/guide/pr-commands.md
+++ b/docs/guide/pr-commands.md
@@ -59,7 +59,7 @@ Merge `main` into the PR branch and resolve any merge conflicts using AI. Use th
 3. Clones the repository and checks out the PR branch from the fork
 4. Attempts `git merge origin/main`
 5. If no conflicts: pushes the merge commit to the fork branch
-6. If conflicts: spawns a container with Claude to resolve them using the PR description and changed files as context
+6. If conflicts: spawns a container agent to resolve them using the PR description and changed files as context
 7. Verifies no conflict markers remain, commits, and force-pushes to the fork
 8. Returns the workflow to the node it was at before the rebase
 
diff --git a/docs/index.md b/docs/index.md
index b03712b7..08dfe6c8 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,6 +1,6 @@
 # Forge
 
-Forge automates the software development lifecycle from feature ideation through code delivery using AI-powered planning and execution. It connects Jira, GitHub, and Claude to transform tickets into shipped code with human approval gates at each stage.
+Forge automates the software development lifecycle from feature ideation through code delivery using AI-powered planning and execution. It connects Jira, GitHub, and Deep Agents-backed LangChain models to transform tickets into shipped code with human approval gates at each stage.
 
 ## How It Works
 
diff --git a/docs/reference/config.md b/docs/reference/config.md
index 72f94b5d..0f5ca68f 100644
--- a/docs/reference/config.md
+++ b/docs/reference/config.md
@@ -22,23 +22,28 @@ All configuration is via environment variables in `.env`. See `.env.example` in
 
 ### LLM
 
-Choose one backend:
+Choose one backend. Forge passes LangChain chat model instances into Deep Agents; the
+built-in factory supports direct Anthropic API credentials and Vertex AI-backed
+models, and can be extended for other LangChain chat model providers.
 
-=== "Anthropic Direct"
+=== "Direct Anthropic API"
 
     ```bash
-    ANTHROPIC_API_KEY=sk-ant-your-key
-    LLM_MODEL=claude-opus-4-5@20251101
+    LLM_API_KEY=your-anthropic-api-key
+    LLM_MODEL=claude-sonnet-4-5@20250929
     ```
 
 === "Google Vertex AI"
 
     ```bash
-    ANTHROPIC_VERTEX_PROJECT_ID=your-gcp-project
-    ANTHROPIC_VERTEX_REGION=us-east5
-    LLM_MODEL=claude-opus-4-5@20251101
+    VERTEX_PROJECT_ID=your-gcp-project
+    VERTEX_REGION=us-east5
+    LLM_MODEL=gemini-3.5-flash
     ```
 
+`ANTHROPIC_API_KEY`, `ANTHROPIC_VERTEX_PROJECT_ID`, and
+`ANTHROPIC_VERTEX_REGION` remain supported as backwards-compatible aliases.
+
 ### Redis
 
 | Variable | Default | Description |
diff --git a/src/forge/api/routes/metrics.py b/src/forge/api/routes/metrics.py
index 42c49656..852ec034 100644
--- a/src/forge/api/routes/metrics.py
+++ b/src/forge/api/routes/metrics.py
@@ -112,7 +112,7 @@
     [
         "service",
         "operation",
-    ],  # service: jira, github, claude; operation: get_issue, create_pr, etc.
+    ],  # service: jira, github, llm; operation: get_issue, create_pr, etc.
     buckets=[0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0, 30.0],
 )
 
@@ -216,7 +216,7 @@ def observe_external_api_latency(service: str, operation: str, duration: float)
     """Record latency of an external API call.
 
     Args:
-        service: External service name (jira, github, claude).
+        service: External service name (jira, github, llm).
         operation: Operation name (get_issue, create_pr, generate, etc.).
         duration: Duration in seconds.
     """
@@ -227,7 +227,7 @@ def record_external_api_error(service: str, operation: str, error_type: str) ->
     """Record an external API call error.
 
     Args:
-        service: External service name (jira, github, claude).
+        service: External service name (jira, github, llm).
         operation: Operation name.
         error_type: Type of error (timeout, rate_limit, auth, etc.).
     """
diff --git a/src/forge/cli.py b/src/forge/cli.py
index fcd0f109..fd980c68 100644
--- a/src/forge/cli.py
+++ b/src/forge/cli.py
@@ -675,13 +675,13 @@ async def cmd_health(_args: argparse.Namespace) -> int:
     else:
         print("[SKIP] Jira: API token not configured")
 
-    # Check Anthropic/Vertex
+    # Check model backend
     if settings.use_vertex_ai:
-        print(f"[OK] Using Vertex AI: {settings.anthropic_vertex_project_id}")
-    elif settings.anthropic_api_key.get_secret_value():
-        print("[OK] Using direct Anthropic API")
+        print(f"[OK] Using Vertex AI: {settings.resolved_vertex_project_id}")
+    elif settings.direct_llm_api_key.get_secret_value():
+        print("[OK] Using direct model provider API")
     else:
-        print("[WARN] No Claude API configured")
+        print("[WARN] No LLM backend configured")
 
     print("\nHealth check complete!")
     return 0
diff --git a/src/forge/config.py b/src/forge/config.py
index e1bc7db9..32733ef3 100644
--- a/src/forge/config.py
+++ b/src/forge/config.py
@@ -147,27 +147,36 @@ def known_repos(self) -> list[str]:
             return []
         return [r.strip() for r in self.github_known_repos.split(",") if r.strip()]
 
-    # Anthropic Configuration
-    # Option 1: Direct Anthropic API
+    # LLM provider configuration.
+    # Generic names are preferred for new deployments. ANTHROPIC_* names remain
+    # supported for compatibility with existing environments.
+    llm_api_key: SecretStr = Field(
+        default=SecretStr(""),
+        description="Direct Anthropic API key, when not using Vertex AI",
+    )
+    vertex_project_id: str = Field(
+        default="",
+        description="Google Cloud project ID for Vertex AI",
+    )
+    vertex_region: str = Field(
+        default="",
+        description="Google Cloud region for Vertex AI",
+    )
     anthropic_api_key: SecretStr = Field(
         default=SecretStr(""),
-        description="Anthropic API key for Claude (leave empty for Vertex AI)",
+        description="Deprecated alias for llm_api_key",
     )
-    # Option 2: Google Vertex AI (supports Claude and Gemini)
     anthropic_vertex_project_id: str = Field(
         default="",
-        description="Google Cloud project ID for Vertex AI",
+        description="Deprecated alias for vertex_project_id",
     )
     anthropic_vertex_region: str = Field(
         default="us-east5",
-        description="Google Cloud region for Vertex AI (e.g., us-east5)",
+        description="Deprecated alias for vertex_region",
     )
-    # Model configuration (supports Claude and Gemini on Vertex AI)
-    # Claude models: claude-opus-4-5@20251101, claude-sonnet-4-5@20250929, etc.
-    # Gemini models: gemini-2.5-pro, gemini-2.5-flash, gemini-3.1-pro-preview, etc.
     llm_model: str = Field(
         default="claude-sonnet-4-5@20250929",
-        description="Model for orchestrator (Claude or Gemini on Vertex AI)",
+        description="Model for orchestrator agents",
     )
     container_llm_model: str = Field(
         default="",
@@ -183,6 +192,23 @@ def container_model(self) -> str:
         """Get model for container execution, falling back to default model."""
         return self.container_llm_model or self.llm_model
 
+    @property
+    def direct_llm_api_key(self) -> SecretStr:
+        """Get the configured direct model provider API key."""
+        if self.llm_api_key.get_secret_value():
+            return self.llm_api_key
+        return self.anthropic_api_key
+
+    @property
+    def resolved_vertex_project_id(self) -> str:
+        """Get the configured Vertex AI project ID."""
+        return self.vertex_project_id or self.anthropic_vertex_project_id
+
+    @property
+    def resolved_vertex_region(self) -> str:
+        """Get the configured Vertex AI region."""
+        return self.vertex_region or self.anthropic_vertex_region
+
     # Backwards compatibility aliases
     @property
     def claude_model(self) -> str:
@@ -194,12 +220,12 @@ def detect_model_provider(model_name: str) -> str:
         """Detect model provider from model name.
 
         Returns:
-            'anthropic' for Claude models, 'google' for Gemini models.
+            'anthropic' for Anthropic models, 'google' for Gemini models.
         """
         model_lower = model_name.lower()
         if model_lower.startswith(("gemini", "models/gemini")):
             return "google"
-        # Default to anthropic for claude-* or unknown models
+        # Default to anthropic for claude-* or unknown direct-provider models.
         return "anthropic"
 
     # Langfuse Configuration
@@ -222,7 +248,7 @@ def detect_model_provider(model_name: str) -> str:
         description="Comma-separated list of TracingField names to include as Langfuse trace metadata",
     )
 
-    # Claude Agent SDK Configuration
+    # Agent Configuration
     agent_enable_tools: bool = Field(
         default=True,
         description="Enable agent tools (Read, Glob, Grep, WebSearch)",
@@ -397,9 +423,9 @@ def trace_metadata_fields(self) -> list["TracingField"]:
 
     @property
     def use_vertex_ai(self) -> bool:
-        """Check if using Vertex AI instead of direct Anthropic API."""
+        """Check if using Vertex AI instead of a direct model provider API."""
         return bool(
-            self.anthropic_vertex_project_id and not self.anthropic_api_key.get_secret_value()
+            self.resolved_vertex_project_id and not self.direct_llm_api_key.get_secret_value()
         )
 
 
diff --git a/src/forge/integrations/agents/agent.py b/src/forge/integrations/agents/agent.py
index 2b69f5a1..a4364030 100644
--- a/src/forge/integrations/agents/agent.py
+++ b/src/forge/integrations/agents/agent.py
@@ -36,7 +36,7 @@
 from forge.prompts import load_prompt, set_default_version
 from forge.skills.resolver import resolve_skill_paths
 
-# Optional Vertex AI support (Claude and Gemini)
+# Optional Vertex AI support
 try:
     from langchain_google_genai import ChatGoogleGenerativeAI
     from langchain_google_vertexai.model_garden import ChatAnthropicVertex
@@ -125,12 +125,13 @@ def __init__(self, settings: Settings | None = None):
         set_default_version(self.settings.prompt_version)
 
     def _ensure_api_key(self) -> None:
-        """Ensure Anthropic API key is available."""
+        """Ensure direct provider API key aliases are available."""
         if self.settings.use_vertex_ai:
             logger.info("Using Vertex AI backend")
-        elif not os.environ.get("ANTHROPIC_API_KEY"):
-            api_key = self.settings.anthropic_api_key.get_secret_value()
+        elif not os.environ.get("LLM_API_KEY") and not os.environ.get("ANTHROPIC_API_KEY"):
+            api_key = self.settings.direct_llm_api_key.get_secret_value()
             if api_key:
+                os.environ["LLM_API_KEY"] = api_key
                 os.environ["ANTHROPIC_API_KEY"] = api_key
 
     def _create_model(self, model_name: str | None = None) -> Any:
@@ -140,9 +141,9 @@ def _create_model(self, model_name: str | None = None) -> Any:
             model_name: Optional model name override. Uses settings if not provided.
 
         Returns:
-            A LangChain ChatModel instance (ChatAnthropic, ChatAnthropicVertex, or ChatVertexAI).
+            A LangChain chat model instance for Deep Agents.
         """
-        model = model_name or self.settings.claude_model
+        model = model_name or self.settings.llm_model
         provider = Settings.detect_model_provider(model)
 
         if self.settings.use_vertex_ai:
@@ -153,42 +154,43 @@ def _create_model(self, model_name: str | None = None) -> Any:
                 )
 
             if provider == "google":
-                # Gemini models via ChatGoogleGenerativeAI with Vertex AI backend
                 logger.info(
-                    f"Creating ChatGoogleGenerativeAI (Gemini) model: {model} "
-                    f"in {self.settings.anthropic_vertex_region}, max_output_tokens={self.settings.llm_max_tokens}"
+                    f"Creating Vertex AI Gemini model: {model} "
+                    f"in {self.settings.resolved_vertex_region}, "
+                    f"max_output_tokens={self.settings.llm_max_tokens}"
                 )
                 return ChatGoogleGenerativeAI(
                     model=model,
-                    project=self.settings.anthropic_vertex_project_id,
-                    location=self.settings.anthropic_vertex_region,
+                    project=self.settings.resolved_vertex_project_id,
+                    location=self.settings.resolved_vertex_region,
                     vertexai=True,
                     max_output_tokens=self.settings.llm_max_tokens,
                 )
             else:
-                # Claude models via ChatAnthropicVertex
                 logger.info(
-                    f"Creating ChatAnthropicVertex model: {model} "
-                    f"in {self.settings.anthropic_vertex_region}, max_tokens={self.settings.llm_max_tokens}"
+                    f"Creating Vertex AI Anthropic model: {model} "
+                    f"in {self.settings.resolved_vertex_region}, "
+                    f"max_tokens={self.settings.llm_max_tokens}"
                 )
                 return ChatAnthropicVertex(
                     model_name=model,
-                    project=self.settings.anthropic_vertex_project_id,
-                    location=self.settings.anthropic_vertex_region,
+                    project=self.settings.resolved_vertex_project_id,
+                    location=self.settings.resolved_vertex_region,
                     max_tokens=self.settings.llm_max_tokens,
                 )
         else:
             if provider == "google":
                 raise ValueError(
                     f"Gemini model '{model}' requires Vertex AI. "
-                    "Set ANTHROPIC_VERTEX_PROJECT_ID or use a Claude model."
+                    "Set VERTEX_PROJECT_ID or ANTHROPIC_VERTEX_PROJECT_ID."
                 )
             logger.info(
-                f"Creating ChatAnthropic model: {model}, max_tokens={self.settings.llm_max_tokens}"
+                f"Creating direct Anthropic model: {model}, "
+                f"max_tokens={self.settings.llm_max_tokens}"
             )
             return ChatAnthropic(
                 model=model,
-                api_key=self.settings.anthropic_api_key.get_secret_value(),
+                api_key=self.settings.direct_llm_api_key.get_secret_value(),
                 max_tokens=self.settings.llm_max_tokens,
             )
 
@@ -761,7 +763,7 @@ async def run_task(
             **(context or {}),
             **(trace_context or {}),
             "system_prompt_length": len(system_prompt),
-            "llm_model": self.settings.claude_model,
+            "llm_model": self.settings.llm_model,
         }
         trace_tags, trace_metadata = resolve_trace_fields(trace_state)
 
@@ -889,7 +891,8 @@ def _get_setting_value(self, var_name: str) -> str:
             "JIRA_DOMAIN": lambda: self.settings.jira_domain_resolved,
             "ATLASSIAN_AUTH_BASE64": lambda: self.settings.atlassian_auth_base64,
             "AGENT_WORKING_DIRECTORY": lambda: self.settings.agent_working_directory or os.getcwd(),
-            "ANTHROPIC_API_KEY": lambda: self.settings.anthropic_api_key.get_secret_value(),
+            "LLM_API_KEY": lambda: self.settings.direct_llm_api_key.get_secret_value(),
+            "ANTHROPIC_API_KEY": lambda: self.settings.direct_llm_api_key.get_secret_value(),
         }
 
         if var_name in var_mapping:
diff --git a/src/forge/integrations/langfuse/tracing.py b/src/forge/integrations/langfuse/tracing.py
index 9b3086e5..048ac2a2 100644
--- a/src/forge/integrations/langfuse/tracing.py
+++ b/src/forge/integrations/langfuse/tracing.py
@@ -227,8 +227,8 @@ def trace_llm_call(
     Note: For LangChain/Deep Agents, use get_langfuse_config() instead
     and pass the callbacks via the config parameter.
 
-    This context manager is kept for backwards compatibility with
-    direct Anthropic API calls.
+    This context manager is kept for backwards compatibility with direct
+    provider API calls.
 
     Args:
         name: Name of the LLM operation.
diff --git a/src/forge/main.py b/src/forge/main.py
index 0826a7fa..5920cf7c 100644
--- a/src/forge/main.py
+++ b/src/forge/main.py
@@ -64,7 +64,7 @@ def create_app() -> FastAPI:
 
 - **Webhook Gateway**: Receives events from Jira and GitHub
 - **Workflow Orchestration**: LangGraph-based state machine
-- **AI Integration**: Claude-powered planning and code generation
+- **AI Integration**: Deep Agents-backed planning and code generation
 - **Multi-repo Support**: Concurrent execution across repositories
 
 ### Workflow
diff --git a/src/forge/sandbox/runner.py b/src/forge/sandbox/runner.py
index 5d81afa1..8a17e3fa 100644
--- a/src/forge/sandbox/runner.py
+++ b/src/forge/sandbox/runner.py
@@ -118,14 +118,20 @@ def _build_env_vars(
         """
         env = {}
 
-        # Pass Anthropic credentials
-        if self.settings.anthropic_api_key.get_secret_value():
-            env["ANTHROPIC_API_KEY"] = self.settings.anthropic_api_key.get_secret_value()
+        # Pass direct model provider credentials. Keep ANTHROPIC_API_KEY for
+        # LangChain's Anthropic integration and older container images.
+        direct_api_key = self.settings.direct_llm_api_key.get_secret_value()
+        if direct_api_key:
+            env["LLM_API_KEY"] = direct_api_key
+            env["ANTHROPIC_API_KEY"] = direct_api_key
 
         # Pass Vertex AI credentials
         if self.settings.use_vertex_ai:
-            env["ANTHROPIC_VERTEX_PROJECT_ID"] = self.settings.anthropic_vertex_project_id
-            env["ANTHROPIC_VERTEX_REGION"] = self.settings.anthropic_vertex_region
+            env["VERTEX_PROJECT_ID"] = self.settings.resolved_vertex_project_id
+            env["VERTEX_REGION"] = self.settings.resolved_vertex_region
+            # Backwards-compatible names consumed by older container entrypoints.
+            env["ANTHROPIC_VERTEX_PROJECT_ID"] = self.settings.resolved_vertex_project_id
+            env["ANTHROPIC_VERTEX_REGION"] = self.settings.resolved_vertex_region
             # GOOGLE_APPLICATION_CREDENTIALS will be set if we mount gcloud creds
             env["GOOGLE_APPLICATION_CREDENTIALS"] = (
                 "/root/.config/gcloud/application_default_credentials.json"
diff --git a/src/forge/utils/__init__.py b/src/forge/utils/__init__.py
index ae87a6b3..d34703b1 100644
--- a/src/forge/utils/__init__.py
+++ b/src/forge/utils/__init__.py
@@ -19,6 +19,7 @@
     ANTHROPIC_RETRY_CONFIG,
     GITHUB_RETRY_CONFIG,
     JIRA_RETRY_CONFIG,
+    LLM_RETRY_CONFIG,
     RetryableError,
     RetryConfig,
     calculate_delay,
@@ -41,6 +42,7 @@
     "ANTHROPIC_RETRY_CONFIG",
     "GITHUB_RETRY_CONFIG",
     "JIRA_RETRY_CONFIG",
+    "LLM_RETRY_CONFIG",
     "RetryConfig",
     "RetryableError",
     "calculate_delay",
diff --git a/src/forge/utils/logging.py b/src/forge/utils/logging.py
index 43ddc55e..97d45ccb 100644
--- a/src/forge/utils/logging.py
+++ b/src/forge/utils/logging.py
@@ -221,7 +221,7 @@ def log_api_call(
 
     Args:
         logger: Logger to use.
-        service: Service name (jira, github, anthropic).
+        service: Service name (jira, github, llm).
         method: HTTP method.
         endpoint: API endpoint.
         status_code: Response status code.
diff --git a/src/forge/utils/rate_limiter.py b/src/forge/utils/rate_limiter.py
index 52ee4805..7e6b7d60 100644
--- a/src/forge/utils/rate_limiter.py
+++ b/src/forge/utils/rate_limiter.py
@@ -97,7 +97,12 @@ def __init__(self) -> None:
                 requests_per_second=1.0,
                 burst_limit=20,
             ),
-            # Anthropic: varies by tier, conservative default
+            # LLM providers vary by tier; keep a conservative default.
+            "llm": RateLimitConfig(
+                requests_per_second=0.5,
+                burst_limit=5,
+            ),
+            # Backwards-compatible service key for existing callers.
             "anthropic": RateLimitConfig(
                 requests_per_second=0.5,
                 burst_limit=5,
@@ -130,7 +135,7 @@ async def acquire(self, service: str, tokens: int = 1) -> None:
         Blocks until tokens are available.
 
         Args:
-            service: Service name (jira, github, anthropic).
+            service: Service name (jira, github, llm).
             tokens: Number of tokens to acquire.
         """
         bucket = self._get_bucket(service)
diff --git a/src/forge/utils/retry.py b/src/forge/utils/retry.py
index 42d12b3a..f8949b0c 100644
--- a/src/forge/utils/retry.py
+++ b/src/forge/utils/retry.py
@@ -186,7 +186,7 @@ def __init__(self, message: str, original: Exception | None = None):
     ),
 )
 
-ANTHROPIC_RETRY_CONFIG = RetryConfig(
+LLM_RETRY_CONFIG = RetryConfig(
     max_attempts=5,
     initial_delay=5.0,
     max_delay=120.0,
@@ -197,3 +197,6 @@ def __init__(self, message: str, original: Exception | None = None):
         RetryableError,
     ),
 )
+
+# Backwards-compatible alias for existing imports.
+ANTHROPIC_RETRY_CONFIG = LLM_RETRY_CONFIG
diff --git a/src/forge/workflow/nodes/ci_evaluator.py b/src/forge/workflow/nodes/ci_evaluator.py
index 144df2b8..669142fb 100644
--- a/src/forge/workflow/nodes/ci_evaluator.py
+++ b/src/forge/workflow/nodes/ci_evaluator.py
@@ -250,7 +250,7 @@ async def attempt_ci_fix(state: WorkflowState) -> WorkflowState:
 
     This node:
     1. Extracts error information from failed checks
-    2. Invokes Claude to generate a fix
+    2. Invokes the configured LLM backend to generate a fix
     3. Applies the fix and pushes
     4. Routes back to CI evaluation
 
diff --git a/src/forge/workflow/nodes/epic_decomposition.py b/src/forge/workflow/nodes/epic_decomposition.py
index 7081ee3b..df264354 100644
--- a/src/forge/workflow/nodes/epic_decomposition.py
+++ b/src/forge/workflow/nodes/epic_decomposition.py
@@ -35,7 +35,7 @@ async def decompose_epics(state: WorkflowState) -> WorkflowState:
 
     This node:
     1. Reads the approved specification from state
-    2. Generates 2-5 cohesive Epics using Claude
+    2. Generates 2-5 cohesive Epics using the configured LLM backend
     3. Creates Epic tickets in Jira linked to parent Feature
     4. Transitions Feature to "Pending Plan Approval"
 
@@ -125,7 +125,7 @@ async def decompose_epics(state: WorkflowState) -> WorkflowState:
             "feedback": state.get("feedback_comment", ""),
         }
 
-        # Generate Epic breakdown using Claude - primary operation
+        # Generate Epic breakdown using the configured LLM backend - primary operation
         epics_data = await agent.generate_epics(spec_content, context)
 
         if not epics_data:
diff --git a/src/forge/workflow/nodes/prd_generation.py b/src/forge/workflow/nodes/prd_generation.py
index 61f2a461..fde0f958 100644
--- a/src/forge/workflow/nodes/prd_generation.py
+++ b/src/forge/workflow/nodes/prd_generation.py
@@ -167,7 +167,7 @@ async def generate_prd(state: WorkflowState) -> WorkflowState:
 
     This node:
     1. Reads the current Jira issue description
-    2. Generates a structured PRD using Claude
+    2. Generates a structured PRD using the configured LLM backend
     3. Updates the Jira description with the PRD
     4. Transitions the ticket to "Pending PRD Approval"
 
@@ -216,7 +216,7 @@ async def generate_prd(state: WorkflowState) -> WorkflowState:
             "project_key": issue.project_key,
         }
 
-        # Generate PRD using Claude - primary operation
+        # Generate PRD using the configured LLM backend - primary operation
         prd_content = await agent.generate_prd(raw_requirements, context)
 
         # Publish PRD - either as GitHub PR or Jira update
diff --git a/src/forge/workflow/nodes/spec_generation.py b/src/forge/workflow/nodes/spec_generation.py
index 396fe78f..81b91fb6 100644
--- a/src/forge/workflow/nodes/spec_generation.py
+++ b/src/forge/workflow/nodes/spec_generation.py
@@ -184,7 +184,7 @@ async def generate_spec(state: WorkflowState) -> WorkflowState:
             "retry_count": state.get("retry_count", 0),
         }
 
-        # Generate specification using Claude - primary operation
+        # Generate specification using the configured LLM backend - primary operation
         spec_content = await agent.generate_spec(prd_content, context)
 
         # Publish spec — either as GitHub PR or Jira update
diff --git a/src/forge/workflow/nodes/task_generation.py b/src/forge/workflow/nodes/task_generation.py
index 26d6bbda..b9f84707 100644
--- a/src/forge/workflow/nodes/task_generation.py
+++ b/src/forge/workflow/nodes/task_generation.py
@@ -22,7 +22,7 @@ async def generate_tasks(state: WorkflowState) -> WorkflowState:
 
     This node:
     1. Iterates through all Epics in epic_keys
-    2. Generates Tasks for each Epic using Claude
+    2. Generates Tasks for each Epic using the configured LLM backend
     3. Creates Task tickets in Jira with repository labels
     4. Updates state with task tracking
 
@@ -369,7 +369,7 @@ def _parse_tasks_response(response: str) -> list[dict[str, str]]:
     """Parse Task generation response into structured data.
 
     Args:
-        response: Raw response from Claude.
+        response: Raw response from the configured LLM backend.
 
     Returns:
         List of Task dicts.
diff --git a/src/forge/workspace/git_ops.py b/src/forge/workspace/git_ops.py
index f7b3fea2..be4b50fe 100644
--- a/src/forge/workspace/git_ops.py
+++ b/src/forge/workspace/git_ops.py
@@ -240,7 +240,7 @@ def commit(self, message: str, author_name: str = "Forge") -> bool:
             "-m",
             message,
             "--author",
-            f"{author_name} <forge@noreply.anthropic.com>",
+            f"{author_name} <forge@example.com>",
         )
         logger.info(f"Committed: {message[:50]}...")
         return True
diff --git a/tests/unit/test_config_prd.py b/tests/unit/test_config_prd.py
index 13d5c78c..3fc27e48 100644
--- a/tests/unit/test_config_prd.py
+++ b/tests/unit/test_config_prd.py
@@ -1,11 +1,31 @@
 """Tests for PRD approval configuration settings."""
 
+import pytest
+
 from forge.config import Settings
 
 
+@pytest.fixture(autouse=True)
+def clear_prd_proposal_env(monkeypatch):
+    monkeypatch.delenv("PRD_PROPOSALS_REPO", raising=False)
+    monkeypatch.delenv("PRD_PROPOSALS_PATH", raising=False)
+    monkeypatch.delenv("LLM_API_KEY", raising=False)
+    monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
+    monkeypatch.delenv("VERTEX_PROJECT_ID", raising=False)
+    monkeypatch.delenv("VERTEX_REGION", raising=False)
+    monkeypatch.delenv("ANTHROPIC_VERTEX_PROJECT_ID", raising=False)
+    monkeypatch.delenv("ANTHROPIC_VERTEX_REGION", raising=False)
+    monkeypatch.delenv("LLM_MODEL", raising=False)
+    monkeypatch.delenv("CONTAINER_LLM_MODEL", raising=False)
+
+
+def make_settings(**kwargs) -> Settings:
+    return Settings(_env_file=None, **kwargs)
+
+
 class TestPrdApprovalConfig:
     def test_default_proposals_repo_is_empty(self):
-        settings = Settings(
+        settings = make_settings(
             jira_base_url="https://test.atlassian.net",
             jira_api_token="test",
             jira_user_email="test@example.com",
@@ -15,7 +35,7 @@ def test_default_proposals_repo_is_empty(self):
         assert settings.prd_proposals_repo == ""
 
     def test_default_proposals_path(self):
-        settings = Settings(
+        settings = make_settings(
             jira_base_url="https://test.atlassian.net",
             jira_api_token="test",
             jira_user_email="test@example.com",
@@ -25,7 +45,7 @@ def test_default_proposals_path(self):
         assert settings.prd_proposals_path == ""
 
     def test_proposals_repo_can_be_set_as_global_fallback(self):
-        settings = Settings(
+        settings = make_settings(
             jira_base_url="https://test.atlassian.net",
             jira_api_token="test",
             jira_user_email="test@example.com",
@@ -34,3 +54,56 @@ def test_proposals_repo_can_be_set_as_global_fallback(self):
             prd_proposals_repo="org/proposals",
         )
         assert settings.prd_proposals_repo == "org/proposals"
+
+
+class TestLlmConfig:
+    def test_default_model_is_direct_anthropic_compatible(self):
+        settings = make_settings(
+            jira_base_url="https://test.atlassian.net",
+            jira_api_token="test",
+            jira_user_email="test@example.com",
+            github_token="test",
+        )
+
+        assert settings.llm_model == "claude-sonnet-4-5@20250929"
+        assert Settings.detect_model_provider(settings.llm_model) == "anthropic"
+
+    def test_generic_direct_api_key_takes_precedence(self):
+        settings = make_settings(
+            jira_base_url="https://test.atlassian.net",
+            jira_api_token="test",
+            jira_user_email="test@example.com",
+            github_token="test",
+            llm_api_key="generic-key",
+            anthropic_api_key="legacy-key",
+        )
+
+        assert settings.direct_llm_api_key.get_secret_value() == "generic-key"
+        assert settings.use_vertex_ai is False
+
+    def test_legacy_direct_api_key_still_works(self):
+        settings = make_settings(
+            jira_base_url="https://test.atlassian.net",
+            jira_api_token="test",
+            jira_user_email="test@example.com",
+            github_token="test",
+            anthropic_api_key="legacy-key",
+        )
+
+        assert settings.direct_llm_api_key.get_secret_value() == "legacy-key"
+
+    def test_generic_vertex_settings_take_precedence(self):
+        settings = make_settings(
+            jira_base_url="https://test.atlassian.net",
+            jira_api_token="test",
+            jira_user_email="test@example.com",
+            github_token="test",
+            vertex_project_id="generic-project",
+            vertex_region="europe-west1",
+            anthropic_vertex_project_id="legacy-project",
+            anthropic_vertex_region="us-east5",
+        )
+
+        assert settings.resolved_vertex_project_id == "generic-project"
+        assert settings.resolved_vertex_region == "europe-west1"
+        assert settings.use_vertex_ai is True