diff --git a/README.md b/README.md
index 58bf59d..3b2ddc0 100644
--- a/README.md
+++ b/README.md
@@ -16,6 +16,49 @@ We recommend using python 3.10, 3.11 or 3.12 and also using a virtual environmen
 pip install terratorch-iterate
 ```
 
+### New instructions for iterate v0.3
+Iterate v0.3 can optimize over arbitrary code running on arbitrary workload managers. 
+Slurm and LSF are supported, Kubernetes/OpenShift and PBS coming soon.
+
+From version 0.3 on the current iterate can be used using `iterate-classig`. Here are some usage examples
+
+#### Prerequisites
+mkdir deleteme.iterate
+cd deleteme.iterate
+python -m venv .venv
+source ./venv/bin/activate
+wget https://raw.githubusercontent.com/terrastackai/iterate/refs/heads/main/examples/bumpy_function.py
+wget https://raw.githubusercontent.com/terrastackai/iterate/refs/heads/main/examples/bumpy_hpo.yaml
+pip install terratorch-iterate==0.3
+
+#### Run locally
+```
+iterate \
+        --script bumpy_function.py \
+        --root-dir . \
+        --optuna-study-name terratorch_hpo_nas_2 \
+        --optuna-db-path "sqlite:///iterate_study.db" \
+        --hpo-yaml bumpy_hpo.yaml \
+        --wlm none \
+        --metric yval
+```
+#### Run on LSF
+```
+iterate \
+        --script bumpy_function.py \
+        --root-dir . \
+        --optuna-study-name terratorch_hpo_nas_2 \
+        --optuna-db-path "sqlite:///iterate_study.db" \
+        --hpo-yaml bumpy_hpo.yaml \
+        --wlm lsf \
+        --metric yval \
+        --gpu-count 0
+```
+#### Useful commands
+```
+pip install optuna-dashboard
+optuna-dashboard --host 0.0.0.0 sqlite:///iterate_study.db
+```
 ### Suggested setup for development
 
 ```sh
diff --git a/examples/bumpy_function.py b/examples/bumpy_function.py
new file mode 100644
index 0000000..e098d76
--- /dev/null
+++ b/examples/bumpy_function.py
@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+import argparse
+import math
+
+
+def bumpy_function_3d(
+    x, y, z,
+    global_mu, global_sigma,
+    mu_rest, sigma_rest, amps_rest,
+):
+    """
+    3D smooth multimodal function with:
+    - one global optimum = 1 at global_mu = (mx,my,mz)
+    - multiple local optima < 1
+
+    f(p) = 1 - Π_k (1 - a_k * exp(-||p - mu_k||^2 / (2 sigma_k^2)))
+    """
+
+    def sqdist(p, q):
+        return (p[0] - q[0])**2 + (p[1] - q[1])**2 + (p[2] - q[2])**2
+
+    p = (x, y, z)
+
+    # Global peak (amplitude = 1)
+    val = 1.0 - math.exp(
+        -sqdist(p, global_mu) / (2.0 * global_sigma**2)
+    )
+
+    # Local peaks
+    for mu_k, sig_k, a_k in zip(mu_rest, sigma_rest, amps_rest):
+        term = 1.0 - a_k * math.exp(
+            -sqdist(p, mu_k) / (2.0 * sig_k**2)
+        )
+        val *= term
+
+    return 1.0 - val
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser("Evaluate the 3D bumpy multimodal function.")
+
+    parser.add_argument("--x", type=float, required=True)
+    parser.add_argument("--y", type=float, required=True)
+    parser.add_argument("--z", type=float, required=True)
+    parser.add_argument("--trial-number", type=int, default=0)
+
+    parser.add_argument(
+        "--global-mu",
+        type=float,
+        nargs=3,
+        default=[0.0, 0.0, 0.0],
+        metavar=("MX", "MY", "MZ"),
+    )
+    parser.add_argument("--global-sigma", type=float, default=0.7)
+
+    parser.add_argument(
+        "--mu-rest",
+        type=float,
+        nargs="*",
+        default=[-2.0, 0.0, 0.0,  2.0, 0.0, 0.0],
+        help="Flat list of (x y z) triplets",
+    )
+    parser.add_argument(
+        "--sigma-rest",
+        type=float,
+        nargs="*",
+        default=[0.6, 0.6],
+    )
+    parser.add_argument(
+        "--amps-rest",
+        type=float,
+        nargs="*",
+        default=[0.5, 0.8],
+    )
+
+    args = parser.parse_args()
+
+    mu_rest = [
+        tuple(args.mu_rest[i:i+3])
+        for i in range(0, len(args.mu_rest), 3)
+    ]
+
+    yval = bumpy_function_3d(
+        x=args.x,
+        y=args.y,
+        z=args.z,
+        global_mu=tuple(args.global_mu),
+        global_sigma=args.global_sigma,
+        mu_rest=mu_rest,
+        sigma_rest=args.sigma_rest,
+        amps_rest=args.amps_rest,
+    )
+
+    print(f'yval: {yval}, trial_number: {args.trial_number}')
diff --git a/examples/bumpy_hpo.yaml b/examples/bumpy_hpo.yaml
new file mode 100644
index 0000000..70a16bf
--- /dev/null
+++ b/examples/bumpy_hpo.yaml
@@ -0,0 +1,30 @@
+# =======================
+# Static parameters - passed to the underlying training script as is
+# =======================  
+  
+static:
+  global-mu: 23 42 66
+  
+# ========================
+# Training hyperparameters - evaluated by optuna and passed to the underlying training script
+# ========================
+
+hpo:
+  x:
+    type: float
+    low: 1
+    high: 100
+    log: true
+
+  y:
+    type: float
+    low: 1
+    high: 100
+    log: true
+
+  z:
+    type: float
+    low: 1
+    high: 100
+    log: true
+
diff --git a/pyproject.toml b/pyproject.toml
index 5c4fd83..019a146 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,7 @@ include = ["terratorch_iterate*"]
 [project]
 
 name = "terratorch-iterate"
-version = "0.2.3"
+version = "0.3"
 requires-python = ">= 3.11"
 description = "A terratorch's plugin for benchmarking and hyperparameter optimization"
 authors = [
@@ -77,8 +77,8 @@ dependencies = [
 ]
 
 [project.urls]
-Homepage = "https://github.com/IBM/terratorch-iterate"
-Issues = "https://github.com/IBM/terratorch-iterate/issues"
+Homepage = "https://github.com/terrastackai/iterate"
+Issues = "https://github.com/terrastackai/iterate/issues"
 
 [project.optional-dependencies]
 dev = [
@@ -113,7 +113,8 @@ line-length = 88
 skip-string-normalization = true
 
 [project.scripts]
-iterate = "terratorch_iterate.main:main"
+iterate-classic = "terratorch_iterate.main:main"
+iterate = "terratorch_iterate.iterate2:main"
 
 [tool.isort]
 multi_line_output = 3
diff --git a/terratorch_iterate/iterate2.py b/terratorch_iterate/iterate2.py
new file mode 100644
index 0000000..b9741bf
--- /dev/null
+++ b/terratorch_iterate/iterate2.py
@@ -0,0 +1,387 @@
+#!/usr/bin/env python3
+
+import argparse
+import json
+import os
+import subprocess
+import re
+from pathlib import Path
+from typing import Dict, Any, Optional, Literal
+
+import optuna
+import yaml
+
+# ============================================================
+# CLI
+# ============================================================
+
+def parse_args():
+    parser = argparse.ArgumentParser(
+        description="Generic Optuna HPO launcher with pluggable execution backend"
+    )
+
+    # ------------------------
+    # Execution config
+    # ------------------------
+    parser.add_argument("--script", required=True, help="Training script to execute")
+    parser.add_argument("--root-dir", default=None, help="Root dir (derived if omitted)")
+    parser.add_argument("--venv", default=".venv", help="Virtualenv dir, default: .venv (set empty to disable)")
+    parser.add_argument(
+        "--wlm",
+        choices=["lsf", "slurm", "openshift", "none"],
+        default="none",
+        help="Workload manager",
+    )
+    parser.add_argument("--gpu-count", type=int, default=1, help="GPUs per trial")
+    parser.add_argument("--cpu-count", type=int, default=4, help="CPUs per trial")
+    parser.add_argument("--mem-gb", type=int, default=128, help="Memory (GB) per trial")
+
+    # ------------------------
+    # Optuna config
+    # ------------------------
+    parser.add_argument("--optuna-study-name", required=True)
+    parser.add_argument("--optuna-db-path", required=True)
+    parser.add_argument("--optuna-n-trials", type=int, default=100)
+
+    # ------------------------
+    # HPO space
+    # ------------------------
+    parser.add_argument(
+        "--hpo-json",
+        type=str,
+        default=None,
+        help="HPO search space as JSON string",
+    )
+    parser.add_argument(
+        "--hpo-yaml",
+        type=str,
+        default=None,
+        help="HPO search space YAML file",
+    )
+
+    # ------------------------
+    # Static arguments (passed to every trial)
+    # ------------------------
+    parser.add_argument(
+        "--static-args-json",
+        type=str,
+        default=None,
+        help="Static arguments as JSON string (key-value pairs)",
+    )
+    parser.add_argument(
+        "--static-args-yaml",
+        type=str,
+        default=None,
+        help="Static arguments YAML file (key-value pairs)",
+    )
+
+    # ------------------------
+    # Metric extraction
+    # ------------------------
+    parser.add_argument(
+        "--metric",
+        default="val/F1_Score",
+        help="Metric name to extract from logs",
+    )
+
+    return parser.parse_args()
+
+
+# ============================================================
+# PATH RESOLUTION
+# ============================================================
+
+def resolve_paths(script: str, root_dir: Optional[str]):
+    script_path = Path(script).resolve()
+
+    if root_dir is None:
+        root_dir = script_path.parent.parent
+
+    return script_path, Path(root_dir).resolve()
+
+
+# ============================================================
+# WORKLOAD MANAGER ABSTRACTION
+# ============================================================
+
+def build_launcher_command(
+    *,
+    wlm: Literal["lsf", "slurm", "openshift", "none"],
+    cmd: str,
+    trial_id: int,
+    out_file: str,
+    err_file: str,
+    gpu_count: int = 1,
+    cpu_count: int = 4,
+    mem_gb: int = 128,
+):
+    if wlm == "lsf":
+        if gpu_count > 1:
+            return (
+                f"bsub -gpu num={gpu_count} -K "
+                f"-o {out_file} -e {err_file} "
+                f"-R \"rusage[ngpus={gpu_count}, cpu={cpu_count}, mem={mem_gb}GB]\" "
+                f"-J hpo_trial_{trial_id} "
+                f"\"{cmd}\""
+            )
+        else:
+            return (
+                f"bsub -K "
+                f"-o {out_file} -e {err_file} "
+                f"-R \"rusage[cpu={cpu_count}, mem={mem_gb}GB]\" "
+                f"-J hpo_trial_{trial_id} "
+                f"\"{cmd}\""
+            )
+
+    if wlm == "slurm":
+        return (
+            f"srun --gres=gpu:{gpu_count} --cpus-per-task={cpu_count} --mem={mem_gb}G "
+            f"--job-name=hpo_trial_{trial_id} "
+            f"--output={out_file} --error={err_file} "
+            f"bash -c \"{cmd}\""
+        )
+
+    if wlm == "openshift":
+        raise NotImplementedError("OpenShift launcher not implemented yet")
+
+    if wlm == "none":
+        return f'bash -c "{cmd} > {out_file} 2> {err_file}"'
+
+    raise ValueError(f"Unknown workload manager: {wlm}")
+
+
+# ============================================================
+# SHELL COMMAND BUILDER
+# ============================================================
+
+def build_shell_command(
+    *,
+    root_dir: Path,
+    script_path: Path,
+    venv: Optional[str],
+    script_args: Dict[str, Any],
+):
+    """
+    Build shell command for argparse-based scripts.
+    
+    Args:
+        root_dir: Root directory to cd into
+        script_path: Path to the Python script
+        venv: Virtual environment directory (optional)
+        script_args: Dictionary of argument name -> value for the script
+    """
+    parts = [f"cd {root_dir}"]
+
+    if venv:
+        parts.append(f"source {venv}/bin/activate")
+
+    # Build the python command with arguments
+    arg_list = [f"python {script_path}"]
+    
+    for key, value in script_args.items():
+        # Convert parameter names to lowercase CLI argument names
+        # e.g., "BATCH_SIZE" -> "--batch-size", "batch_size" -> "--batch-size"
+        #arg_name = key.lower().replace("_", "-")
+        arg_name = key.replace("_", "-")
+        
+        # Handle boolean flags
+        if isinstance(value, bool):
+            if value:
+                arg_list.append(f"--{arg_name}")
+        # Handle string "False"/"True" from YAML/JSON
+        elif isinstance(value, str) and value.lower() in ("false", "true"):
+            if value.lower() == "true":
+                arg_list.append(f"--{arg_name}")
+        else:
+            arg_list.append(f"--{arg_name} {value}")
+    
+    parts.append(" ".join(arg_list))
+
+    return " && ".join(parts)
+
+
+# ============================================================
+# HPO SPACE LOADING
+# ============================================================
+
+def load_hpo_space(args) -> Dict[str, Any]:
+    """Load HPO search space configuration."""
+    data = {}
+    if args.hpo_json:
+        data = json.loads(args.hpo_json)
+    elif args.hpo_yaml:
+        with open(args.hpo_yaml, "r") as f:
+            data = yaml.safe_load(f)
+    
+    # If the YAML has an 'hpo' section, use only that. 
+    # Otherwise, assume the whole file is the HPO space.
+    if isinstance(data, dict) and "hpo" in data:
+        return data["hpo"]
+    return data
+
+def load_static_args(args) -> Dict[str, Any]:
+    """Load static arguments."""
+    data = {}
+    if args.static_args_json:
+        data = json.loads(args.static_args_json)
+    elif args.static_args_yaml:
+        with open(args.static_args_yaml, "r") as f:
+            data = yaml.safe_load(f)
+    elif args.hpo_yaml: # Fallback: check the HPO file for a 'static' section
+        with open(args.hpo_yaml, "r") as f:
+            data = yaml.safe_load(f)
+
+    if isinstance(data, dict) and "static" in data:
+        return data["static"]
+    return data if data else {}
+
+
+# ============================================================
+# OPTUNA PARAM INSTANTIATION
+# ============================================================
+
+def _num(x):
+    """Convert string to numeric if needed."""
+    if isinstance(x, str):
+        return float(x)
+    return x
+
+
+def suggest_from_spec(trial, name: str, spec: Dict[str, Any]):
+    """
+    Suggest a hyperparameter value based on specification.
+    
+    Args:
+        trial: Optuna trial object
+        name: Parameter name
+        spec: Parameter specification dict with 'type' and other fields
+    
+    Returns:
+        Suggested parameter value
+    """
+    t = spec["type"]
+
+    if t == "float":
+        return trial.suggest_float(
+            name,
+            _num(spec["low"]),
+            _num(spec["high"]),
+            log=spec.get("log", False),
+        )
+
+    if t == "int":
+        return trial.suggest_int(
+            name,
+            int(_num(spec["low"])),
+            int(_num(spec["high"])),
+            log=spec.get("log", False),
+        )
+
+    if t == "categorical":
+        return trial.suggest_categorical(name, spec["choices"])
+
+    raise ValueError(f"Unknown param type: {t}")
+
+
+# ============================================================
+# METRIC EXTRACTION
+# ============================================================
+
+
+def extract_metric_from_log(path, metric: str):
+    pattern = re.compile(
+        rf"{re.escape(metric)}\s*[: ]\s*([-+]?\d*\.?\d+(?:[eE][-+]?\d+)?)"
+    )
+
+    with open(path, "r", encoding="utf-8", errors="ignore") as f:
+        text = f.read()
+
+    matches = pattern.findall(text)
+
+    if not matches:
+        raise RuntimeError(f"Metric '{metric}' not found in {path}")
+
+    return float(matches[0])
+
+
+# ============================================================
+# MAIN
+# ============================================================
+
+def main():
+    print("IMPORTANT: For the old iterate HPO Launcher v0.2.3 use iterate-classic")
+    args = parse_args()
+    hpo_space = load_hpo_space(args)
+    static_args = load_static_args(args)
+
+    script_path, root_dir = resolve_paths(args.script, args.root_dir)
+
+    def objective(trial):
+        # Combine static arguments with HPO parameters
+        script_args = static_args.copy()
+        
+        # Add HPO parameters
+        for name, spec in hpo_space.items():
+            script_args[name] = suggest_from_spec(trial, name, spec)
+
+        # Add trial number
+        script_args["trial_number"] = trial.number
+
+        # Log file paths
+        out_file = f"trial_{trial.number}.out"
+        err_file = f"trial_{trial.number}.err"
+
+        # Build command
+        shell_cmd = build_shell_command(
+            root_dir=root_dir,
+            script_path=script_path,
+            venv=args.venv if args.venv else None,
+            script_args=script_args,
+        )
+
+        launcher_cmd = build_launcher_command(
+            wlm=args.wlm,
+            cmd=shell_cmd,
+            trial_id=trial.number,
+            out_file=out_file,
+            err_file=err_file,
+            gpu_count=args.gpu_count,
+            cpu_count=args.cpu_count,
+            mem_gb=args.mem_gb,
+        )
+
+        # Execute trial
+        print(f"Trial {trial.number}: Executing command")
+        print(f"  HPO params: {hpo_space.keys()}")
+        subprocess.run(launcher_cmd, shell=True, check=True)
+
+        # Extract and return metric
+        metric_value = extract_metric_from_log(out_file, args.metric)
+        print(f"Trial {trial.number}: {args.metric} = {metric_value}")
+        
+        return metric_value
+
+    # Create or load Optuna study
+    study = optuna.create_study(
+        study_name=args.optuna_study_name,
+        storage=args.optuna_db_path,
+        direction="maximize",
+        load_if_exists=True,
+    )
+
+    # Run optimization
+    study.optimize(objective, n_trials=args.optuna_n_trials)
+    
+    # Print best results
+    print("\n" + "="*60)
+    print("OPTIMIZATION COMPLETE")
+    print("="*60)
+    print(f"Best trial: {study.best_trial.number}")
+    print(f"Best value: {study.best_value}")
+    print(f"Best params:")
+    for key, value in study.best_params.items():
+        print(f"  {key}: {value}")
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/terratorch_iterate/main.py b/terratorch_iterate/main.py
index 8f8c105..9dabddb 100644
--- a/terratorch_iterate/main.py
+++ b/terratorch_iterate/main.py
@@ -171,6 +171,7 @@ def _convert_config(args: Namespace):
 
 
 def main():
+    print("DEPRECATED: iterate-classic is deprecated. Please use iterate instead.")
     parser = ArgumentParser()
 
     parser.add_argument("--defaults", type=Defaults)  # to ignore model
diff --git a/tests/integration/test_main.py b/tests/integration/test_main.py
index acc342d..dffbbe6 100644
--- a/tests/integration/test_main.py
+++ b/tests/integration/test_main.py
@@ -78,7 +78,7 @@ def test_main(
         abs_path = repo_home_dir / storage_uri
         storage_uri = str(abs_path.resolve())
     experiment_name = config_data["experiment_name"]
-    arguments = ["terratorch", "--config", str(config_file.resolve())]
+    arguments = ["iterate-classic", "--config", str(config_file.resolve())]
     if hpo:
         arguments.insert(1, "--hpo")
     sys.argv = arguments
diff --git a/tests/unit/test_iterate2.py b/tests/unit/test_iterate2.py
new file mode 100644
index 0000000..cb0fe22
--- /dev/null
+++ b/tests/unit/test_iterate2.py
@@ -0,0 +1,19 @@
+import os
+
+def test_iterate2( ):
+    script = """
+iterate \
+  --script ./examples/bumpy_function.py \
+  --root-dir . \
+  --optuna-study-name hpo \
+  --optuna-db-path "sqlite:///iterate_study.db" \
+  --hpo-yaml examples/bumpy_hpo.yaml \
+  --optuna-n-trials 10 \
+  --wlm none \
+  --metric yval \
+  --gpu-count 0 \
+  --cpu-count 1 \
+  --mem-gb 1
+    """
+    ret = os.system(script)
+    assert ret == 0
\ No newline at end of file