diff --git a/test/test_tensor.py b/test/test_tensor.py
index 21a868838f..f71844b233 100644
--- a/test/test_tensor.py
+++ b/test/test_tensor.py
@@ -892,13 +892,13 @@ class TestIdxUpcast(unittest.TestCase):
 
   @unittest.skipUnless(is_dtype_supported(dtypes.long), "int64 is supported")
   def test_overflow_sym(self):
-    self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 1, 2048).bind(32))
+    self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 0, 2048).bind(32))
 
   def test_regular(self):
     self.do_op_then_assert(dtypes.int, 64, 64, 64)
 
   def test_regular_sym(self):
-    self.do_op_then_assert(dtypes.int, 2048, 2048, UOp.variable("dim3", 1, 64).bind(32))
+    self.do_op_then_assert(dtypes.int, 2048, 2048, UOp.variable("dim3", 0, 64).bind(32))
 
   @unittest.skipIf(PTX, "PTX always convert Ops.INDEX to int64")
   def test_symfold(self):
@@ -910,7 +910,7 @@ class TestIdxUpcast(unittest.TestCase):
   @unittest.skipIf(is_dtype_supported(dtypes.long), "int64 is supported")
   def test_int64_unsupported_overflow_sym(self):
     with self.assertRaises(KeyError):
-      self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 1, 2048).bind(32))
+      self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 0, 2048).bind(32))
 
   @unittest.skipIf(is_dtype_supported(dtypes.long), "int64 is supported")
   def test_int64_unsupported_overflow(self):
diff --git a/tinygrad/codegen/__init__.py b/tinygrad/codegen/__init__.py
index 9ee02e682b..24456a2a4d 100644
--- a/tinygrad/codegen/__init__.py
+++ b/tinygrad/codegen/__init__.py
@@ -16,7 +16,6 @@ from tinygrad.codegen.devectorizer import load_store_folding, load_store_indexin
   ReduceContext, correct_load_store, pm_render
 from tinygrad.codegen.optional import get_late_rewrite_patterns
 from tinygrad.codegen.linearize import block_create, pm_blockend_merge, block_merge, pm_finalize, BlockContext
-from tinygrad.opt import pm_optimize
 
 @dataclass
 class RewriteStep:
@@ -43,10 +42,6 @@ def get_rewrites_for_renderer(opts:Renderer, linearizer:bool=True) -> list[Rewri
 def _get_rewrites_for_renderer(opts:Renderer, linearizer:bool, _QUANTIZE, _DEVECTORIZE, _TRANSCENDENTAL) -> list[RewriteStep]:
   # ** lowerer (rewrite_shapetracker_with_index) **
   ret: list[RewriteStep] = []
-
-  # this is kernel.py
-  ret.append(RewriteStep(pm_optimize, ctx=lambda _: opts, name="optimize ast"))
-
   if _QUANTIZE and opts.device in {"CPU", "DSP"}: ret.append(RewriteStep(pm_quant, name="quantize"))
   ret.append(RewriteStep(pm_lowerer, get_index, name="lowerer", bottom_up=True))
 
diff --git a/tinygrad/engine/realize.py b/tinygrad/engine/realize.py
index 388f7d33e8..f4cd06c5bf 100644
--- a/tinygrad/engine/realize.py
+++ b/tinygrad/engine/realize.py
@@ -7,7 +7,9 @@ from tinygrad.uop.ops import Ops, PatternMatcher, UOp, UPat, Variable, sym_infer
 from tinygrad.device import Device, Buffer
 from tinygrad.renderer import Renderer, ProgramSpec, Estimates
 from tinygrad.engine.schedule import ScheduleItem
+from tinygrad.opt import get_optimized_ast
 from tinygrad.codegen import full_rewrite
+from tinygrad.uop.spec import type_verify
 
 # **************** Program Creation ****************
 
@@ -25,13 +27,16 @@ def get_program(ast:UOp, renderer:Renderer) -> ProgramSpec:
   """
 
   if getenv("VIZ"): graph_rewrite(ast, PatternMatcher([]), name="View Base AST")
+  modified_ast = get_optimized_ast(ast, renderer) if ast.arg is None or ast.arg.opts_to_apply is not None else ast
+  if __debug__: type_verify(list(modified_ast.toposort()))
 
   # linearize
   try:
-    uops = full_rewrite(ast, renderer)
+    uops = full_rewrite(modified_ast, renderer)
   except RuntimeError:
     print("***** LINEARIZE FAILURE *****")
     print(f"ast = {ast}")
+    print(f"opts = {modified_ast.arg.applied_opts}")
     raise
   assert uops[-1].op is Ops.SINK, "last uop must be sink"
 
diff --git a/tinygrad/opt/__init__.py b/tinygrad/opt/__init__.py
index 6128b21a5b..934b9f0749 100644
--- a/tinygrad/opt/__init__.py
+++ b/tinygrad/opt/__init__.py
@@ -2,10 +2,9 @@
 
 from tinygrad.opt.kernel import Kernel
 from tinygrad.opt.heuristic import hand_coded_optimizations
-from tinygrad.uop.ops import UOp, PatternMatcher, UPat, Ops
+from tinygrad.uop.ops import UOp
 from tinygrad.helpers import NOOPT, BEAM, USE_TC, getenv
 from tinygrad.renderer import Renderer
-from tinygrad.uop.spec import type_verify
 
 def get_optimized_ast(ast:UOp, renderer:Renderer) -> UOp:
   """
@@ -28,11 +27,4 @@ def get_optimized_ast(ast:UOp, renderer:Renderer) -> UOp:
       kb = Kernel(ast, opts=renderer)
       rawbufs = bufs_from_lin(kb, allocate=False)
       k = beam_search(kb, rawbufs, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))
-  ret = k.get_optimized_ast()
-  if __debug__: type_verify(list(ret.toposort()))
-  return ret
-
-pm_optimize = PatternMatcher([
-  (UPat(Ops.SINK, name="ast"), lambda ctx,ast:
-   get_optimized_ast(ast, ctx) if (ast.arg is None or ast.arg.opts_to_apply is not None) and ast.src[0].st is not None else None),
-])
+  return k.get_optimized_ast()
diff --git a/tinygrad/uop/ops.py b/tinygrad/uop/ops.py
index add5ca012f..1dfdaeb857 100644
--- a/tinygrad/uop/ops.py
+++ b/tinygrad/uop/ops.py
@@ -440,7 +440,7 @@ class UOp(MathTrait, metaclass=UOpMetaClass):
     all_vars = set([x for x in self.toposort() if x.op is Ops.DEFINE_VAR])
     return bound_vars.union(set([x for x in all_vars if x not in bound_var_base]))
   def variables(self) -> list[Variable]:
-    st_vars: list[set[Variable]] = [x.arg.vars() for x in self.toposort() if x.op is Ops.VIEW]
+    st_vars: list[set[Variable]] = [x.st_arg.vars() for x in self.toposort() if x.op in GroupOp.Buffer]
     return sorted(set.union(*st_vars, set([x.unbind()[0] if x.op is not Ops.DEFINE_VAR else x for x in self.vars()])), key=lambda v: v.arg)
 
   # *** uop symbolic stuff ***