diff --git a/tinygrad/codegen/__init__.py b/tinygrad/codegen/__init__.py
index 0783c7bc76..e4803b70ff 100644
--- a/tinygrad/codegen/__init__.py
+++ b/tinygrad/codegen/__init__.py
@@ -1,7 +1,7 @@
 from typing import Any, Callable
 import functools
 from dataclasses import dataclass
-from tinygrad.helpers import QUANTIZE, DEVECTORIZE, TRANSCENDENTAL, RANGEIFY, POSTOPT
+from tinygrad.helpers import QUANTIZE, DEVECTORIZE, TRANSCENDENTAL
 from tinygrad.uop.ops import PatternMatcher, graph_rewrite, UOp
 from tinygrad.uop.spec import type_verify
 from tinygrad.renderer import Renderer
@@ -16,7 +16,6 @@ from tinygrad.codegen.late.expander import migrate_indexing, expander, pm_pre_ex
 from tinygrad.codegen.late.devectorizer import load_store_folding, load_store_indexing, devectorize, pm_reduce, \
   ReduceContext, correct_load_store, pm_render
 from tinygrad.codegen.late.linearize import block_create, pm_blockend_merge, block_merge, pm_finalize, BlockContext
-from tinygrad.codegen.opt.kernel import pm_get_optimization, pm_do_optimize
 from tinygrad.codegen.opt.swizzler import view_left, view_right, fix_kernel_ops
 from tinygrad.codegen.opt.postrange import pm_postrange_opt
 from tinygrad.schedule.rangeify import pm_add_buffers_local, rangeify_codegen
@@ -46,24 +45,22 @@ rewrites_for_linearizer = [
 
 def get_rewrites_for_renderer(opts:Renderer, linearizer:bool=True) -> list[RewriteStep]:
   # cache with the values of the context vars
-  return _get_rewrites_for_renderer(opts, linearizer, QUANTIZE.value, DEVECTORIZE.value, TRANSCENDENTAL.value, RANGEIFY.value, POSTOPT.value)
+  return _get_rewrites_for_renderer(opts, linearizer, QUANTIZE.value, DEVECTORIZE.value, TRANSCENDENTAL.value)
 
 @functools.cache
-def _get_rewrites_for_renderer(opts:Renderer, linearizer:bool, _QUANTIZE, _DEVECTORIZE, _TRANSCENDENTAL, _RANGEIFY, _POSTOPT) -> list[RewriteStep]:
+def _get_rewrites_for_renderer(opts:Renderer, linearizer:bool, _QUANTIZE, _DEVECTORIZE, _TRANSCENDENTAL) -> list[RewriteStep]:
   # ** lowerer (rewrite_shapetracker_with_index) **
   ret: list[RewriteStep] = []
 
   # view pushing
   ret.extend(rewrites_for_views)
 
-  # this is kernel.py
-  if _POSTOPT <= 1 and not _RANGEIFY: ret.append(RewriteStep(pm_get_optimization, ctx=lambda _: opts, name="get optimization"))
-  if not _POSTOPT and not _RANGEIFY: ret.append(RewriteStep(pm_do_optimize, ctx=lambda _: opts, name="optimize ast"))
-
+  # lowerer first
   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))
 
-  if _POSTOPT or _RANGEIFY: ret.append(RewriteStep(pm_postrange_opt, ctx=lambda _: opts, name="post optimize ast"))
+  # optimize (schedule) the AST
+  ret.append(RewriteStep(pm_postrange_opt, ctx=lambda _: opts, name="post optimize ast"))
 
   # ** expander (expand_rewrite) **
   ret.append(RewriteStep(sym+migrate_indexing, name="initial symbolic"))
diff --git a/tinygrad/codegen/opt/kernel.py b/tinygrad/codegen/opt/kernel.py
index 02f522dce4..832a8e5fa6 100644
--- a/tinygrad/codegen/opt/kernel.py
+++ b/tinygrad/codegen/opt/kernel.py
@@ -4,13 +4,13 @@ from dataclasses import dataclass
 from collections import defaultdict
 from typing import cast, Final, Callable, Sequence
 from tinygrad.codegen.opt import OptOps, Opt, KernelOptError, check, axis_letters, axis_colors
-from tinygrad.uop.ops import GroupOp, KernelInfo, UOp, Ops, can_pad, resolve, Variable, sint, graph_rewrite, AxisType, PatternMatcher, UPat
+from tinygrad.uop.ops import GroupOp, KernelInfo, UOp, Ops, can_pad, resolve, Variable, sint, graph_rewrite, AxisType
 from tinygrad.uop.spec import type_verify, ast_spec
 from tinygrad.device import Device
 from tinygrad.codegen.opt.tc import TensorCore
 from tinygrad.renderer import Renderer
 from tinygrad.dtype import ImageDType
-from tinygrad.helpers import all_same, colored, ansilen, dedup, prod, round_up, to_function_name, unwrap, argfix, DEBUG, NOOPT, BEAM, getenv, POSTOPT
+from tinygrad.helpers import all_same, colored, ansilen, dedup, prod, round_up, to_function_name, unwrap, argfix, DEBUG
 from tinygrad.shape.shapetracker import ShapeTracker
 from tinygrad.shape.view import strides_for_shape, get_contraction
 from tinygrad.codegen.opt.swizzler import view_left, view_left_through_load
@@ -433,47 +433,3 @@ class Kernel:
     fixed_ast = fixup_ast(self.ast)
     del fixup_ast
     return graph_rewrite(fixed_ast, view_left+view_left_through_load, name="fixup optimized AST")
-
-def get_optimized_ast(ast:UOp, renderer:Renderer) -> UOp|None:
-  """
-  Optimize an AST based on heuristics or BEAM search.
-
-  Args:
-    ast: The Ops.SINK rooted AST
-    renderer: The renderer used to generate the code
-
-  Returns:
-    The Ops.SINK rooted AST transformed to apply the opts and with a KernelInfo in the arg.
-  """
-
-  # no shape, no opt
-  if ast.src[0].st is None: return None
-  new_arg = ast.arg
-  if new_arg is None:
-    k = Kernel(ast, opts=renderer)
-    if not NOOPT:
-      from tinygrad.codegen.opt.heuristic import hand_coded_optimizations
-      k.apply_opts(hand_coded_optimizations(k))
-      if not POSTOPT and BEAM >= 1:
-        from tinygrad.codegen.opt.search import beam_search, bufs_from_lin
-        kb = Kernel(ast, opts=renderer)
-        rawbufs = bufs_from_lin(kb, allocate=False)
-        k = beam_search(kb, rawbufs, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))
-    new_arg = KernelInfo(opts_to_apply=tuple(k.applied_opts))
-  elif len(new_arg.applied_opts): return None
-  return Kernel(ast.replace(arg=None), opts=renderer).get_optimized_ast().replace(arg=new_arg)
-
-pm_get_optimization = PatternMatcher([
-  (UPat(Ops.SINK, name="ast"), lambda ctx,ast: get_optimized_ast(ast, ctx)),
-])
-
-def apply_opt(ast:UOp, renderer:Renderer):
-  k = Kernel(ast, opts=renderer)
-  k.apply_opts(ast.arg.opts_to_apply)
-  ret = k.get_optimized_ast()
-  if __debug__: type_verify(list(ret.toposort()))
-  return ret
-
-pm_do_optimize = PatternMatcher([
-  (UPat(Ops.SINK, name="ast"), lambda ctx,ast: apply_opt(ast, ctx) if ast.arg is not None and ast.arg.opts_to_apply is not None else None),
-])
\ No newline at end of file
diff --git a/tinygrad/codegen/opt/postrange.py b/tinygrad/codegen/opt/postrange.py
index f143e5beba..0df88ffef3 100644
--- a/tinygrad/codegen/opt/postrange.py
+++ b/tinygrad/codegen/opt/postrange.py
@@ -6,7 +6,7 @@ from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, KernelInfo, graph_r
 from tinygrad.uop.symbolic import symbolic_flat
 from tinygrad.device import Buffer
 from tinygrad.dtype import AddrSpace, dtypes, ImageDType
-from tinygrad.helpers import colored, BEAM, getenv, DEBUG, to_function_name, NOOPT, argsort, round_up, POSTOPT, prod
+from tinygrad.helpers import colored, BEAM, getenv, DEBUG, to_function_name, NOOPT, argsort, round_up, prod
 from tinygrad.codegen.opt import axis_colors, Opt, OptOps, KernelOptError, check, axis_letters
 from tinygrad.renderer import Renderer
 from tinygrad.schedule.rangeify import remove_tags
@@ -347,16 +347,14 @@ def apply_opts(ctx:Renderer, ast:UOp):
   if ast.tag is not None: return None
   k = Scheduler(ast, ctx)
   k.convert_loop_to_global()
+  k.simplify_merge_adjacent()
   if BEAM >= 1:
-    k.simplify_merge_adjacent()
     from tinygrad.codegen.opt.search import beam_search
     rawbufs = bufs_from_ast(ast, ctx.device)
     k = beam_search(k, rawbufs, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))
   elif ast.arg is not None and ast.arg.opts_to_apply is not None:
-    if POSTOPT >= 2: k.simplify_merge_adjacent()
     for opt in ast.arg.opts_to_apply: k.apply_opt(opt)
   elif not NOOPT and (ast.arg is None or ast.arg.applied_opts == ()):
-    k.simplify_merge_adjacent()
     from tinygrad.codegen.opt.heuristic import hand_coded_optimizations
     # NOTE: hand_coded_optimizations doesn't support multiblock opts yet
     if all(len(u.src) == 1 for u in ast.parents if u.op is Ops.LOAD):
diff --git a/tinygrad/helpers.py b/tinygrad/helpers.py
index 088b42ef1e..37467c5eea 100644
--- a/tinygrad/helpers.py
+++ b/tinygrad/helpers.py
@@ -140,7 +140,7 @@ DONT_REALIZE_EXPAND, DONT_GROUP_REDUCES = ContextVar("DONT_REALIZE_EXPAND", 0),
 QUANTIZE, VALIDATE_WITH_CPU, DISABLE_FAST_IDIV = ContextVar("QUANTIZE", 0), ContextVar("VALIDATE_WITH_CPU", 0), ContextVar("DISABLE_FAST_IDIV", 0)
 CORRECT_DIVMOD_FOLDING, FUSE_OPTIM = ContextVar("CORRECT_DIVMOD_FOLDING", 0), ContextVar("FUSE_OPTIM", 0)
 ALLOW_DEVICE_USAGE, MAX_BUFFER_SIZE, AMD_LLVM = ContextVar("ALLOW_DEVICE_USAGE", 1), ContextVar("MAX_BUFFER_SIZE", 0), ContextVar("AMD_LLVM", 1)
-RANGEIFY, POSTOPT, FUSE_ATTENTION = ContextVar("RANGEIFY", 0), ContextVar("POSTOPT", 2), ContextVar("FUSE_ATTENTION", 0)
+RANGEIFY, FUSE_ATTENTION = ContextVar("RANGEIFY", 0), ContextVar("FUSE_ATTENTION", 0)
 EMULATE = ContextVar("EMULATE", "")
 
 @dataclass(frozen=True)