diff --git a/docs/source/developers/computeir.rst b/docs/source/developers/computeir.rst
deleted file mode 100644
index 9ebe1d5afb2..00000000000
--- a/docs/source/developers/computeir.rst
+++ /dev/null
@@ -1,59 +0,0 @@
-.. Licensed to the Apache Software Foundation (ASF) under one
-.. or more contributor license agreements.  See the NOTICE file
-.. distributed with this work for additional information
-.. regarding copyright ownership.  The ASF licenses this file
-.. to you under the Apache License, Version 2.0 (the
-.. "License"); you may not use this file except in compliance
-.. with the License.  You may obtain a copy of the License at
-
-..   http://www.apache.org/licenses/LICENSE-2.0
-
-.. Unless required by applicable law or agreed to in writing,
-.. software distributed under the License is distributed on an
-.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-.. KIND, either express or implied.  See the License for the
-.. specific language governing permissions and limitations
-.. under the License.
-
-**********************************************
-Arrow Compute IR (Intermediate Representation)
-**********************************************
-
-In the same way that the Arrow format provides a powerful tool
-for communicating data, Compute IR is intended to provide a
-consistent format for representing analytical operations against
-that data. As an arrow-native expression of computation it includes
-information such as explicit types and schemas and arrow formatted
-literal data. It is also optimized for low runtime overhead in both
-serialization and deserialization.
-
-Built-in definitions are included to enable representation of
-relational algebraic operations- the contents of a "logical query plan".
-Compute IR also has first class support for representing operations
-which are not members of a minimal relational algebra, including
-implementation and optimization details- the contents of a "physical
-query plan". This approach is taken in emulation of `MLIR`_ (Multi-Level
-Intermediate Representation), a system which has had strong successes in
-spaces of comparable complexity to representation of analytic operations.
-To borrow terms from that project, there are two mutations of interest:
-
-* Replacement of representations with semantically equivalent representations
-  which will yield better performance for consumers- an optimization pass.
-* Replacement of abstract or generic representations with more specific
-  and potentially consumer-specific representations- a lowering pass.
-  This modification corresponds to the translation of a logical plan
-  to a physical plan.
-
-Allowing representation of physical plans (and plans which are between
-logical and physical) in Compute IR enables systems to define incremental
-optimization and lowering passes which operate on and produce valid
-Compute IR. This in turn enables communication, manipulation, and inspection
-at every stage of lowering/optimization by the same tools
-used for logical-plan-equivalent-IR. This is especially useful for systems
-where such passes may depend on information only available on every node
-of a distributed consumer (for example statistics unique to that node's
-local data) or may not be universal to all backends in a heterogeneous
-consumer (for example which optimizations nodes are capable of for
-non equi joins).
-
-.. _MLIR: https://mlir.llvm.org
diff --git a/docs/source/index.rst b/docs/source/index.rst
index b3d232fbb86..b261474c6fa 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -100,4 +100,3 @@ target environment.**
    developers/benchmarks
    developers/documentation
    developers/release
-   developers/computeir