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new e5342c3ab [DOCS] Refresh README positioning and features (#179)
e5342c3ab is described below
commit e5342c3ab218310ef307ca82213d04170fd4d10e
Author: Bohan Hou <[email protected]>
AuthorDate: Tue Nov 3 20:16:27 2026 -0500
[DOCS] Refresh README positioning and features (#179)
Update the README to explain TIRx's role as a minimal, stable, and
extensible DSL and compiler foundation for agent-driven kernel
development, analysis, and eventual correctness verification. Streamline
the feature descriptions and documentation section while retaining the
project tagline.
---
README.md | 25 +++++++++++++------------
1 file changed, 13 insertions(+), 12 deletions(-)
diff --git a/README.md b/README.md
index 3bd023ff4..154ef61ad 100644
--- a/README.md
+++ b/README.md
@@ -19,21 +19,22 @@
📚 [Documentation](https://tvm.apache.org/tirx/) | 🚀 [Quick
Start](https://tvm.apache.org/tirx/get_started/quick_start.html)
-Apache TVM TIRx is a minimal, open ML compiler foundation for the agentic era.
+**We believe that, in the future, all GPU kernels will be developed,
optimized, and verified by AI agents.**
+
+You might wonder: **If my Claude or Codex can just spit out CUDA, PTX, or even
SASS directly, why bother with another compiler layer?** We've been asking
ourselves the same question.
+
+Our answer is **yes, but perhaps not in the form we know today**. Even when
agents generate code directly, analysis and independent verification still need
structured program representations and precisely defined semantics. A minimal,
extensible compiler foundation provides these shared building blocks while
leaving agents free to explore their own optimization strategies.
+
+**TIRx is our attempt to build a minimal, stable, and extensible DSL and
compiler foundation for that future**, enabling agents to write and optimize
kernels, develop their own analyses, and eventually verify correctness.
## Features
-- **Minimal, stable core IR** - a small, stable set of core AST nodes,
designed for common needs and for extension.
-- **Predictable utilities** - TVM-FFI bridge generation, symbolic integer
analysis, structural traversal and mapping, and minimal code generation for
CUDA and host LLVM.
-- **Dynamic extension by design** - all compiler APIs are open, so developers
and agents can iterate quickly on extensions in separate packages that link to
TIRx dynamically, without rebuilding one monolithic bundle.
-- **First-class cross-language support** - Python, C++, and native Rust.
Prototype an analysis or extension in Python, then bake it into Rust or C++;
extensions work across all supported languages.
-- **Built on stable toolchains** - a minimal layer for ML compilation needs
that connects to stable compiler toolchains and leverages their backend
capabilities when possible.
+- **Minimal, stable core IR** — a small, stable set of core AST nodes,
designed for common needs and extensions.
+- **Predictable utilities** — TVM-FFI bridge generation, symbolic integer
analysis, structural traversal and mapping, and minimal code generation for
CUDA and host LLVM.
+- **Dynamic extension by design** — agents can build and iterate on extensions
in independent packages, without rebuilding a monolithic compiler.
+- **First-class cross-language support** — Python, C++, and Rust, allowing
agents to prototype rapidly and move performance-critical components across
languages.
+- **Built on stable toolchains** — leverage established compiler backends
instead of reinventing them.
## Documentation
-Check out the [documentation site](https://tvm.apache.org/tirx/) for the full
documentation, including:
-
-- [Quick Start](https://tvm.apache.org/tirx/get_started/quick_start.html)
-- [IR Guides](https://tvm.apache.org/tirx/ir_guides/overview.html)
-- [Programming
Guides](https://tvm.apache.org/tirx/programming_guides/index.html)
-- [Extending
TIRx](https://tvm.apache.org/tirx/advanced/extending_ir_in_rust.html)
+Check out the [documentation](https://tvm.apache.org/tirx/) to get started.
