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MOL

A programming language where pipelines trace themselves

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Hi HN,I built MOL, a domain-specific language for AI pipelines. The main idea: the pipe operator |> automatically generates execution traces — showing timing, types, and data at each step. No logging, no print debugging.Example: let index be doc |> chunk(512) |> embed("model-v1") |> store("kb") This auto-prints a trace table with each step's execution time and output type. Elixir and F# have |> but neither auto-traces.Other features: - 12 built-in domain types (Document, Chunk, Embedding, VectorStore, Thought, Memory, Node) - Guard assertions: `guard answer.confidence > 0.5 : "Too low"` - 90+ stdlib functions - Transpiles to Python and JavaScript - LALR parser using LarkThe interpreter is written in Python (~3,500 lines). 68 tests passing. On PyPI: `pip install mol-lang`.Online playground (no install needed): http://135.235.138.217:8000We're building this as part of IntraMind, a cognitive computing platform at CruxLabx. """

HN · launched Feb 11, 2026 · 38 upvotes (top 22%) · 1 view

Niche: programming languages and interpreters · 161 launches, 2 in the last 7 days ▼ -75% · Explore this niche →

Category and tags

  • Horizontal
  • Dev tools
  • Developer
  • Not AI
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Partial The syntax and basic interpreter wrapper can be vibe-coded, but designing a reliable DSL runtime with automatic runtime tracing, type checking, and AI pipeline introspection requires compiler and language design fundamentals.

What it would actually take: The system requires a lexer, parser, and AST interpreter/compiler (likely built in Rust or Go) supporting custom pipe operators and automated execution telemetry. It requires hooks for streaming LLM outputs, asynchronous IO for embeddings/vector DB operations, and OpenTelemetry-compatible tracing infrastructure without introducing runtime overhead. This demands solid programming language design (PL) and distributed tracing expertise.

Discussion

16 comments analyzed.

Competitors mentioned: Elixir (pipe operator), Haskell (MonadTrace), F# (pipe operator), Python (operator overloading), Rust (operator overloading)

Concerns raised: Not Pythonic to use operator overloading for pipes, Performance overhead compared to native Python, Dynamic pipelines and batching execution unclear, Orphan rule violation in Rust implementation, Auto-tracing not truly automatic, still requires explicit setup

Feature requests: Examples of complex workflows and open-ended loops/agents, Clarification on dynamic pipeline support, Separate pipeline definition from execution for throughput optimization, Documentation on durable pipeline execution

Competitors

Other products that read as similar to this one : 209 launches clear the similarity bar, closest 8 shown.

Attention rank: #67 of 210 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 103 days after the earliest competitor.

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