MOL
A programming language where pipelines trace themselves
Details
- External ID
- 46977967
- Source
- HN
- Company
- —
- Product
- MOL
- Website domain
- github.com
- Launched
- Feb. 11, 2026
- Cohort
- —
- Upvotes
- 38
- Upvotes percentile
- 0.7756064690026954
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:25 p.m.
- Updated at
- Sept. 7, 2026, 9:25 p.m.
Description
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. """
Enrichment
- Theme
- browser automation and scraping for AI
- Vertical
- Horizontal
- Function
- Dev tools
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Hobby / open-source project
- Normalized one-liner
- programming language with self-tracing pipelines
- Manually corrected
- False
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 — 72 launches clear the similarity bar, closest 8 shown.
Attention rank: #23 of 73 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 98 days after the earliest competitor.
- SHDL · hn · 2026-01-28 · 48 upvotes · similarity 0.46
- The Mog Programming Language · hn · 2026-03-09 · 163 upvotes · similarity 0.44
- laborix · github · 2026-09-30 · 87 upvotes · similarity 0.41
- Pipevals · hn · 2026-03-20 · 6 upvotes · similarity 0.39
- LLM agents that write Python to analyze execution traces at scale · hn · 2026-03-07 · 5 upvotes · similarity 0.38
- Tracepipe · ph · 2026-09-10 · 5 upvotes · similarity 0.38
- GlyphLang · hn · 2026-01-10 · 44 upvotes · similarity 0.38
- A small programming language where everything is pass-by-value · hn · 2026-01-25 · 91 upvotes · similarity 0.37
Other launches for this product
- No other launches for this product.
Same idea, different domain
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