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Unlegacy

document everything, from COBOL to AI generated code

Details

External ID
47720860
Source
HN
Company
—
Product
Unlegacy
Website domain
unlegacy.ai
Launched
April 10, 2026
Cohort
—
Upvotes
9
Upvotes percentile
0.5501285347043702
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Enrichment

Theme
AI coding agents and developer tools
Vertical
Horizontal
Function
Vertical SaaS
Audience
B2B
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
code documentation for legacy and modern systems
Manually corrected
False

Could you build this?

Partial Generating documentation with LLMs is easy to prototype, but reliably parsing and reverse-engineering complex legacy codebases like COBOL requires dedicated AST parsers and legacy compiler knowledge.

What it would actually take: Building a reliable legacy documentation platform requires specialized parsers/grammars (e.g., ANTLR for COBOL dialects, mainframe JCL, PL/I) to construct accurate call graphs, data dictionaries, and ASTs. These representations are then fed chunk-by-chunk into an LLM context pipeline using RAG. The hard part is handling legacy syntax idiosyncrasies and mainframe execution flows that generic coding assistants fail to parse.

Discussion

1 comment analyzed.

Feature requests: PDF and markdown download options

Competitors

Other products that read as similar to this one — 2075 launches clear the similarity bar, closest 8 shown.

Attention rank: #877 of 2076 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 163 days after the earliest competitor.

Other launches for this product

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