Existing diagram languages force auto-placement without user layout control, while manual graphical tools are time-consuming and inefficient for AI agents to manipulate.
Existing diagram languages force auto-placement without user layout control, while manual graphical tools are time-consuming and inefficient for AI agents to manipulate.
auto-placement languages like Mermaid or Graphviz (which don't let me decide how the diagram looks)
postShow HN: Reladraw – A diagram language where you decide where to place things
Show HN: Reladraw – A diagram language where you decide where to place things
If I had a nickel for every hour I spent fiddling with a Plantuml diagram to get the relation directions to force the layout into at least an approximation of what I wanted, I'll be a lot closer to retirement.
commentThat's an interesting idea, and an unexplored design space. Graphviz's dot has rank and head/tail ports, and Plantuml's class diagram has some support for relative position, but both are more hints for the layout engine, not deterministic declarations. If I had a nickel for every hour I spent fiddling with a Plantuml diagram to get the relation directions to force the layout into at least an approximation of what I wanted, I'll be a lot closer to retirement. I like that you're going for one generic syntax instead of many specific ones, like mermaid and Plantuml, but it's as much as a pro as it is a con, it's one reason why these languages evolved in the first place, instead of everyone just using DOT. One possible mitigation would be some sort of reuse mechanism? Some way that generic nodes could be defined once and instantiated many times, so if I wanted to draw something like a sequence diagram, I could define/change my participant lanes just once. Another issue the "No multi-line statements, no line continuations, no blocks." philosophy. I get *why* you chose it, and has its advantages, but it's a pretty annoying constraint, specially if one wants to have longer node names, or have more detailed description of the node in its label, like listing the responsibilities of a class, for instance. "No blocks" is something that can probably won't make much difference, but line continuations (i.e., some distinction between physical and logical lines) can make or break the user experience, IMHO The syntax for line breaks is another thing I urge you to reconsider, '/' is waaay to common of a character, and being forced to write long strings in a single line can get *really* annoying. Some sort of multiline string support would really make your existing syntax shine. The last two suggestions/complaints would complicate your parser a lot, specially since you're writing it manually, so, they are trade offs, but as a user who'd love to have something like this on my toolbelt, not having these features would make me hesitate a lot on investing time in this tool. That said, it's a nice idea, I'll keep an eye on it =)
Engineers and writers creating system architecture diagrams who struggle with rigid auto-placement engines or slow manual drawing tools.
Multiple complaints regarding layout frustration with Mermaid and PlantUML, coupled with the rising need for AI agent-friendly text formats.
Combines text-based developer workflows with precise manual layout control and AI agent editability, solving the black-box layout problem of Mermaid and Graphviz.
A text-based diagramming language and editor extension that combines the ease of code-based diagram generation with fine-grained, deterministic control over spatial layout and element placement, optimized for both human developers and programmatic editing by AI agents.
Developers waste hours fighting auto-layout configuration hints; a $12/mo subscription easily pays for itself by saving billable engineering and documentation time.
“From frustrating auto-layout to precise diagrams in 6 weeks.”
A text-based diagramming language and editor extension that combines the ease of code-based diagram generation with fine-grained, deterministic control over spatial layout and element placement, optimized for both human developers and programmatic editing by AI agents.
Launch on Hacker News, r/programming, r/webdev, and GitHub showcasing side-by-side comparisons with Mermaid and PlantUML layout failures.
Developers are already accustomed to Mermaid or PlantUML syntax and may resist learning a new diagram definition format.
Building a reliable rendering engine that honors explicit positioning while maintaining clean auto-routing is technically difficult.
Keeping VS Code and Obsidian extensions performant and stable across updates requires ongoing engineering effort.
Run an Investment Memo to get a structured Go / No-Go verdict, competitor landscape, unit economics, and a 90-day validation roadmap for this opportunity.
Generate an investment memoThis opportunity scores well above the median for ideas surfaced by MonetScope, with a validation sub-score of 9/10 against 3 independently sourced evidence signals. A "strong" rating in this band typically means the pain signal is consistent and recurring across multiple discussions, but one of the three pillars (severity, willingness to pay, or competitor weakness) is somewhat softer than top-tier opportunities. Founders evaluating this should focus customer discovery on the softest pillar first — confirming the gap before committing engineering time to a build.
It sits at the intersection of "ai-powered", "browser-extension", "developers", which makes it relevant to a specific subset of founders rather than a generic horizontal opportunity. SaaS opportunities at this stage tend to win on the strength of their initial wedge — a single workflow that the target user runs every week, where the existing solution is either spreadsheets, a clunky incumbent feature, or a manual process they hate. The build cost is moderate; the distribution cost is everything. The MonetScope pipeline surfaces this category alongside other saas signals, which is why it appears here rather than in a generic "trending ideas" feed.
Scores are derived from real forum discussions across Reddit, Hacker News and X, weighted by evidence volume and signal quality. How scoring works
MonetScope does not generate ideas from a language model's imagination. Every opportunity on this site is anchored to specific source posts and comments from real public discussions — typically on Reddit, Hacker News, or X — where actual users describe the pain in their own words. The AI's role is structuring, scoring, and grouping those signals into a navigable opportunity, not inventing the problem.
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