Why system modeling should look like code, not PowerPoint

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Systems engineers model billion-dollar spacecraft, life-saving medical devices, and autonomous vehicles in tools that can't even do a proper diff/merge/version control even with large expensive infrastructure. I built Sylang to address that. What is Sylang? A text-based language for modeling complex systems. Write declarative code, get visual diagrams, traceability matrices, FMEA analyses, and compliance reports automatically. Works with Git, VSCode, and AI code assistants. Example: def requirement BrakeActivation description "System shall activate brakes within 100ms" safetylevel ASIL-D testedby ref testcase EmergencyBrakeTest derivedfrom ref safetygoal PreventCollision allocatedto ref block BrakeController This generates: - Architecture diagrams (decomposition, internal block diagrams) - Traceability matrix (requirement ↔ test ↔ block ↔ safety goal) - Coverage analysis (which requirements lack tests?) - Compliance reports (functional safety, ASPICE, etc.) Why text-based modeling works: Your AI code assistant (Cursor, GitHub Copilot, Claude, Gemini) can: - Generate requirements from safety goals - Create test cases from requirements - Draft FMEA analyses from architecture - Refactor across files with semantic understanding - Suggest missing relationships Git workflows that actually work: git diff requirements.req # See what changed git merge feature/new-sensors # Merge architecture branches git blame safety-goals.sgl # Who defined this safety goal? No XMI. No database exports. No PowerPoint. Just readable text that generates everything you need. What you get: 23 file types covering the full engineering lifecycle: - Product lines & variants (.ple, .fml, .vml) - Architecture (.blk, .fun, .ifc) - Requirements & tests (.req, .tst) - Behavioral models (.ucd, .seq, .smd) - Safety analysis (.haz, .sgl, .sam, .flr, .fta) - Dashboards & specs (.dash, .spec) - Automation (.agt, .spr) All auto-generating visual diagrams: feature models, decomposition diagrams, sequence diagrams, state machines, traceability matrices. Current state: - Language stable (v0.9.27) - VSCode extension available (search "Sylang" in Extensions) - Works with Cursor, GitHub Copilot, Claude, Gemini code assistants - Diagram rendering, traceability, coverage analysis working - Solo dev, part-time, building in public Download at: https://marketplace.visualstudio.com/items?itemName=balaji-e... Website: https://sylang.dev GitHub: https://github.com/balaji-embedcentrum/sylang Feedback welcome—especially from engineers who've wished their modeling tools worked more like their code editors.

Visit product View on Hacker NewsOct 20, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, cursor, claude · Missing: agents, macos, agent

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Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

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