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Motionode – Cursor for Technical Planning

Motionode – Cursor for Technical Planning

by oscarcaldera·Feb 17, 2026·2 points·0 comments
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AI Analysis

●●SolidBig BrainSolve My ProblemSlick
The Take

They split the work smartly: an LLM extracts deliverables from messy docs, then a deterministic 'physics' engine computes dependencies, capacity-based timelines, and a defendable critical path. Client-ready SOW PDFs, a scope-change ledger, and on-the-fly what-if scenarios feel immediately useful; I'd want to see proof it integrates cleanly with existing PM tooling and handles truly noisy inputs.

Category
SaaS
Target Audience

Product/engineering managers, agency leads, technical PMs, and small dev shops who need repeatable, defensible estimates

Post Description

Hey HN, I'm Oscar. After 15 years running a dev shop, I got tired of LLMs hallucinating project timelines and dependencies. They are word calculators, not scheduling engines.

I built Motionode. Think of it as "Cursor for technical planning."

How it works: 1. Paste a raw, unstructured requirements doc. 2. An LLM extracts the core deliverables. 3. A deterministic physics engine takes over—mapping the actual task dependencies and calculating the critical path based on your specific team capacity (e.g., 2 frontend, 1 backend).

The V0 Vision: AI coding agents fail today because they lack a strict architectural blueprint. By capturing the project as a deterministic graph from day one, we are building the unified layer where an LLM can eventually generate a V0 codebase without hallucinating.

I'd love for you to throw a messy requirements doc at it and tell me where my scheduling math breaks.

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