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Grade Coach is a complete AI teacher toolkit built on a shared substrate: every paper you grade compounds into per-student concept-mastery maps. Tools include rubric-locked paper grading, printable worksheet creation, personalized practice, parent reports, password-gated student views, personalized grading (one answer key per student), and class deep-dive analytics. Powered by Google Gemini 3.1 and gpt-image-2.
The core mechanic: lock your rubric on the first paper, grade the rest of the class against the same locked interpretation. No drift between paper 1 and paper 30. The teacher is always the final check.
Private by default. Student work never trains any AI, never gets shared with other teachers or schools. Built by an ex-teacher with 10+ years in international classrooms (RMIT, Scotch AGS, ISB, HCMC University of Science).
Free tier: 10 credits/month with a free account, no card required. Pro: $15/mo for 500 credits. Power: $30/mo for 1,200 credits. Top-up: $10 = 300 credits that never expire.
VS Code
Grade CoachGrade Coach's answer:
Grade Coach is in early-customer phase (post-launch, pre-scale). Tested by teachers at institutions where the founder has taught or partnered:
Grade Coach's answer:
Frontend - React 18 + TypeScript + Vite - Tailwind CSS v4 - Zustand (state)
Backend - Netlify Functions - Google Gemini 3.1 Pro - OpenAI gpt-image-2
Database & auth - Supabase Postgres
Payments & ops - Stripe
Grade Coach's answer:
Enzo, the founder, spent more than a decade teaching in international classrooms โ RMIT, Scotch AGS, ISB, HCMC University of Science, plus partnerships with Hanyang University, Shandong UST, and Teach For America. The grading pile was killing his weekends.
He tried ChatGPT for nearly a full term before building anything. It worked โ for a few papers. Then it drifted. Same essay scored differently on Tuesday vs Friday. Handwriting recognition was unreliable. The model would invent rubric criteria the teacher hadn't asked for.
The realization: general chatbots aren't built for grading consistency across a class set. A tool that locks the rubric, applies it the same way every time, and lets the teacher stay the final authority โ that's what was missing.
Grade Coach started as a personal tool to grade his own classes. Then friends asked for access. Then schools. Now it's a complete teacher toolkit built on a shared substrate: every paper graded compounds into per-student concept-mastery maps that power worksheet generation, parent reports, and class analytics.
The founder still teaches the product the way he wished someone had taught him.
Grade Coach's answer:
K-12 teachers grading rubric-based assignments, with a wedge focus on:
Secondary audience: university instructors grading short-answer or essay work where rubric-lock matters more than question-grouping.
Grade Coach's answer:
Three reasons, in order:
The teacher is always the final check. Every AI score and comment is shown to you for review and edit before anything is final. Other tools auto-submit; Grade Coach treats AI as a first pass, not the last word.
Private by default. Student work never trains any AI, never gets shared between teachers or schools. We don't sell student data. The privacy line is locked: student work stays between you and your students.
Consistency across the class. Where other graders treat each paper as a fresh AI prompt (and drift between them), Grade Coach locks the rubric on the first paper and uses that locked interpretation across the whole stack. The same essay would get the same grade if you re-ran it tomorrow.
The product is also honest about what it isn't. No AI detection (skeptical that it works reliably). No auto-submission. No chatbot pretending. Just rubric-locked grading that gives you your evening back.
Grade Coach's answer:
The locked-rubric guarantee is the core mechanic. When you upload your first paper, Grade Coach locks the AI's understanding of your rubric, then uses that exact same locked interpretation for every paper in the class set. Paper 1 and paper 30 are scored against identical criteria โ no model drift, no inconsistency.
A few other things that set it apart:
Based on our record, VS Code seems to be more popular. It has been mentiond 1215 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Visual Studio Code, a code editor created by Microsoft, was first introduced on April 29, 2015, at the Build conference. - Source: dev.to / 3 days ago
The step up from there is an editor with a built-in agent like Cursor, Google Antigravity, Windsurf, or VS Code with a coding extension. These are code editors with an AI agent living inside them, and the difference is the responsible party for getting things from place to place. Instead of the software creator shuttling code between windows, the AI agent edits the project files directly and runs the GitHub and... - Source: dev.to / 18 days ago
For IDE-heavy teams, BYOK (bring your own key) can be interesting, no matter whether you live in WebStorm or VS Code. On the JetBrains side, the JetBrains AI plans and Junie BYOK docs allow it, and most VS Code AI extensions offer the same idea: keep the IDE, connect provider keys, pay the provider. - Source: dev.to / about 1 month ago
Option 1: Raw editing in IDE. You open the .md file in VS Code or whatever you use. Syntax highlighting shows you the structure. Maybe you toggle a preview pane. This works for quick edits but becomes painful for anything involving tables, diagrams, or complex formatting. - Source: dev.to / about 1 month ago
You'll need Python 3.8+ and pip for the quickstart, with venv recommended for isolation. Install the requests library for HTTP calls. VS Code with the Python extension works well as an editor, though PyCharm or Sublime Text work equally well. You'll also need a free Foxit developer account. - Source: dev.to / about 1 month ago
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