Courses Architectural Design Vibe Coding for Designers: Adaptive Toolmaking

Vibe Coding for Designers: Adaptive Toolmaking

Name: Vibe Coding for Designers: Adaptive Toolmaking
Price: 85.00 EUR

This workshop explores how designers can use AI, Python, and Grasshopper to build adaptive tools to control geometry across digital and physical workflows.

Days

Hrs

Min

Overview
Content
Instructors
Reviews

50 Seats

May 16, 17, 2026

13:00 - 17:00 GMT

Saturday - Sunday

Lessons in Progress

Beginner

8 Hours

Certificate — Learn

English

Unlimited Access

€100.00

€85.00

Last 1 seats at this price!

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Introduction of the workshop:

Every language has the same purpose: communication between two entities. With the proliferation of AI tools, it has suddenly become much easier to communicate your needs to a computer in plain language, rather than machine code. In this workshop, we will discuss how to use AI tools to create custom applications, web pages, and one-off Grasshopper tools.

We will start with how to describe a piece of software you want to use with an AI coding tool, how to start integrating real data, and how to export that data for use elsewhere. Then, we will go over how to make a piece of software ready for combining with another using hidden tricks for smooth communication.

Then we will start with Python and how to use it in Grasshopper to experiment with 3D-printed textures. Then, we will tie it all together by building a custom computer vision algorithm that produces data ready for Grasshopper to use.

What You’ll Learn?

Understand the basics of coding

How to install and use Python

How to prepare data to move between software

How to describe a software goal to AI effectively

How to edit and review AI-Generated code

How to structure code for integration using AI

Vibe Coding for Designers: Adaptive Toolmaking

Methodology:

This workshop will navigate the dynamic world of AI coding to learn the most resilient coding workflows for different types of problems. The goal is an understanding of how to figure out what problems you want to solve and the optimal tools to help you solve them.

We will use real-time data where available to help inform design decisions, where, instead of pulling a static set of statistics once, you can continuously review the exact conditions of a place. This new push into real-time allows architects to focus on the ongoing condition of their building post-delivery while still designing for a day-one occupancy.

With that foundation in accessing real-time data, we will move into the ways that you can construct unique data and output combinations to fit your own needs. This will include methodologies for Computer Vision, and how to creatively interpret this data into a pattern generator for a 3D printed object in Grasshopper.

The goal is to reflect on the open-endedness of the possible combinations of data source and data interpretation. By doing this, we can create projects that are even more dynamically specific to their location and to the data that is generated and constructed within them.

Program:

Day 1:

Information: Introduction to AI Coding
Demonstration: Gemini to Claude Workflow for Website Page
Instruction: Data Structuring for Communication
Application: Expand Website
Instruction: API 101
Application: Exports - JSON, How to speak to a computer
Application: Hidden Comments - how to make AI talk to AI

Day 2:

Information: AI Agency, Authorship, Biases, and Rapid Innovations
Instruction: How to Use Python + pip Install
Application: Bring it into Grasshopper
Application: DIY 3D Printing in Grasshopper
Application: Expand Grasshopper Applications to use JSON
Application: Python in VSCode
Next Steps - Local Models, Claude Code Agents, CV use cases

What You’ll Use?

Highlights:

Content

Instructors:

Jacob Lehrer

Biography

Jacob Lehrer is an architectural designer and researcher dedicated to exploring the intersection of architecture, technology, and ecology. Currently an M.Arch II candidate at the Southern California Institute of Architecture (SCI_Arc), he holds a Bachelor of Science in Architecture from Wentworth Institute of Technology and is an Advanced Study Fellow from MIT. His professional background spans from co-founding LMDA LLC, where he led design development for animal care facilities, to managing operations and space planning as a Project Coordinator for the MIT Mathematics Department. Jacob views architecture as a problem-solving discipline, leveraging his diverse experience to bridge the gap between abstract algorithms and physical space. A triple-accredited LEED AP (BD+C, O+M, ND), Jacob combines a deep commitment to sustainability with advanced technical proficiency in tools like Python, Rhino, Grasshopper, and KUKA robotics. His recent work includes developing the "Sentient Environment Engine," a custom computer vision algorithm for analyzing occupant behavior, and fabricating mathematical sculptures for MIT’s permanent collection. Whether teaching PAACADEMY parametric design workshops or publishing research on the ethics of language models, Jacob focuses on using computation to create built environments that are responsive, efficient, and tailored to their specific contexts.