A Bicycle for the Mind

Amid the chaos of a world in crisis, I’ve found hope in an unexpected place: coding. With tools like Claude.ai and MCP, I’ve been building a web app to help food pantries serve their communities better—automating inventory, breaking language barriers, and streamlining processes. This isn’t just about code; it’s about turning anxiety into action, using technology to create something meaningful. If you’ve ever wondered how AI can amplify human effort, this is a story for you.

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Learning Through Building: Adding Sort & Translation Features to a Food Pantry Web App

Today was a journey of wins and "learning opportunities" as I worked on improving William Temple House’s food pantry management system. The morning started great - implementing sortable table headers was surprisingly smooth — I’m continually impressed by the coding capabilities of Claude.ai. Working with both Claude and ChatGPT, we created a modular code structure, which made it easy to add sorting without breaking existing features.

But then came the interesting part. When I began tackling multi-language support, my API requests to OpenAI exploded into the tens of thousands. The goal seemed simple: translate food items into our client community's languages. William Temple House serves many non-English speaking clients: Spanish, Russian, Ukrainian, Chinese, Arabic, etc. I’ve integrated OpenAI's gpt-4o-mini API for translations, and everything worked beautifully... until it didn't.

Turns out a rate limit is easier to hit once the database of food items reaches critical mass. Who knew sending thousands of translation requests over a period of just a few hours would hit OpenAI's daily cap? Probably everyone who bothered to read the documentation first. :-)

It's actually kind of funny watching the error logs fill up with "please try again in 8.64 seconds" messages. Claude as an AI coding assistant was invaluable throughout this process. When I got stuck on implementing sort functionality, it helped refactor the code while maintaining the existing event-driven architecture. Later, when we hit the translation rate limits, it suggested implementing batch processing and queuing systems - solutions I wouldn't have considered immediately.

Key takeaways:

  • Small wins matter: The sorting feature works great in my Test UI

  • Read API docs before sending 10,000 requests

  • Sometimes the best solution is to wait 24 hours for rate limits to reset; I should be taking a break on a holiday weekend anyway

  • Having an AI pair programmer helps spot potential issues before they become problems

Next steps? Take a brief pause while OpenAI's rate limit resets, then return with a smarter approach to batch translations. As frustrating as the rate limit issue was, it's pushing us to build a more robust system.

I’m going to use some of this down time to reflect more on the process of building this system. I’ve learned a lot about how best to leverage AI for software development, and hope others will benefit from what I’ve found along the way.

Video Lecture: 3D Modeling Basics for Beginners – Techniques, AR Tips, and Intro to AI Tools

I have some exciting news! October 23rd, 2024, I was once again invited to guest lecture at CMU School of Design. I decided to follow up with a recorded version to share. In this recording, made after the original lecture session, I cover the essentials of 3D modeling with a focus on beginner-friendly techniques. You'll find practical insights into mesh modeling, workflow tips for Blender, and an introduction to preparing models for augmented reality. The full lecture video is embedded below, followed by detailed notes that offer a step-by-step breakdown of theory and techniques for anyone new to 3D design. Dive in, explore, and start building your own 3D modeling skills.

Principles of Mesh Modeling

Note on Mesh Modeling Focus—Or Why This Lecture Focused Primarily on Mesh Modeling:

Meshes are the standard 3D model type used in real-time 3D engines—like Unity, Unreal, and virtually every AAA video game title in the last 30 years, going all the way back to Quake, by id Software in 1996.

Key Principles:

  1. Use Quad Faces Whenever Possible: Design your shape faces with quads instead of triangles and ngons.
    Reason: Quads are infinitely divisible, making it easier to adjust geometry resolution as needed. Tris and Ngons are not as flexible, which can lead to undesirable artifacts and poor topology.
    3D games primarily use triangles (tris) instead of quads because triangles are the simplest polygon shape and always planar (a flat surface), making them computationally faster to render in real-time on limited hardware, which was crucial for early gaming systems underpowered computer hardware. Essentially, triangles require less processing power to calculate and display on screen compared to quads, which have more vertices and edges.
    On modern computer hardware we can get away with more complex geometry, and it's generally a better trade-off to build mesh models from quads. That is, the computational costs are vastly outweighed by the benefits of evenly divisible face geometry and more manageable topology. Lastly, quads are easily converted into tris, by producing diagonal edges between the four vertices.

  2. Work from the Lowest Possible Polygon Count: Always start with the lowest polygon count (i.e., resolution) for your model. You can increase resolution later with subdivision modifiers, but it's not as easy to reduce the resolution later.
    Reason: Editing a high-resolution mesh is more difficult than working with a low-resolution one, which offers greater control and flexibility. It also takes much more processing power and memory, which will slow down Blender and increase the risk of crashes.

  3. Keep Base Shapes Simple: Keep your base shapes as simple as possible. When adding details, create those elements as separate objects. When you hit a milestone, consider duplicating a model or a collection of models to a new instance for further refinement.
    Reason: This approach makes 3D modeling more manageable, allowing for easier adjustments and maintaining clean geometry.

  4. Use Modifiers and Non-Destructive Editing Whenever Practical: Designing a symmetrical shape? Cut it in half and use a Mirror Modifier to cut your editing time in half. Keep in mind that the most complex designs can ultimately be derived from very basic shapes: Spheres, Cones, Toruses, and Cubes.

  5. Work From Reference Images, Even If Just A Few Basic Sketches: Press Shift + A to open the Add menu. Navigate to Image > Reference. Select the image file you want to use from your computer. The reference image will be added to your 3D Viewport, where you can position, scale, and rotate it as needed for your modeling task.

  6. Build The Overall Form First, and Then Separate into Smaller Objects: This will ensure that your designs are cohesive and edges are properly aligned. When you're ready to divide into separate objects, duplicate the objects into a new Collection.

  7. Experiment, Tinker, Explore, and Start Over: You're unlikely to get the design right on the first attempt. It's often necessary to work through the problem, and then start over from scratch once you've had enough time to explore the form. Reason: Your second draft will almost certainly be better than the first.

Blender Quality of Life Recommendations:

  1. Save Your Project Files Early and Often: Use Blender's "Save Incremental" (⌥+⌘+S) (Option + Command + S) to manage version control. Doing this will give you the freedom to fearlessly tinker and explore (as mentioned in the previous point) before settling on a final design.

  2. Crank Up The Number of Undo Steps: Open Edit from the top menu. Select Preferences to open the Blender Preferences window. In the Preferences window, click on the System tab. Scroll down to find theUndo Steps setting.

    Increase the value (the default is 32). If you have enough system memory, set it to 256 for more flexibility in undoing actions. Close the Preferences window to save your changes.

  3. Consider Using A Material Library: Blender has a basic built-in material library, but it's not very useful. Look into large libraries, such as PBR Material Asset Library + OneClick Add-on for Blender (https://shardsofred.gumroad.com/l/CfOnY). Creative Commons License (CC0) materials can be used for basically anything, and will save you time.

  4. Remember to Perform a UV Unwrap on Your Model Geometry for Best Results When Texturing: The most realistic textures in the world won't help you if your model doesn't have good UV Mapping. Remember the chocolate Santa Claus example? Proper wrapping is essential for creating realism with your models. https://docs.blender.org/manual/en/latest/ modeling/meshes/uv/applying_image.html

  5. Recommended Extensions and Add-ons:

    • VDM Brush Baker: Helps you create and bake Vector Displacement Maps directly in Blender.

    • Bool Tool: Boolean operations for complex shape creation.

    • Node Wrangler: Enhances node editing management.

    • Rigify: Automated rigging solution for character animation.

    • Loop Tools: Useful for organic modeling (with some bugs appearing

      in Blender 4.2—be sure to keep this add-on updated!).

  6. Other Useful Add-ons: Auto Mirror, F2, Extra Mesh/Curve Objects, Extra

    Grease Pencil Tools, Copy Attributes Menu, and MeasureIt.

    Bonus: Need furniture? Most of IKEA's catalog of products have 3D models available. Search for "IKEA" under Extensions and you can easily search and import 3D models into your scenes.
    Note: Ensure 'Allow Online Access' is enabled in Blender's System Preferences for add-on updates.

Create Augmented Reality Experiences for iOS with Xcode Developer Tools, Reality Composer, and USDZ File Format

Once you've finalized your form, added necessary details, and applied your materials, you should be ready to export your model.

Step-by-Step Instructions for Preparing 3D Assets for Export to USDZ:

  1. Duplicate Your 3D Assets and Collections: Create a new instance of your 3D assets specifically for export.

  2. Apply All Transforms: Hit A to select all visible objects, then press ⌘ + A (Command + A) and select All Transforms to apply.

  3. Apply All Modifiers: Apply all modifiers in the same order they were added to each model—except for subdivision, as tessellation data can (usually) be included without applying it directly to the models.

  4. Join All Components: Hit A to select all visible objects, then press ⌘ + J (Command + J) to perform a join operation.

  5. Export the File: Go to File > Export > Universal Scene Description (usd*).

  6. Configure Export Settings:

    • Include: Check Visible Only and Selected Only.

    • Blender Data: Select Custom Data.

    • Namespace: Use the default setting (UserProperties).

    • Blender Names: Enable this option.

    • File References: Set to Relative Path.

    • Convert Orientation:

      •  Z = Forward Axis

      • Y = Up Axis

        Note: Many other 3D tools, including Xcode's tools, interpret 3D models with a different axis orientation than Blender. If you don't apply this conversion, you'll find your model improperly rotated following import. If this happens to you, double-check these settings.

    • Use Settings for Render: Enable this option.

    • Object Types: Select Mesh, Volumes, Curves.

    • Geometry: Enable UV Maps, Rename UV Maps, Normals.

    • Subdivision: Set to Best Match.

    •  Rigging: Enable Armatures (if you have rigged and animated your

      model).

    • Materials: Select USD Preview Surface Network and Export Textures.

    • USDZ Texture Downsampling: Set to 1024px or up to 2048px (the

      largest size acceptable for iOS QuickLook).

  7. Update File Extension: Change the export file name extension

    from .usdc to .usdz.

  8. If no issues are encountered after export, you should be able to view your model in Augmented Reality on any iOS device. Open your exported file from iCloud, send it as an email, text, or AirDrop to another device to view.

Setting Up Xcode and Reality Composer:

The latest version of Xcode doesn't include Reality Composer, as Apple has shifted their focus to the Vision Pro. You can still access the Augmented Reality Tools for iOS devices, with some additional steps.

Step-by-Step Instructions:

  1. Download the Latest Version of Xcode 14: Download from the provided

    link: https://developer.apple.com/download/all/

    NOTE: You'll need to create an Apple Developer Account (it's free) to access the above link, or using this direct link: https://download.developer.apple.com/Developer_Tools/Xcode_14.3.1/Xcode_14.3.1.xip

  2. Extract and Rename The Older Version of Xcode: Rename Xcode.app to Xcode14.app and place it in your Applications folder.

  3. Open Terminal on Your Mac.

  4. Open the Applications Folder in Finder.

  5. Drag the Xcode14 App into Terminal: This will automatically add its path.

  6. Add to the Path: Next to the path, add: /Contents/MacOS/Xcode.

  7. Full Command Example: The command will look like:

    /Applications/Xcode14.app/Contents/MacOS/Xcode

  8. Run the Command: Press Enter to run the command.

  9. You should now have access to Reality Composer in Xcode. Click on the Xcode menu on the task bar, then click Open Developer Tool, and then click on Reality Composer.

    Learn more about using Reality Composer here: https://developer.apple.com/documentation/realitykit/realitykit-reality-composer
    Learn more about Apple Reality Kit and ARKit here: https://developer.apple.com/augmented-reality/tools/

BONUS: Generative AI and 3D

Tripo AI (https://www.tripo3d.ai/app) is an advanced generative AI tool that allows for both text-to-3D and image-to-3D model generation. This tool offers users an intuitive way to create complex 3D assets with minimal manual input, simply by describing what they need or providing a reference image.

Key features:

  • Text-to-3D and Image-to-3D Conversion: Users can input a detailed description or upload an image, and within seconds, the AI generates a draft model ready for refinement.

  • Prompt: "A pineapple-hedgehog with spiky fruit armor and leafy quills."

    https://tripo3d.ai/preview?share=9a57357e-6262-469c-afb1-c7af74d92c93

  • Prompt: "A 1980s sci-fi robot stylized as a Nintendo NES product."

    https://tripo3d.ai/preview?share=a08a55cd-9e66-48a5-be3d-85a26160e461

  • High-Speed Generation: Tripo’s AI processes are optimized for efficiency, allowing users to generate detailed models in a matter of seconds, ideal for prototyping or quick visualizations.

  • Customization Tools: After generating a model, users can adjust topology for increased details, or apply stylization, such as voxels.

  • Seamless Integration: Tripo3D supports a variety of export formats like .usdz .obj and .fbx, making it easy to import models into Blender and other software for further editing.

  • Generate full texture maps with PBRs: includes generation of PBR textures, adding even greater details beyond the geometry.

  • Automatic rigging and basic animations: Applies a basic animation rig to generated models and simple animations, such as a running character, to the model geometry.

Downsides:

  • Imprecise generation: just like AI image generators, results are unpredictable and often wrong.

  • Costs: Using this tool will require a membership plan, and has limited monthly credits, which limits usage.

CREDITS:

Thanks to all of these wonderful educators and content creators who continue to inform and inspire me throughout my 3D journey. Preparing this lecture required lots of time and consideration for how to condense what I’ve learned over the last five years into something I could demonstrate in under 2 hours. This wasn’t easy, but I had many fantastic resources to pull from.
If I’ve left anyone out, please leave a comment so I can include them here:

YouTube Creators:

Reference Files:

Robot model created with Tripo AI

Robot model with corrected orientation

Reality Composer demo file

Interactive USDZ demo file

Note: Due to a bug, the robot walking animation doesn’t playback in QuickLook AR for iOS.

HAVE QUESTIONS? ASK PHIL

Have questions about CAD, Fusion 360, or the Portland maker scene? Ask Phil! He’s a Principal Software Engineer at Autodesk, inc. and teaches CAD at Portland Community College. He’s also the host of Community Conversations series: Getting started with 3D modeling in Fusion 360

You can reach him at phil.eichmiller@autodesk.com

Phil Eichmiller — Principal Software Engineer at Autodesk, Inc.

TUTORIAL: How to use ultra realistic Quixel Mixer materials with Fusion 360 [Part 2]

Welcome back! In Part 2, we’ll explore adding Quixel Materials to your designs in Fusion 360 and setting up a rendering scene. If you haven’t already, review Part 1 and install Quixel Mixer. You’ll want to create and export a mix for use in Fusion 360 prior to the steps in this tutorial, or download an example material set here.

First, let’s create a new project in Fusion 360:

  1. Creating a new Fusion 360 Project

After you open Fusion 360, Click “Save” and give your project a name. In this example I used “QuixelMaterialDemo.”

After you save your project, we’ll want to create a new component and make it active.

2. Create a new Component

This is generally a good practice with Fusion 360, because we can more easily manage changes made to the design when the timeline is broken up by individual component histories. Name your component “Floor” and then make sure “Activate” is selected (should be by default), click “OK” to continue.

Next, we’ll want to create a sketch to define the floor’s dimensions. Click “Create” and make a Center Rectangle on the bottom plane.

3. Create a Floor

Make your sketch 3 meters x 3 meters in size, with the Origin at the center. Click “Finish Sketch” to continue. If you’ve done everything right, then you should have a sketch that is fully constrained (i.e., you’ll see black lines instead of blue lines for the outer dimensions of your sketch).

Next, we’ll extrude the sketch below the plain. This will create a new body, based on our sketch dimensions.

Click Create and then Extrude. Then, extrude the sketch -1mm below the plane and click “OK.”

Next, Save the design. You’ve created your first body and now would be a good time to save your progress.

Note the reason for your save and Click “OK.”

Next, we’ll want to change the Appearance of our floor. Click Modify Appearance to bring up the Appearance Window.

4. Add material

Here we can see the default material for the Floor body. We’ll want to replace that material with our Quixel Mix. To do that, let’s start by downloading a similar material.

Note: in general, you’ll find it is easier to add Quixel Mixer materials when you adapt an existing material in Fusion 360 with similar attributes. In this case, we can use the existing Asphalt Material.

After the download finishes, click and drag the Asphalt material into your design.

We can then replace the default material with the Asphalt.

5. Replace Fusion 360 Material with Quixel Mix

Next, we can begin modifying the Fusion 360 Asphalt material with the Quixel Mix.

As mentioned in Part I, the materials in Fusion 360 are made up of individual map image files:

Albedo/Diffusion/Color — the color a material reflects

Normal and/or Height Maps — the bumps and imperfections along a surface

Roughness — the smoothness of a surface (ranging from a sharp reflection to fuzzy/diffuse)

Reflectance/Specular/Metalness — the reflectiveness of a surface (ranging from mirror finish to a dull surface)

Anisotropy/Ambient Occlusion — the shadows along a surface

Refractive —how light bends through a surface

Emissive — how much light a surface emits (glow)

Translucency/Opacity — how transparent a surface is to light

If you’re using the included sample images, you’ll find some but not all of these maps. Depending on what materials you’re mixing, you’ll need different image maps. The sample image package includes:

Floor_Diffuse.png — Color (placed in Parameters)

Floor_Roughness.png — Roughness (placed in Parameters)

Floor_Specular.png — Reflectance (placed in Parameters)

Floor_Normal.png — Normal (placed in Relief Pattern (Bump))

Floor_AO.png — Anisotropy (placed in Advanced Highlight Controls)

By replacing and adding these map files to the Fusion 360 Asphalt material, you can transform it to the Quixel mix. To start this replacement process, open the Appearance window, double-click the Asphalt material and then click “Advanced…”

Rename the material to “Quixel_Asphalt” to distinguish the material from the original Fusion 360 Asphalt.

Under Parameters, we can add three (3) image maps. First, we’ll apply the diffusion/color map to the Image input in Fusion 360. Click on the Image filename 1_mats_surface_asphalt_color.jpg and navigate to your replacement images.

Select your Albedo/Color/Diffuse map file. If you’re using the sample images, it’s the file named Floor_Diffuse.png. Click Open to replace the default image file.

Next, we’ll repeat the process with the Reflectance and Roughness maps. By default, these two material attributes are set as Slider values, click the drop down arrow and then select Image to replace the slider value with an image map.

Next, select the Metallic/Specular image map if you’re using the sample images, select Floor_Specular.png and click Open.

Next, repeat the same steps for the Roughness value. Select Image and then select your Roughness Map. If you’re using the sample images, select the Floor_Roughness.png.

Now that we’ve completed the three Parameter maps, we can move on to the Relief Pattern (Bump) map. Once again, we’ll replace the default image file (1_mats_surface_asphalt_.jpg) associated with the material. Note: Fusion 360 supports both bump and normal maps. If you want to know more about these two approaches to texturing a 3D model, then click here.

Next, we need to change the Relief Pattern from a Height Map to a Normal Map. To do this, we need to Edit the image.

Next, scroll down to Advanced and change Data Type to Normal Map.

Next, we need to ensure that all of our maps are using the same Sample Size. Be sure to repeat this step for all image maps. We also need to ensure that all of our Maps have Linked texture transforms. Check the Link texture transforms under the Transforms section of the Texture Editor. Be sure to repeat this step for all image maps.

These steps are important, because they ensure that all of the image map data are aligned equally to the material in Fusion 360. After you’ve verified these settings, you can click “OK” to finalize the changes to this material.

Now that the material has been updated you can Close the Appearances window.

To check and validate our new material, we need to switch to the Render Workspace in Fusion 360. Click on the Workspace button, and change it from DESIGN to RENDER.

6. Test render scene

Next, let’s save the design to capture the new material settings in your Fusion 360 Timeline. Click File and Save.

Fusion 360 will prompt you to describe your save point. Let’s name this save “Quixel Material Added” and click OK.

Before we can test our new material, we need to edit the SCENE SETTINGS from the SETUP Menu. Open the SCENE SETTING Window and Click+Drag “Dry lake bed” to the Current Environment and then Click Close.

We also need to change the IN-CANVAS RENDER settings to FAST, so that we can easily see the material’s performance during rendering. To do this, click on the IN-CANVAS RENDER SETTINGS icon and Click on the Fast tab. Then, Click OK to update the rendering method.

Next, we can preview the rendering, and see how the various maps work together under different lighting conditions. To do this, start the In-Canvas Rendering and then open Scene Settings, click on the Position Icon to bring up the Rotation and Scale Sliders. By changing the rotation, you can see how the surface of your floor object casts shadows at different angles, corresponding to the surface material.

Make sure to save your project to retain your rendering settings. If you’ve made it this far, then congratulations! You now have all of the information necessary to import Quixel Mixer materials in Fusion 360. In Part 3, we’ll explore some techniques for applying these materials to complex geometries, and how to post-process your images for additional realness. In Part 4, we’ll take these realistic models and generate Augmented Reality experiences for iOS.

Stay tuned!

Core77 Design Awards 2022

I’m very pleased to see Stuart Candy’s project “Imagination is a Commons” is the winner for Core77’s award for Speculative Design, 2022. Back in March of 2021, I received a somewhat unusual paid request — for studio photography services. One year into the COVID-19 pandemic, when vaccines were still out of reach for many, and facilities and institutions remained shuttered, I was suffering from cabin fever isolation and grieving the death of my uncle.

I was finishing up my second Master’s degree, and Pittsburgh had only begun to thaw after a long and difficult winter. Without access to the campus photography studio, Stuart had reached out to his network at Carnegie Mellon, seeking alternatives. As luck would have it, during my undergraduate studies I invested in my own studio photography setup.

My barebones digital photography setup

Scrappy resilience was a constant theme throughout 2020. Students without studio space were constantly finding ways to make do. This was one of those rare moments where few compromises were necessary, and I had everything I needed on hand. Imagine my surprise when I was handed a bag full of artifacts from the future…

T-shirts from a coding festival in the year 2030

Social distancing and staying home (for the better part of a year) had distorted my sense of time. In the first year of the pandemic, there were days and weeks that seemed to vaporize, and weekends that lasted a month. To hold these artifacts, and to focus on them through a viewfinder, I felt as though I had stepped completely outside of time and space. This was a perfect diversion from my mundane existence, and a reminder that this too shall pass.

Thank you, Stuart and Ceda. And congratulations!

Scripting in Blender

For folks who use blender to create animated characters for Unreal Engine, you might find the process of creating a rig fairly tedious. You may also discover that some constraints in Blender are causing problems with your exported skeleton in Unreal.

If you need to sanitize your bone constraints, this work can be labor intensive if done manually.

Here’s a simple script that will automate that process. (shoutout to manuDesk for providing this)

import bpy

for bone in bpy.context.selected_pose_bones:
    for c in bone.constraints:
        if 'Constraint Name' in c.name:
            bone.constraints.remove(c)  # Remove constraint

Replace “Constraint Name” with the name of the constraint you wish to remove from your rig, and then run the script. This could save you hours of work.

Suppose you need to copy constraints between a control rig and a deform rig. CGDrive has provided an entire video tutorial on this process. Below, is the code used in their script. Watch the video for a basic workflow, as there is some preparation necessary for this script to work.

import bpy
sel = bpy.context.selected_pose_bones

for bone in sel:
    name = bone.name
    bpy.context.object.pose.bones[name].constraints["Copy Transforms"].subtarget = name

Summer Internship: mid-July Update

It’s been nearly a full month since my last update, so what have I been working on?

The last few weeks have been incredibly busy. I’ve had several interviews and job application submissions. My gallery and design pages received some helpful updates. I’ve successfully built a standardized data format for a visualization project and introduced some of my fellow interns to the history and purpose of data visualization, and its role in matters of social justice and equality. I’ve also continued to make leaps and bounds on my 3D character work.

I’ve resolved the primary issue that was plaguing me early on in this project: mesh topology.

To be efficient for a game engine, it’s important to resolve mesh geometry with minimal faces. Unreal Engine 5 supports a new level-of-detail automation called “nanite,” which allows 3D modelers to create elements with a virtually unlimited number of faces (geometric detail). This does not seem to work with animated characters, however — if you know a way around this, please send me a message!

A “face,” in this context refers to a plane that has 3 (tris) or more points. Ideally, the geometry should have faces with 4 points (quads). While modern engines and graphics hardware have gotten significantly more advanced since the early days of 3D gaming, it’s nevertheless still important to avoid models with excessive polycounts (the sum total of faces in a model).


The challenge with my model is that it requires several tangent geometries that intersect with a central body. Image if you were modeling Tree Character, and you need to cover the various branches with leaves, blossoms, or pine needles. Blender can easily generate these elements using weighted vertex mapping and particle systems (hair). The difficulty, however, comes from trying to export this data for use in Unreal Engine.


Unreal Engine supports FBX models for import, but FBX models do not support shape keys. By default, Blender applies Particle System modifier as a shape key. You can, however convert particle instances into their own individual body/mesh component in Blender prior to export. This works, Unreal will interpret the model as being several individual bodies with shared coordinates. When exporting this type of arrangement, animation rigs cannot deform the free meshes — your leaves (or whatever) will stay in place while the rest of the tree animates.

You may already be thinking to yourself, “why not just combine the meshes?” And since the beginning of this project, I anticipated that this might be necessary at some point. The challenge then is how to create a combined mesh that is free of visual artifacts. Additionally, the boolean modifier in Blender only allows you to select a single target body to combine (union).

Thankfully, there is a Blender add-on for this last issue: BoolTool.

Suppose you want to combine all of your individual leaf meshes to the main tree body, but you know it would be insanely time consuming to go through the tedious sequence of selecting each leaf, one at a time, applying the modifier, creating a new modifier, and repeating that x700.

You could try writing a script, to automate this process, but you’d need to write it in python, and that would be a can of worms unto itself. You can already imagine the mission creep setting in…

BoolTool makes this process dead simple. You just select the mesh body you want everything to join with (active object), and then select all of those other meshes. Go to the BoolTool menu and select “union.” You may think that Blender has crashed, but give your computer a break. Grab a cup of coffee, meditate, embrace the here-and-now… *BING* [Your mesh combine operation is complete!]

BlenderBool.png

Assuming you created an efficient mesh, primarily out of quad faces, with intersecting meshes containing the same number of vertices, then you should have a single mesh geometry that is ready for rigging and animation.

I’ve tried dozens of other approaches so far, and this method produces the best results all-around: faster, easier to execute, high fidelity, and with the lowest poly count.

I’m still working out the kinks on my current model, and the animation sequences will be a next-level creative challenge for me (I have a lot of inspiration and ambition on this front), but I feel confident in the current direction, and early tests have been quite promising.

I’m also starting to make simple prototypes for augmented reality, and will add some notes about that later this month.

Week 3 and 4 Update: 3D content migration woes

This update is coming in late, as I’ve been trying to come up with some way to explain the difficulties I’m facing with this project, while also respecting the privacy and IP. I’m leaning heavy on metaphor, but…

Imagine there are three people sitting at a bar. One of them speaks Dutch, English, and German (but only okay German, not great). Another speaks Spanish, some English (okay-ish grammar, few nouns), and fluent German. The last person at the table is a little bit unusual. They’re a rapper from Japan, they speak fluent Japanese and a little English. As a child they were an exchange student in Germany, but they’ve forgotten most of what they learned. The rapper also insists on speaking-as-quickly-as-their-mouth-can-run. They never slow down. Speed is everything.

They all have some overlap, however imperfect, in their spoken languages, but none can understand each other perfectly. This is what it feels like to develop assets for a still-in-beta realtime engine, while leveraging a parametric modeler, an open source 3D creator tool, and adhering to standards from a professional VFX and CGI-specific 3D tool.

This week my primary focus has been on getting Blender and Unreal Engine to talk to each other. Unreal prefers FBX file format (Autodesk Maya Native). Blender can export most data in this format, but there are a few catches:

  • No shape keys

  • Subdivision data is limited to a single iteration

  • Dynamic animation can only be exported with baked physics, and is limited to vertices and face transformations (kind of, depending on what you’re doing).

Additionally, Unreal doesn’t quite understand Blender’s material system. It will still export textures and UV map data, but you’ll need to build the material blueprint to recreate whatever you have in Blender. It is far from being a 1:1 exchange.

There are also a many weird quirks:

In Blender, the default units are meters. In Unreal, the default unit is centimeters. Before exporting from Blender, you need to set Unit Scale to 0.01. If you switch units in Blender to centimeters and leave the Unit Scale at the default of 1.0, then you’ll experience strange anomalies for things like collider bodies, skeleton mesh, etc..

In naming the rigging elements (IK skeletons, etc.), you DO NOT name any bones “root,” because Unreal will assume a hierarchy which may differ from your hierarchy (parenting) in Blender. However, you may rename the Armature container to “root” to conform to Unreal’s hierarchy.

Lastly, the only rigging data that reliably translates between Blender and Unreal Engine are deform bones and baked animations/transformations.

I’ve reached a stumbling block with my current 3D character. I can rig the character to animate, and even output that data in a manner which Unreal Engine can interpret. This comes at the expense of a vital visual element that was procedurally generated. What comes next is a difficult choice:

I can either integrate procedurally generated elements into a single mesh geometry (potentially compromising some rendering performance and visual fidelity) but without having to rework existing animation and rigging, or I can attempt to recreate the procedural mesh instancing I developed inside Blender but natively within Unreal. The former will be labor intensive, but I understand the tools well enough to work consistently toward a known output. The latter involves many unknowns, but I will also gain a deeper understanding of workflows within Unreal Engine. I’m attracted to this latter option, but I don’t know if it is best for the client and their expectations.

Week 2: Summer Internship

This week I continued working on 3D asset creation. My basic approach so far has been to start with a simplified geometry from Fusion 360, then export that design as an .FBX (Autodesk Maya file format), import the FBX to Blender for UV mapping, material, and motion rigging. There’s probably a more streamline way to generate this content, but from a feasibility standpoint, this approach allows me to be flexible and to use different tools for discrete tasks. This week I will be importing these combined assets into Unreal Engine.

This week was also my final week for the term at PCC, where I have enrolled in their online course for Advanced Fusion 360. I’ve been working on a group project, and designing assemblies for use in a solar projector system. The design is based on COTS (commercial off-the-self parts), which required me to draft profiles to meet engineering specifications.

Picatinny rail specification downloaded from wiki-commons.

Picatinny rail specification downloaded from wiki-commons.

The final deliverables are due this coming Saturday, and there is still a good bit of work to be done before we get graded on this project. Nevertheless, I am very pleased with the current state of things. I’ve been using Quixel Mixer to produce more realistic rendering material than the library included with Fusion 360. I say, “more” realistic because Fusion 360 already has some excellent materials. Take a look at this rendering of a Bushnell 10x42 monocle (one of the components in this project):

Bushnell Legend 10x42 Ultra HD Tactical Monocular Black rendering v14.png

I haven’t yet added any details, but as you can see, the rubberized exterior and textured plastic hardware are fairly convincing. Now, take a look at the mounting hardware rendered with Quixel textures:

Picatinny rail bracket rendering v7.png

An important component in photorealism is the inclusion of flaws. Real life objects are never perfectly clean, perfectly smooth, or with perfect edges. Surface defects, dirt, scratches, and optical effects play an important role in tricking the eye into believing a rendering. With Quixel Mixer, it is possible to quickly generate customized materials. While this product is intended for use with Unreal Engine and other real-time applications, it does an amazing job when coupled with a physical based renderer.

Picatinny rail set with hardware and bracket.

Picatinny rail set with hardware and bracket.

I’m excited to see what can be done with these materials in a real-time engine, especially given the advanced features of Unreal Engine 5. Fusion 360’s rendering is CPU driven, whereas Unreal is GPU accelerated. With both Nvidia and AMD now selling GPUs with built-in raytracing support, it won’t be long before we see applications that offer simultaneous photorealism rendering within modeling workflows.

Additionally, GPUs also work extremely well as massively parallel computing units, ideal for physical simulations. This opens up all kinds of possibilities for real-time simulated stress testing and destructive testing. It wasn’t that long ago that that ASCI Red was the pinnacle of physical simulation via supercomputer. Today, comparable systems can be purchased for less than $2,000.

Of course, this price assumes you can buy the hardware retail. The current chip shortage has inflated prices more than 200% above MSRP. Fortunately, with crypto markets in decline and businesses reopening as vaccination rates exceed 50% in some regions, there are rays of hope for raytracing-capable hardware being in hand soon.

Week 2 mini-update: outputting video from Unreal Engine 5

Usually, I only update my blog on Sunday nights — I like to reflect after the week is done and I’ve had a full dose of daylight to consider what matters.

I’m breaking that rule because I’ve learned something that I think might be useful to others. Last week, Epic Games released a preview of Unreal Engine 5. If you haven’t looked at this tech, it’s worth your attention. We’re rapidly approaching a point where individual creatives (equipped with modern hardware) will be capable of producing photorealistic graphics in realtime. This is due to a convergence of procedurally-generated content, open libraries providing physically based materials, templates, and raytracing technology.

I’m a huge advocate for 3D technology. Being able to show something instead of telling it is huge. Consider all of the times in your life that you had an idea, something that you could clearly, vividly see inside your mind, but you felt was difficult or impossible to describe? What if you had the tools to quickly take your idea and represent it visually, with no limits to fidelity or realism? These tools exist, and they are getting better every day. Additionally, many of these tools are free and have a wealth of community-led learning and support.

Today I was asked to come up with a way to capture video from unreal, and I discovered a great way to do it in Unreal 5 Engine. Here’s how!

Geigertron’s Very Practical Guide to Exporting Video From Unreal Engine 5

For this example, I’m using a sample project based on MetaHuman Creator, you can download UE5 preview, it’s all free!

1) After opening the sample project, click on the clapperboard icon (“Cinematics”).

2) In this example, there’s already a sequence (MetaHumanSample_Sequence), so we’ll select that. To learn more about creating a cinematic sequence, click here.

UE5_Record_Cinematics_3.png

3) Within the sequencer window, there is another clapperboard icon on the top row menu. Click this to open the “Render Movie Settings” window.

4) From the Render Movie Settings window, you can select, output format for image and audio, resolution, compression, and output file location. After setting up, click the “Capture Movie” button on the lower right and wait for UE5 to finish rendering and saving your output file.

UE5_Record_Cinematics_5.jpeg

This operation completed in near realtime and the output is pristine. If your scene contains audio, then you’ll need to merge/combine it with the video output. I did this in After Effects, but other programs would probably work equally well.

Week 1: Summer internship

This week I kicked off an internship with Astrea Media. We began with a general meeting via zoom, with each intern and staff member introducing themselves. I’ll be generating some 3D content for an exciting new project and so far the work is going well. This is not my first experience working with a realtime engine. I’ve done some work in Unity, but never to a polished degree. Our team is working with similar technologies, and I’m eager to learn more about this process.

This week I began optimizations for an existing 3D model. I discovered several hindrances to efficient rendering: absurdly high poly-count, textures in needlessly large image format, non-solid mesh geometry, etc. Rather attempting to rework this model, I instead decided to explore a new design. Due to the organic shapes for this asset, I decided to use Fusion 360’s Sculpt workspace. The sculpt workspace enables designers to create complex shapes with smooth surfaces (e.g., car bodies). There are a few trade-offs to this approach:

  • Non-parametric design

    • Sculpt bodies are based on t-splines (I’ll say more about this later), and do not offer design history/timeline functions

  • Symmetry functions

  • Rapid mesh generation

  • Efficient generation organic shapes

  • T-splines

    • 3D modeling is achieved through a variety of mathematical models for defining shapes. T-splines allow for the creation of freeform surfaces that are defined by a matrix of control points. While meshes tend to be defined by triangles, t-splines work best when all faces are defined by 4 vertices (T-shapes and rectangles).

This last point is important.

Screen Shot 2021-05-30 at 21.19.24.png

This sphere seems like a perfectly logical shape. Indeed, if you click “FINISH FORM” in the upper right corner, Fusion will compute this body and create a solid. Seems simple, right? There’s just one problem: the top of that sphere contains faces with only 3 vertices. As mentioned earlier, t-splines work best when faces are made of 4 vertices. The sphere computes just fine, but as soon as you begin to manipulate this shape, there’s a very good chance that all of those converging 3-point faces at the top and bottom will begin overlapping each other. For example, see what happens when I attempt to apply symmetry to this shape:

Screen Shot 2021-05-30 at 21.51.47.png

Instead of maintaining the converging vertices, the solver calculated something like the iris on a camera.

To avoid problems like this, there’s another option: quadballs.

Screen Shot 2021-05-30 at 22.03.43.png

As you can see, this sphere doesn’t have the same aggressive converging vertices as the other model. The advantage here is that each face can also be split diagonally, efficiently creating triangle mesh faces with minimal distortion.

Screen Shot 2021-05-30 at 22.09.32.png

When exporting this geometry for use in a realtime engine, the mesh conversion produces a high-fidelity representation of the t-spline body, preserving shape details.

Week 15: Final Project Update

This will be my final update for the Studio II project. I feel a complex blend of emotions as I write this. I am relieved to be done. I am also sad to know that my time with this team has come to an end. I consider myself incredibly lucky to have spent so much time working with some truly amazing designers. I don’t know if I will ever experience anything like this again, but I hope so.

Remote collaboration has few perks, and I was lucky to be working with folks who helped to make this experience so much fun

Remote collaboration has few perks, and I was lucky to be working with folks who helped to make this experience so much fun

The work we have done this week feels different for many reasons. We had to prepare something for a large and diverse audience, not all of which knew or were familiar with the context of our work. Additionally, we also needed to use this time to tie up remaining loose ends—we needed to reach an end state where our process could feel somewhat conclusive.

Our efforts were just as collaborative as ever, as we divided up the labor of our remaining tasks. I was incredibly reassuring to know my team members strengths and capabilities. Knowing who was working on a particular task was reassuring. For my part, I was busy scrubbing through a timeline in After Effects, rapidly assembling visual representations and edited footage to make a convincing newscast from the future. Considering the constraints of remote collaboration, I’m very pleased with the final product.

I have continued to ruminate about over this notion that the future is something we cannot predict, but rather something we build through imperfect knowledge. I question the power our team has to influence this process, not because I lack the confidence in our shared abilities —as I said earlier and often, I’ve been working with an amazing team— but more of a concern around consequences of inspiration. Our process was far from perfect. The vagaries of a pandemic distorted every effort. The educators we sought to connect with were terribly busy. Our own team suffered from fatigue and sleeplessness as we juggled future careers and other academic expectations. The complexity of this topic is well beyond the scope of fifteen weeks of diligent inquiry.

I cannot speak for the entire team, but I know that for me personally our exploratory research was the most intimidating phase. It was immediately clear that we were engaging in a very difficult problem. Education intersects with so many other areas of study. It is a problem of policy, culture, funding, methodologies, and it is weighed down by a history of systemic inequality and racism. Generative research methods were the biggest surprise. I was astonished by what could be gleaned through a participatory process. Including educators in the generation of concepts was exciting, and I wish we had more time to engage in this work.

Our final concepts are a reflection of many perspectives and early prototypes generated by K-12 educators

Our final concepts are a reflection of many perspectives and early prototypes generated by K-12 educators

Every phase also felt too short. We needed to move on before we could fully digest what we were learning. Nevertheless, I stand behind the work we have done, because I know it represents the best we had to offer. I’ve known that design is a messy process long before my time at CMU, but I now have a much clearer sense of what it means to engage with that mess and to assemble something coherent. This work is not easy, and it is never, ever truly complete. The deadlines for a design project function like the layers of silt in a fossil record. The strata of every layer represents a progression with no clear ending or beginning. We can always dig deeper.

I hope these artifacts will inspire others as they have inspired us.

Screen Shot 2021-05-14 at 8.14.32 PM.png

Our team has assembled a project homepage. There you will find more comprehensive information about this work, the final outcome and documentation. Check it out!

Week 14 update: The Late Edition

The final push is now upon us. This past week I’ve been working nearly around the clock with my team, pushing to bring about our future vision. One of the most labor intensive, yet rewarding parts of this project has been the production of a newscast from the future. We’ve made countless script revisions, scraped stock images, sound, footage, and crafted motion graphics elements to bring this story to life. It’s been challenging, but I’m excited to see the final results.

What’s working: our approach to generating a video is deeply grounded in research. We’re incorporating concepts generated with participants — public educators who so generously gave us their time and perspectives on the present and future state of teaching in American schools. We’re also building our story to represent several systems-level shifts, including national legislation, teachers union contracts, and individual school reforms. We used several different futuring frameworks to develop these narratives, including: cone of possibility, backcasting, STEEP+V, Multilevel Perspective mapping, affinity mapping, and worldview filters.

Concepts+ MCCC - Version 2 MLP and STEEP+V Sorting.jpg
MLP_Past.png
futurescone-cdb-4.png

This process has been anything but precise. The future is something we build, not something we predict through careful measurements of trends. Understanding this truth has been very reassuring. Now that we are approaching a conclusion, I feel as though I have been on a long drive through undeveloped territory. The daylight of exploratory research gave way to the twilight of generative research and in the pitch of night we evaluated concepts. With only one headlight, we squinted off into the distance, to read the signs. Sometimes the precipitation of a pandemic obscured everything, but we relished the intermittent moments of clarity.

Those latter kinds of moment were by far the most exciting. “Oh, oh, what if…” was a common preamble to productive yet heady conversations with peers over zoom, as we scrambled together various visual representations in Miro and Figma. 

Concepts+ MCCC - Frame 26.jpg
Concepts+ MCCC - Frame 28.jpg

This workflow has been essential to synthesizing content and a visual language for our video, which we’ve been iterating on through various stages of prototyping. I’m concerned about the overall fidelity and recognize that this will be important to suspension of disbelief for our intended audience — policymakers and various stakeholders connected to PPS must find this artifact compelling enough to act and bring these concepts into a shared reality.

Concepts+ MCCC - Frame 29.jpg
Concepts+ MCCC - Frame 30.jpg
Concepts+ MCCC - Frame 31.jpg

On the technical side, video editing and motion graphics are computationally intensive tasks. I built a beefy workstation prior to starting at CMU, and this machine has been essential to so many tasks and assignments. Nevertheless, I’ve found that this work has strained my system’s capacity. I’ve purged files to make room for temporary caching and rendering outputs. I’ve reset my router in a desperate effort to speed up the transfer of data to Google Drive, and ran my system in a barebones state to maximize resources available to Adobe CC’s memory-hungry apps.

The stress I place upon the tools I use to design are complemented by the stress I’ve applied to myself. My sleep has been intermittent. I take short naps on the couch and found myself on more than one occasion this week working through the sounds of birds before the break of dawn. These late night hours are quiet and free of distraction, but tend to make the day that follows less than appealing. I’m staying awake through this last week of lectures, but finding my mind trailing off into thoughts about the timeline and how I might optimize frame rates for nominal render times. I’m obsessed with getting this video done, but know that this pace is not sustainable.

Week 13: Artifact Generation

We’ve began to generate assets for our final artifacts. This should be an exciting time for us. For the last 13 weeks, we’ve been living and breathing the problem space. The future of Portland Public Schools is not a matter of fate, it is something that will be built — not only designed, but also transformed by external forces and deliberate interventions. This work and our team’s research are only one tiny piece of this larger unfolding process, and we cannot know what impact (if any) will come from what we have done.

On some level, I cannot help but feel a little bit sad as we conclude this work. I have a very real sense of the scope of this issue and understand that fifteen weeks cannot generate anything conclusive. Nevertheless, we must honor this process and the deliverable. There is an underlying contradiction in this work. What this project calls for is “bold humility.” We know that our research is not conclusive, we also know that without bold presentation, we cannot inspire meaningful change or the greater vision by Prospect Studio.

Screen Shot 2021-05-02 at 23.16.55.png

Our primary concept is a news story about PPS holding their first ARC summit, and what it means for the future of Portland schools and teachers. We can use this medium to communicate the most salient details while glossing over the more bureaucratic aspects of our system level thinking. For secondary artifacts, we’re thinking about “swag” that is typical for a professional conference, as well as a custom logo for the ARC council.

Screen Shot 2021-05-02 at 23.53.35.png
Screen Shot 2021-05-02 at 23.53.27.png

I’m feeling a lot of pressure to resolve these artifacts to the highest fidelity possible. I know that the success of this project rests somewhat on our ability to persuade others, and we cannot know how this work will be interpreted if the artifacts are not convincing or feel too generic. I’m also worried that we have spent so much time working on the particulars that we haven’t given ourselves room for making these things.

I wish that we had a better sense of what is expected, and how craft will be factored into our grade. This is the first time that I’ve taken a studio class where nothing was made until the last two weeks. I expect that our team will be evaluated on the strength of our research and the clarity of our concepts, but as a studio class, I cannot shake this feeling that we should have been crafting prototypes along the way.

NewsMockup.png

My hope for this week is that the momentum of making and the joy of purely creative pursuits will have a feedback effect to keep us motivated through this final push. I’m excited about the potential for the project even though we are still grappling with an incredibly high degree of uncertainty.




Week 12 Update: Evaluative Research Presentation and Reflection on Reaching The Project's Final Stage

This week our team presented our evaluative research to Prospect Studio (Fiona and other representatives were asynchronous for this session) and our guest, Arnold Wasserman. This presentation is the last before our final deliverable, and represents the conclusion of our research phase. While there are some loose ends for us to address (and further evaluation of our concept has not yet been attempted), we are now in the early stages of artifact synthesis.

The last few weeks have helped our team to understand the importance of user evaluation, what strategies do and do not work well in a remote/online context. In particular, we learned that building a survey is a miniature design project unto itself. The creation of an interactive system, and evaluating the results required significant labor up front and a lot of uncertainty throughout. Nevertheless, I feel that our team was successful in achieving specific goals.

I’m proud to say that we managed to get several different concepts in front of several educators from around the country as well as from within PPS specifically. We successfully navigated and sorted through feedback to gauge overall patterns of responses to several concepts as well as system-level evaluations. We managed to coordinate and divide our labor effectively, and communicated asynchronously as we brought key components together. This process was mirrored in the creation of our latest slide deck for Wednesday.
We received helpful feedback and challenges to our concept following our team’s presentation. As previously has been the case, our team had a good sense of who ought to respond to specific questions, since our divided labor has granted each team member some degree of specialization and familiarity with the topic we’ve been researching. Specifically, Arnold Wasserman was curious about how our artifacts could communicate these concepts in a compelling and persuasive manner. Arnold Wasserman pointed out that school boards and the people elected to them, have a tendency to be self-serving, to the detriment of the districts they represent. He questioned how our concepts would overcome the significant obstacle of implementation, especially given the fact that school boards and public officials hold the levers of power and the teachers are functionally an underclass in the United States.

This is something I’ve been thinking about since the beginning of this project, and I related back to these thoughts in response. My ideas are largely based on the work of Donella Meadows, and her famous essay on leverage points.

PLACES TO INTERVENE IN A SYSTEM

(in increasing order of effectiveness)

12. Constants, parameters, numbers (such as subsidies, taxes, standards).
11. The sizes of buffers and other stabilizing stocks, relative to their flows.
10. The structure of material stocks and flows (such as transport networks, population age structures).
9. The lengths of delays, relative to the rate of system change.
8. The strength of negative feedback loops, relative to the impacts they are trying to correct against.
7. The gain around driving positive feedback loops.
6. The structure of information flows (who does and does not have access to information).
5. The rules of the system (such as incentives, punishments, constraints).
4. The power to add, change, evolve, or self-organize system structure.
3. The goals of the system.
2. The mindset or paradigm out of which the system — its goals, structure, rules, delays, parameters — arises.
1. The power to transcend paradigms.


In particular, look at points three and four: the power to self organize and the goals of the system are key to understanding the forces necessary to reform PPS to more closely resemble the vision from Prospect Studio. I agree with Arnold Wasserman’s observation regard the school boards and policy makers, but I also see a real opportunity with this difficult and problematic group. They hold the levers, so we need only find a way to align their goals with the reforms we envisions for PPS.

If we accept the premise that politicians and school board members care about their own tenure and individual interests, and do so above all other considerations, then what we need to produce are artifacts that provokes the parents and registered voters of that school district. Once an activated and inspired public knows what they desire, they will vote for and ultimately elect representatives who promise to bring that vision to life. We have seen this on matters ranging from civil rights and infrastructure, to economics and war. Politicians will follow public pressure to keep their own seats warm.

Arnold seemed pleased with my answer, and suggested that our topic relates directly to the fate of our nation’s democracy — so, no pressure at all!

This weekend our team held three meetings to jumpstart this process of future artifact synthesis, and we have been more or less fruitful in this endeavor. It’s exciting to be in the final stretch, but our team has been struggling to maintain momentum lately. The demands of presentation weeks, and the rush to complete our research, often requires long hours, multiple zoom meetings outside of class, and many late nights. This has began to produce negative health consequences for our team.

We’ve been intensely looking at teacher burnout, but have also been confronted with the burnout of a pandemic, and the rigorous academics of a graduate program. Illness, headaches, and signs of exhaustion have crept into our team dynamic, and I’m concerned about what this will mean now that we are heading into the final push for this semester. What we really need at this stage is that spark of creativity and divergent thinking. It’s hard to do this level of work while also pushing up against the steady hum of stress and exhaustion.

Brainstorming session, mapping events and trends to eventual implementation of key ARC concepts

Brainstorming session, mapping events and trends to eventual implementation of key ARC concepts

I think it was a gigantic error on the part of CMU to breakup our spring break. I understand the rationale, and the concerns around travel, but this alternative strategy of giving students a random Monday or Tuesday off has not provided the benefits of time off to rest. I simply cannot “sleep faster” when given a 24 hour window, and I cannot catch up when one day of classes is omitted from an otherwise packed calendar. I’m burned out. I’ve got this strange ringing in my ear that won’t let up, and I’m having more trouble concentrating than at any other time this year.

Languishing in the fog of constant deadlines, constant tasks, constant meetings, constant emails, Slack messages, updates, etc., etc., have left me depleted. It has also sucked the joy out of doing this work. I hope this terrible mental and physical state doesn’t last, because I don’t see how I can be productive while feeling this way.

Week 11: qualitative evaluation of concepts

Our online survey is now underway, and while this virtual format isn’t exactly like so-called “speed dating,” we are hoping that it will be able to serve a similar purpose for our research. Creating a meaningful online experience for our participants was a tall order, especially with such tight constrains. There are many risks when created a fully automated and hands-off system. Not being there to clarify or to address questions or concerns in realtime was something we needed to accept as a trade-off. In exchange, we have a dozen unique participants ranging from 2 years to 27 years of experience, and from various districts around the country.

So far, the majority of responses have been from an online community of English teachers, so our data is skewed toward this perspective. On the plus side, English teachers provide excellent written responses. To avoid the pitfalls of statistics and quantitative analysis, we designed an online survey with open text fields, and we framed our questions around hypothetical scenarios. This would provide us with reflection and insights into how teachers imagine these concepts for themselves, and what perceived deficiencies come up for them in thinking about these systems in action.

Screenshot of survey responses, exported into a CSV file

Screenshot of survey responses, exported into a CSV file

The last 24 hours in particular have been very exciting, as we finally gained access to online educator communities. This process has been slower than wanted, but we first needed to fully develop our survey before we could deploy it. This process in and of itself was a design challenge. 

Last weekend, we decided to use the Tripetto platform. This gave us the same logic capabilities as TypeForm, but without any additional costs. It became clear almost immediately that we would need to prototype and refine our survey before receiving teacher feedback, and this effort was highly collaborative.

With multiple teammates, it was possible to divide this task into several areas that could be worked on independently and in parallel. We first decided on a basic structure  and strategized the division of labor. Carol worked on the text/content based on a logic diagram we crafted together. While Carol crafted this outline, I created a mockup version in Tripetto. Without access to finalized concept sketches, I took some poetic license.

Screenshot of 2nd iteration prototype survey

Screenshot of 2nd iteration prototype survey

As Carol and I worked together to refine the text copy, Cat and Chris worked together to create images and descriptive text for our participants. Once all of this content was ready for Tripetto, we began doing test runs, trying to break the experiences. This revealed some quirks with Tripetto’s logic functions and some of the less apparent features.

There are a few honorable mentions; Tripetto has a lot of subtle features that we often take for granted in other online experiences. Things like placeholder text, required fields, multiple choice radio buttons, checkboxes, multi and single-line text boxes. During the refinement phase, these features became essential and it was exciting to discover them—only after they were deemed essential enough to be worth the effort.

The minimalist UI of Tripetto made these features less evident, but not too hard to locate or execute. From start to finish, this experience felt a little shaky and uncertain but viable.

TripettoPrototypeFinal.png

I often found myself this week grinding away on the platform, slipping into a state of mind that Mihaly Csikszentmihalyi describes as “flow.” In other words, creating a survey on Tripetto wasn’t easy to use, but just challenging enough to keep me interested in working through obstacles. I think that what helped support this effort the most was building models within platforms where everyone on the team is already fluent. For us, this was primarily Miro, Google Docs, and Sheets.

Screenshot of two representations of the survey, carried across platforms (Miro and Sheets)

Screenshot of two representations of the survey, carried across platforms (Miro and Sheets)

First impressions matter, and we didn’t want to put out anything that wasn’t necessarily a work in progress. Even with this in mind, we did have a few last minute tweaks as we adapted our survey to maximize pulling power with other social media environments.

Arnold Wasserman’s desk critique was incredibly valuable for our team, as his feedback helped us to consider the importance of our survey as a communication tool. He recommended that we make the implicit, explicit, to directly communicate to our participants what we expected and why. We were encouraged to explain what questions we were asking, and to share this openly. This kind of transparency can be tedious, especially in text-based systems. I took this to task and simplified statements throughout the entire experience.

This gave the survey a personality all its own; like a casual and curious friend, we asked about specifics but with little pressure. We kept things open.

Open data cannot be calculated, it must be evaluated for patterns. Next week will be a scramble to synthesize patterns and new insights as we work to finalize system concepts into well defined parameters. We hope that through this process we will also identify opportunities to produce relevant and compelling artifacts (our final output/deliverable).

It still feels like a risk to be so far into a process and to still not have a clear idea of what it is we are making. We instead draw our assurances from what we have already made: an index of relevant articles, interview notes, countless diagrams and visual representations of high-level abstract concepts and maps at almost every level of visual fidelity imaginable, hundreds of presentation slides, dozens of pages of reflective text, and months worth of slack messages, shared links, and drafted emails. We created interactive digital workshop spaces and protocols for our participants, and archives with 256-bit encryption.

When looking at the collective volume of effort from this team, it’s difficult to imagine that we wouldn’t make something meaningful in the end. Is that too optimistic? Ask me in a month.

Week 10 update: Speed dating and concept evaluation

We had a somewhat irregular week for studio II. After our presentation, our team regrouped and strategized on how we might conduct the next phase of our research. We started out with just two concepts (an ARC educator “hackathon” and a community-promoting “ARC awards” program), and while our team felt confident that these concepts were feasible and desirable to addressing our problem space, we still had a lot of open-ended questions that would require further inquiry. Additionally, we became very concerned with the potential opportunity costs of not exploring more alternatives.

To address this concern, we decided to return to our primary research and synthesize niche problem statements that my provoke additional concepts. This went extremely well, and we now have more than a dozen concepts ready for evaluation. We’re excited to get these ideas in front of educators, but this remains to be a substantial obstacle to our process.

We consulted with Hajira and Sofia about our concerns, and asked how we might convert the highly synchronous activity of “speed dating” to a more online and asynchronous form. They recommended Typefrom and while this option was appealing, it came with a few drawbacks. The ultimate dealbreaker on this platform was the price. It costs $40 to enable the features that actually make the platform more useful than free products such as Google Forms. After some digging, I found a free alternative (they literally marketed themselves as such). Tripetto offers logic and branches that will enable our team to structure paths for our survey to tailor the individual experience. This is pretty huge, considering the scarcity factors our team has struggled with since the beginning of this project.

TripettoTestSurv.png

Despite this progress and excitement for next steps, I’ve personally struggled with motivation this week. I know that a lack of regular sleep and some external stressors are partially to blame, but there are many factors contributing to this. It’s been difficult to process (cognitively and emotionally) what comes next for me.

This week, I received my cap and gown, a diploma frame, and a few other artifacts to commemorate my time at CMU. I’ve been in school since January of 2014, and I feel incredibly lucky and grateful for this opportunity. To date, academics has been my longest career. I have spent more time being a student than my entire Navy enlistment, or my time working at Intel as an engineer. Each chapter came with its own struggles, failures, and success.

Each made an indelible mark on my psyche and personality. I could never imagine in my wildest dreams that my educational path would end here, in Pittsburgh, confined to my shoebox apartment, a deadly virus burning down countless lives while I indulge in high-level theories. I owe so much for this good fortune, and I do not know how I will ever repay the world for what it has given me.

It’s not so much that I am procrastinating — I put in a lot of hours this week, especially for this project — it’s that I’m paralyzed, afraid that what we are doing is missing something vitally important yet still unnamed. I also know that 15 weeks is hardly enough time to understand potential futures and their relationships to the current state. 

It’s all crushing me down. I feel the weight of an obligation to deliver good work, yet terribly uncertain about this process. I’ve never done such intensive research before, and while I believe these theories and frameworks I’m soaking in (Worldview filters; Voroscone; Archplot structures; CLA;  Empathy mapping; Participatory, Generative, Co-design, etc.) are helpful and necessary to our work, it’s difficult to know if the way our team applies these unfamiliar methods will yield truly impactful results.

I know that this is a learning experience, first and foremost it is an invitation to fail brilliantly as we discover new ways of making, but without any prior experience with this stage, it’s so difficult to keep my chin up and to believe in my own creativity and ability.

Week 9 Update: Presenting Generative Research Findings

Fiona Hovenden (of Prospect Studio) was back in class with us this week. Monday through Wednesday blurred together as our team worked around the clock to bring our findings into coherence. Through this process, we found that it was easier than past presentations for us to produce clear and concise summaries of our work. This outcome stems from two key advantages:

  • Our team continues to get better at coordination and understanding of each other’s strengths and weaknesses. This has accelerated our communication and the delegation of tasks.

  • As we continue living and breathing in this problem space, we have gained deep familiarity with core concepts and structures. This has allowed us to develop a kind of fluency in addressing Portland Public Schools as a topic.


There is still a lot that we do not know, but this is something which we must (as a matter of need) become comfortable accepting as a default state. There are limits to what we can and cannot know over a fifteen week period, with limited access to our stakeholders.

Nevertheless, we are slowly inching toward viable concepts.

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These concepts are derived from last week’s workshops and diary studies. There was a lot of doubt and uncertainty going into our work last week, as we started with a zero participants. By Tuesday, all of this changed, and we found ourselves scrambling to coordinate with five different participants. Additionally, we coordinated with our counterparts (“Team Ahaa”) and I even took part in one of their workshops—after nearly 11 years of living in Portland, I had some qualified opinions to share.

This accelerated and compressed path from research to presentation ensured that we quickly moved from documentation to synthesis. Our team only had ten minutes to present all of this, and this constraint was helpful motivation to distill everything we learned over the last two weeks. So, what did we learn?

At a high level, generative research helped us to understand how educators see their relationship with various stakeholders. We gained more intimate, personal, and “day in the life of” perspectives from educators. We also got surprising feedback regarding their perception of possible futures. In general, there is not much hope for things improving substantially in the next ten years, but there is still a very real sense of urgency to make things better. This paradox has been with us since our first round of interviews but remains unresolved.

The most salient insights for our team were around issues of resilience and community: 

  • Educators feel supported when colleagues show up and help proactively

  • Informal but reliable networks among educators support their resilience

  • Lack of resources and top-down surprises make teachers feel unsupported

  • Quality of life and mental health resources are poorly leveraged

“Empathy” and “Community” are other target areas in the Educator Essentials ring.

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In our team’s presentation debrief, we had a lengthy discussion about this overlap, and our concerns about spreading ourselves too thin or not staying on target. This is an ongoing conversation and part of our general concerns for this project. We considered whether or not ARC is a “keystone” goal— resting on requisite conditions, and also essential to achieving other areas. This enmeshment is not entirely incompatible with the brief and Prospect Studio’s understanding of the problem space, but we must carry the burden of interpretation.

As we continue developing and evaluating concepts and potential interventions, we hope to achieve more focus on ARC, and to draw clear distinctions between outcomes and means to outcomes—e.g., is empathy an outcome of ARC, or is it a means to achieve ARC? This isn’t yet well defined, but I have faith in our team’s ability to resolve it.

Coming away from our Wednesday presentation, I can say that this task was both a relief and a source of pride. It was a huge relief to affirm key findings from Prospect Studio’s work, and also a moment of pride to have found these insights through workshops and protocols developed in house. This validated our research methods and demonstrated our core competency. Our protocols and assets were effective and entirely reproducible.

In terms of project management, we also took time to reflect on what was and was not working with our process and team contract. We do this every week as part of our “Rose, Bud, Thorn, and Shoutout” check-in exercise. We still felt more rushed than we’d preferred, and thought about ways to better support each other. We decided to designate “backup roles” to augment the facilitator and note-taker tasks. We hope that this will keep everyone equally engaged, while still offering flexibility and variety throughout the process. There are diminishing returns to these types of reforms, as we are already more than half way through the project. Nevertheless, every improvement counts.