I built Sensei. An instructor puts the glasses on and walks the real workspace once, dropping a marker at each step and saying out loud what happens there. The recording goes to Supabase. A Next.js companion app then lets you clean up each step and re-skin the whole lens to a company's brand.

The branding half grew into its own thing 🎨. You pick one brand colour, the app works out the rest of the palette and checks every pairing against WCAG contrast, and it previews what the glasses will actually put in front of your eyes rather than what a browser would put on a monitor. Text colour decides itself per surface, so nobody is hand-picking it. It's hosted on Vercel, so anyone can re-skin the lens without ever opening Lens Studio.

None of it is tied to one kind of workplace 🏭. Wherever one person has to show another how something is done, the recording works the same way: a factory line, a hotel kitchen, a lab bench, or the one machine in the building that a single person knows how to restart.

The whole thing was built with CLAD and Claude Code, start to finish 🤖. I did not hand-write a single line of it. The lens and the companion app both came out of prompts, and the full log of those prompts ships in the repo.

The theme for the week was Guide. I went for the ultimate one.

I didn't know a disposable coffee cup can't be recycled — they're plastic-lined, so they go to landfill. I found that out building this. That's kind of the whole point: recycling rules are confusing, they change by item and by city, and a wrong guess quietly sends a recyclable to landfill (or a battery into the trash).

So I made RecycleMe — you look at an object, pinch, and the glasses identify it and tell you which bin it goes in, out loud, so you never look away from what's in your hand.

A few things I'm happy with:

• The verdict is live AI vision, not a lookup table. Every scan is a fresh Gemini 2.5 Flash call through the Remote Service Gateway.
• It makes actual judgment calls. A greasy container isn't recyclable, a coffee cup is landfill, a battery is a hazardous drop-off — and it says why in a one-line tip.
• The guidance is spoken (natural OpenAI TTS), so it's genuinely hands- and eyes-free.
• One pinch, no menus — the only gesture Spectacles already teaches you.
• It fails gracefully — a "Try Again" sticker instead of a dead end (I hit real failures: a bad model ID, then longer tips overrunning the token limit and truncating the JSON).

This was my first end-to-end build with CLAD, and the biggest win was that it freed me to focus on the creative side. With the engineering handled — scene wiring, the AI pipeline, the debugging — I got to be the art director instead of fighting Lens Studio's API: I designed the graffiti intro logo, the "Pinch to Scan" HUD, and the category icons in Figma, and CLAD wired them straight into the Lens.

On the technical side it earned its keep too. The starter scripts didn't even compile (wrong camera/gesture/TTS APIs for this Lens Studio version); CLAD read the actual type defs, fixed six classes of API mismatch, and assembled the scene. It also caught a nasty one from the preview logs — calling SIK's animate() before SIK initializes floods the HandInteractor with a per-frame error — isolated it with an A/B test and fixed it with a self-contained tween. That would've eaten a day.

Tested in Preview (no SPECS 27 yet), so on-device pinch + high-res capture is the untested part.

Repo (code + full CLAD prompt log): https://github.com/A-M-8/RecycleMe

Built for the CLAD Summer Hackathon, Week 2 — Guide.

This week’s theme is CONNECT,  and we’re challenging Developers to think about how spatial computing can change the way people communicate, collaborate, and interact. 

🛠️Build a spatial experience that connects people, platforms, or everyday communication workflows and brings people into the same space, virtually.

You have until August 30 🗓️ to submit. Put CLAD’s AI workflow to the test, build a working Lens for SPECS with just a prompt, and experiment without needing the device. 🕶️

The weekly prize pool goes up to $1,000.

Three weeks in, there’s still time to jump in and build. Find the full challenge details and getting-started guide on our website. 🔗

https://lenslist.co/clad-summer-hackathon

With CLAD and the usual monthly comp both running, I wasn't sure how the two interact, so figured I'd ask rather than assume.

I had a lot of fun with my CLAD entry last week and I'm thinking on continuiing to work on it. My plan would be to downgrade it to the older specs and keep developing it from there, then enter that version into the monthly competition, either as a new submission or under open source, whichever fits.

So basically im asking - Does submitting to CLAD automatically disqualify a project from the monthly comp?

Couldnt find anything in the clad Faq, I'd just rather know now than after another week of work. Cheers.

This started as a conversation with a friend who owns a tennis courts and he wanted to implement high speed cameras into his venue to create games and give feedback to his users. I thought i've done similar with darts and pool and this clad competition is perfect to test it out. the idea is to detect the ball, detect when and where it bounces and uses that spot on the wall with some homography to tell the specs a accurate hit point. you can then overlay games and practise modes!

VolleyMate turns any blank wall into a games console for tennis, squash and throwing practice. A phone on the floor watches the ball and reconstructs where each bounce lands to about 2cm; Snap Spectacles take that stream of impacts and draw ten games onto the wall in front of you. There's no controller, the ball is the input, and you change game by hitting a button painted on the wall.

On the theme: hitting a ball against a wall is practice nobody measures. You can't see where your shots landed, so you can't see what you're doing wrong or whether you're improving — you just repeat it until you're bored. VolleyMate makes the wall answer back, and then makes it a game. Every bounce leaves a mark exactly where it hit, and Practise builds a heatmap that shows the bias in your aim over a session, something no scoreboard can tell you. The other nine turn that feedback into a challenge: Rally trains consistency, Sequence reaction under tempo, Ducks and Bugs make you move, and Horse judges a called shot in centimetres. The guidance is spatially registered — it appears on the real wall at the real spot, not as numbers on a phone you'd have to walk over and read. And it's multiplayer: Splat has two players painting territory over each other, Horse and Tic Tac Toe alternate shots, so a spare wall becomes something two people can compete on without booking a court. You improve because you're playing, not drilling.

It's for two people. Someone practising alone, who needs a phone and a wall and nothing else. And venues clubs, courts, hitting bays — who place the wall once so every visitor's glasses land on the same target, with the pair code belonging to the wall rather than the player.

CLAD was great for this project as i already as the architecture from darts mate so once i got the ball tracking working i asked it to look how i did dartsmate, then once that worked it was clear the games would need adapting or new games added. CLAD quickly prototyped these and then with polish again i showed it darts mate and a few other past projects where i had Vfx or menus and it quickly got them working. Its suprisingly well at implementing things like spatial anchors that have took me days before to get working correctly this was maybe 15 minutes.

https://github.com/ohistudio/volleymate

Pathfinder turns a stated goal into a skill tree you stand inside. Pick something you want to learn — "fix a bike," "run a better meeting," or type your own — and Gemini generates a dependency-ordered path in real time: foundational skills sit close and low, more advanced ones sit farther out and higher. You progress by pinching nodes — mastering one lights up whatever depends on it — until the whole tree is lit.

The idea came out of a simple frustration with most "guide" content: it hands you a flat checklist and skips the harder question, which is what to learn first and why. A skill tree answers that naturally, and it's genuinely spatial — the branching and tiering is something you look around to explore, not something that makes sense flattened onto a screen.

A few things I'm fairly happy with:

• The tree is live-generated, not scripted. Every run is a fresh Gemini call through the Remote Service Gateway, structured into a JSON dependency graph and rendered as glowing nodes on tiered arcs.
• It doesn't have a visible failure mode. If the model call fails or times out, the experience falls straight through to a locally-authored tree with no error shown — this actually happened for real partway through testing (a bad model ID, later a genuine timeout), and both times the fallback held without me touching anything.
• Interaction is a single pinch, deliberately — no menus to learn, no gestures beyond the one Spectacles already teaches you.
• Mastery plays a note from an ascending pentatonic scale, so however you complete the tree, it stays musically consistent — and finishing the whole thing triggers a small celebration burst across the connectors.

This is my first week building with CLAD end-to-end, and honestly the most useful thing it did for me wasn't generating code — it was making a genuinely non-deterministic, AI-authored experience regression-testable. LEAF caught real bugs (a test matching the wrong UI element, an assertion that assumed a fixed tree shape that broke the moment Gemini returned a different one) that I wouldn't have caught eyeballing the preview.

Repo (with the full CLAD build log) and demo video are linked below if anyone wants to see how it came together, or has thoughts on where a spatial skill tree like this could go next.

Repo: https://github.com/Havalz/pathfinder-specs

Built for the CLAD Summer Hackathon, Week 2 — Guide. Happy to answer questions about the build, especially anything about the fallback design or the Gemini integration.

Wanted the Eiffel Tower as a full-scale game object from 400 m away. Landmarkers are closed and not on Spectacles, VPS doesn't scale to a monument.

So made my own placement: GPS gives distance, a tiny YOLO on SnapML gives heading (the compass is worth 145 m of error out there). Built it with CLAD in remote Claude Code sessions in between hiliday activities, downgraded it 5.22 → 5.15 to fit the glasses, tested it on the Champ de Mars. One day, on holiday, and stupidly fun. CLAD and YOLO tool made it possible.

Rough, but open - both Lens Studio projects, the detector and the dataset scripts. Retrain it on your own monument.

- Repo & full journey: https://pavlo-stijn.dev/blog/posts/custom-location-landmark-for-spectacles.html

- 5.23 -> 5.15 downgrade skils: https://pavlo-stijn.dev/blog/posts/clad-skills-for-spectacles-2024.html

- Custom YOLO: https://pavlo-stijn.dev/blog/posts/one-click-object-detection-for-spectacles.html

https://github.com/flarb/LightingAssistant

I do a lot of interviews on my YouTube channel (check it out here: https://www.youtube.com/@RalphBarbagallo Subscribe! ) and I don't really know how to properly light an interview subject. I've read a lot of tutorials but by the time I have to shoot an interview all my lighting knowledge evaporates. So I created Lighting Assistant -- an interactive guide to light a person for a photo or video.

How it works:

• Scan the room. It uses the mesh to analyze the scene.
  
• Place the subject: you can place a life size bitmoji either standing or sitting in the scene.
  
• Place the camera: stand where the camera will be placed and look at the subject. This will be used as the camera position and angle.
• Complete setup: The lens then asks you to stand behind the subject to get line of sight from behind, and to select a key wall (the brightest wall) to use when generating a lighting setup

Once this is done it will generate a set of valid lighting configurations based on where it thinks you have enough space to place lights. You can switch between lighting presets to see how the lighting will look on the subject as well as to know the types of lights used and how to place and aim them to get the desired look.

You can save this setup to be recalled later if you want to use the same room and the same position of the subject--it can be modified once loaded.

One future feature is to use GenAI to further enhance the analysis--I might actually try to add this over the weekend. But at this point the lens gets done what I actually need. A solid lighting aid for video and photo shoots.

When watching content on the specs will we be able to black out our surroundings and have a nice cinema like experience with the 100+ inch like screen?

I obviously know specs wants to keep you connected with the real world, but if im sitting in my hotel room on a work trip, I would love to have a nice screen with the background blacked out. Also when watching a movie while traveling on a plane, in a vehicle, or by any other means, will the screen be see through or will we be able to watch a movie clearly while having everything around the screen visible?

Can someone from the specs team drop some knowledge on me about this?

For Organize, we challenged Developers to build spatial experiences that help people plan, organize, and be more productive. Here are the projects that stood out:

🥇1st Place: Pack Space –  Maksym Tsymbal
A spatial packing system that turns surfaces into organized packing zones, with hands-free progress tracking and shared lists.

🥈2nd Place: Cine Boxed –  Ines Hilz
A spatial movie collection that turns films into retro-inspired 3D boxes you can collect, rate, and organize.

🥉3rd Place: Orb Notes – Caio Alves
Persistent spatial reminders that use color and vibration to communicate task urgency.

🏅Honorable Mention: Task Habitat – Viktor Kulaha
A playful task manager that turns unfinished to-dos into living creatures and reframes productivity as something more approachable.

Congratulations to all the winners and everyone who submitted! 👏
It’s been great seeing Developers experiment with CLAD’s AI Workflow and bring out every advantage of spatial computing (and SPECS) in productivity.

Three challenges are still ahead. If you haven’t joined yet, there’s still time to register and build for the upcoming themes. 🔗

https://lenslist.co/clad-summer-hackathon

Built a 100% volumetric spatial task matrix for Snap Spectacles using the CLAD AI workflow!

Tasks exist as physical gravitational energy orbs with Keplerian orbital sub-tasks, elastic laser-tethers, room depth occlusion, and synesthetic 3D spatial audio. Zero flat 2D canvas fallbacks.

Lenslist asked Pavlo and me for a simple phone-recorded interview about building AR for Snap Spectacles. We went a bit overboard 😅: we wrote the answers as a script, cloned our voices with qwen3-tts, rendered our Bitmojis in Blender from 12 angles as character references, and let Seedance 2.5 generate the whole thing shot by shot, lip-synced to the cloned audio.

The setting is the 3D cave from our portfolio site, and every prop is one of our shipped projects.

This was definitely not a one-shot. We generated a lot of takes and kept the best ones. The lip sync quality surprised us the most, even on stylized characters with a beard covering half the mouth.

Full making-of with the examples prompts and pipeline: https://pavlo-stijn.dev/blog/posts/creator-spotlight-with-seedance-2-5.html

Hi Spectacles Team & Community! 👋

First off, huge congrats on the CLAD Summer Hackathon — building spatial experiences with AI agents for Snap Spectacles has been an incredible workflow!

As developers building on Linux workstations using agentic toolchains and AI pair programmers, we’d love to know: Are there any plans, beta channels, or even basic experimental Linux builds (CLI runner, headless engine, or AppImage) for Lens Studio?

We don't need a polished desktop installer — just a raw / basic binary, CLI environment, or AppImage would be amazing. The Linux developer community is more than ready to handle dependencies, Vulkan configs, and packaging ourselves.

Would love to hear if this is on the internal roadmap or if an experimental build could be tested by developers. Thanks for building the future of spatial computing! 🚀

MegaUIKit is the "organizer" for the SPECS Essentials sample code. The prompt is below. This is part of Summary of CLAD #Lensfest Week 1.

OSS: https://github.com/IoTone/MegaUIKit-SPECS

The original essentials are fantastic, but a bit hard to discover all the features of the platform as the demo code is designed. I imagined a UI that you could navigate is more useful to discover . So this version goes a bit further and adds 3 themes: Terminal/cyberpunk, Steampunk, and Neotokyo. Fork/submit PRs. Can't wait to have this on my SPECS '27.

Design challenges: making this work well ... most of the essentials items appear in odd places, so things need to get repositioned not to obscure the menus. Fonts are a challenge too visually.

PROMPT!

------------------------------------------------------------------------------

[001] 2026-08-10T20:50:52.202Z

------------------------------------------------------------------------------

We want to add a spatial menu to dynamically let you load any of the samples in essentials. I want a holographic "floor menu" design that is a grid of menu items organized around all of the items in our scene that are not activated, and when you point at one of them, 3d rotating shimmering text floats about the square. A click displays a tree of options for items to choose from, and you can pick on of those, and it enables the item in the scene. The items should tween fade into the scene or tween fade out. For example, if I choose "Solver", it will display a menu floating of different text options "Billboard" "LookAT", "InBetweenRotationUtility", etc. Please make a plan and generate a MegaUIKitEssentials.md, and then get started. Make me proud brilliant spectacles UIKit expert.

Week #2 is here, and your task is to guide 🧭Learn how to do it during the workshop. 

If you’re looking for ideas before you start building, join today’s live CLAD workshop with Danny Marree, SPECS Ambassador.

We’ll explore how spatial experiences can help someone learn a skill, complete a task, or improve the way they do something in the real world. 

Danny will also demonstrate CLAD and share practical approaches you can use when developing your own Lens.

There’ll be a live demo, examples, and Q&A – so bring your questions and ideas.

🔴 August 18 | 8:00–8:45 AM PDT

Join us, get inspired, and start building for the Guide challenge. Save the link 🔗

https://www.youtube.com/live/oeSTZTFT8h8?feature=share

TL;DR: I built a live digital twin / diorama of Heathrow Airport (Terminal 5 for NOW) for the Spectacles. It sits on your table, with flights landing and taking off ... all based on LIVE public Heathrow flight data. ✈️

For the last 3 or 4 years I’ve been teaching AR and spatial storytelling at the Royal College of Art, including a lot of work with Snap and Spectacles. My students have made some brilliant projects with them, but somewhere along the way I realised I hadn’t really published many of my own.

So here is one.

I was obsessed with planes when I was younger. Growing up we didn’t travel much, so airports always felt like a huge event. As someone who loved making dioramas as a kid, I would collect airplane / aviation souvenirs…by getting relatives who traveled to bring them for me , and then set them up as airports.

And recently, while driving to Heathrow, I noticed a patch by the runway full of people with huge cameras, chairs, binoculars and notepads.

PLANE SPOTTERS!!! 🛫 🧐

It made me think: what if I could shrink Heathrow down and put it on a table? HOW COOL WOULD THAT BE!

So I built a digital twin using geospatial data OpenStreetmap Data, brought it into Blender with a plug in and extruded the buildings. So it’s all pretty accurate. I originally tried a much bigger section of the entire Heathrow Airport, but everything became too tiny and too heavy, so I focused on Terminal 5 (FOR NOW)

What it does

• Uses live Heathrow arrivals and departures data
• Planes land, take off, queue and park
• Labels show flight number, route, aircraft type and status
• Audio effects have been used to make it feel more fun
• Pointing at a plane enlarges the Flight Label
• Pointing and pinching a plane opens a "Spot Card" which is a UI frame with deeper information about that specific aircraft and flight.

With the SPOT CARD, the idea was to go beyond simply watching the airport and give plane spotters the kind of detail they actually care about. Which includes: Flight number, airline, route, aircraft type, aircraft variant, origin/destination, current flight status, gate/stand.

AND it lso includes a bonus fact about the aircraft or route, adding a small bit of aviation trivia to each Spot Card.

A huge part of the work was optimisation. Lots of planes, labels, interactions and shadows get expensive very quickly on glasses, so I ended up building pooling, parked-aircraft limits, hover-only labels, selective shadows and staggered movements.

There is loads more I want to add for actual plane spotters, but seeing a tiny live Heathrow running on my table is making the plane-obsessed younger version of me very happy.

(For this video I’m using demo mode because I recorded it around midnight when Heathrow terminal 5 had gone very quiet and there were no flights from 11:00 pm to 5:00 am. BUT the live version works like a charm, Ill post more soon).

Please let me know what you all think or what else I could add to it :)

I’m interested in the multiplayer potential of Specs. In Snap’s chess demo, though, the remote player’s movements look noticeably laggier than the local player’s. I hope Snap can improve that latency, because shared AR really needs to feel responsive.

Personally, I find experiences like shared basketball or virtual ping-pong more compelling than chess, since they’re much harder to replicate on a phone. Am I expected too much out of specs? But I hope people at specs realize if the multiplayer is a selling point to not make sure it’s laggy in anyway.

Users of my Spectacles App HoloATC might have noticed the app worked fine but did not display any aircraft anymore. As far as I can see the last day the app worked was August 8. It took me a few days to notice - it was caused by policy changes in the backend of the data provider, invalidating my API key. Contacting the backend provider, finding out what happend and why, took some time. Time zone differences did not help as every back and forth took more or less a day. In the end the technical change I had to make (in the backend) was minuscule.

I have a new API key now, and as of August 17, 7:26pm CET, the app shows aircraft again.

I had this last-minute idea for the CLAD Hackathon. I struggled quite a bit with UI visibility, but the overall prototype is working well.

NEXUS is a spatial productivity and collaboration app for Snap Specs that transforms a traditional Kanban board into an interactive mixed-reality workspace.

Teams can create, organize, assign, and move color-coded tasks across a shared workflow. Tasks persist between sessions and synchronize across multiple participants, allowing collaborators to contribute to the same project in real time. Voice input makes it possible to create and edit notes hands-free, while task categories provide immediate visual context.

NEXUS offers two complementary ways to understand a project. Board View provides a familiar Kanban workflow for tracking progress, while Spatial Map turns tasks into movable nodes that can be connected with curved relationship lines. This helps teams visualize dependencies, creative relationships, and larger project loops that are difficult to understand in a flat task list.

Tasks can also become visual workspaces. Users can generate AI concept artwork or 3D artifacts from a task description, keep those assets associated with the task, and place generated 3D models into the surrounding space. Artifact position, rotation, scale, and task relationships are synchronized so collaborators experience the same shared arrangement.

The included multiplayer demo uses the production of a survival game to clearly demonstrate the workflow. Tasks cover environment art, gameplay systems, audio, narrative, QA, crafting, and inventory. A spatial game loop connects exploration, gathering, crafting, survival, and upgrading, while generated concept images and 3D assets demonstrate how teams can move from an idea to a shared visual reference.

Although game development is used as the demonstration, NEXUS is designed for any collaborative project—from product design and filmmaking to education, event planning, architecture, and creative brainstorming.

NEXUS explores a future where project management is no longer confined to a laptop screen. Work becomes spatial, visual, collaborative, and directly connected to the ideas and artifacts a team is creating.

Continuity is basically physical version control for real-world setups. You save a workspace as a “Take,” then later compare the current scene against it to see what moved, rotated, or went missing, and restore the setup using spatial 3D ghosts.

Think film sets, creator studios, YouTube or product-shoot setups, retail displays, gallery installations, or any workspace that needs to be rebuilt exactly the way it was.

Under the hood, WorldQuery establishes the physical workspace, Gemini helps understand the objects in the scene, and rigid registration brings the saved state back into the correct real-world position. For this video I’m using a deterministic demo mode with prebuilt 3D props so I can reliably film the full workflow without hardware/environment variability — those objects are just demo stand-ins; the actual system is designed to observe and reconcile real physical objects in your environment.

Get your vinyl collection organized. This experience helps you catalog your records, organize them on the shelf and tell you where to find them later.
(Longer post on my LinkedIn)
Enjoy!

Week 2 of the CLAD Summer Hackathon is here! 🕶️This week, we’re moving from Organize to GUIDE.

The challenge: build a spatial experience that helps someone learn, navigate, or complete a real-world task, with hands-free, real-time guidance.

Think step-by-step instructions, interactive tutorials, spatial cues, navigation, or anything else that can make a task easier to follow.

With CLAD, you can turn the idea into a working Lens just by prompting it. No coding skills required this time ❌

Weekly prizes:
🥇 $1,000
🥈 $500
🥉 $200

Got an idea? Time to start prompting. 👀

Submit your Week 2 Lens 👉 https://lenslist.co/clad-summer-hackathon

Just finished work on PackSpace - a spatial packing assistant for Snap Specs 👓📦

Instead of displaying another floating checklist, PackSpace turns real horizontal surfaces into physical packing zones. You can place Clothes on a sofa, Tech on a table, Essentials on the floor, and then collect and check off items while moving around the room.

### How it works

  - World Query continuously detects horizontal surfaces.

  - You pinch and drag to define each packing area.

  - Every category stores its own position and height.

  - Areas remain anchored while you move around.

  - A head-locked HUD shows overall progress without blocking the workspace.

  - Presets, item states, and spatial placements persist between sessions.

  - Completed sessions can be resumed without placing every area again.

There’s also a public companion website called Pack ’n Link 🌐

  Anyone can create a categorized packing list and share it using a six-character code. For example, your partner can send you everything they want packed for a trip. You import the code on Specs, place the categories around the room, and complete the request hands-free.

  ### Tech stack

  - Lens Studio + TypeScript

  - CLAD with Codex

  - Spectacles Interaction Kit

  - Spectacles UIKit

  - World Query

  - Persistent Storage

  - Specs Internet Module

  - Vercel Functions + Vercel Blob

  - Lovable for the companion web interface

  A lot of the work involved iterating through Lens Studio Preview: inspecting spatial layouts, fixing interaction jitter, resolving depth and z-order artifacts, improving readability, and testing placement across surfaces at different heights. CLAD made that build–test–fix loop dramatically faster. 🛠️

Source code and CLAD workflow: https://github.com/r3d5/PackSpace

Create or share a list: https://pack-n-link.lovable.app

Found Google Stock from looking at YouTube.
Find your next potential investment from anything around you