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9865
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learning ig by @Otoko | Stardance
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Otoko
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0
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0.0
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0
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[]
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[]
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Title: learning ig by @Otoko | Stardance
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1793393299.916183
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1793998099.916183
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45505
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learning assistant by @sakshyamniraula | Stardance
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sakshyamniraula
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0
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0.0
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0
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[]
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[]
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Title: learning assistant by @sakshyamniraula | St Title: learning assistant by @sakshyamniraula | Stardance...
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1793335956.784468
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1793940756.784468
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4182
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learning JS by @dimple | Stardance
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dimple
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0
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0.0
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0
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[]
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[]
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Title: learning JS by @dimple | Stardance
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1793487409.1694736
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1794092209.1694736
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45633
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learnbot-ros2 by @antek042 | Stardance
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antek042
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0
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0.43
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0
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[]
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[{"post_id": 43464, "ts": "202 [{"post_id": 43464, "ts": "2026-08-08T18:57:56Z", "hours": 0.4292, "text": "Power management PCB is now finalized. It takes the 12V battery input and provides regulated 5V and 3.3V rails for the robot. I’ll add the full BOM in the next commit."}]...
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Title: learnbot-ros2 by @antek042 | Stardance
Dev Title: learnbot-ros2 by @antek042 | Stardance
Devlogs:
Power management PCB is now finalized. It takes the 12V battery input and provides regulated 5V and 3.3V rails for the robot. I’ll add the full BOM in the next commit....
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1793339935.3329616
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1793944735.3329616
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10019
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learn react by @ttiramisu | Stardance
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ttiramisu
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0
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0.92
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0
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[]
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[{"post_id": 3920, "ts": "2026 [{"post_id": 3920, "ts": "2026-06-07T01:09:27Z", "hours": 0.9158, "text": "working on learning react while making some bad ui designs for fun. no css yet though cuz i didnt have the time for it…."}]...
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Title: learn react by @ttiramisu | Stardance
Devl Title: learn react by @ttiramisu | Stardance
Devlogs:
working on learning react while making some bad ui designs for fun. no css yet though cuz i didnt have the time for it…....
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1793444016.322345
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1794048816.322345
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59415
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learing html by @sharma_manjuroyal | Stardance
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sharma_manjuroyal
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0
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0.82
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0
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[]
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[{"post_id": 63992, "ts": "202 [{"post_id": 63992, "ts": "2026-09-08T02:49:33Z", "hours": 0.405, "text": "uploaded new repo"}, {"post_id": 63616, "ts": "2026-09-07T15:20:11Z", "hours": 0.4106, "text": "here my peoject dealited i will teaching a html term and css per day"}]...
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Title: learing html by @sharma_manjuroyal | Starda Title: learing html by @sharma_manjuroyal | Stardance
Devlogs:
here my peoject dealited i will teaching a html term and css per day
uploaded new repo...
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1793559071.0689352
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1794163871.0689352
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29677
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leapfrog 3d by @jwexly | Stardance
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jwexly
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0
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13.8
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0
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[]
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[{"post_id": 53464, "ts": "202 [{"post_id": 53464, "ts": "2026-08-24T01:12:38Z", "hours": 4.6022, "text": "start screen pt 2 ANOTHER 4 hours of coding the start screen later genuinely whys it taking so long anyway i want a first ship by the end of august so im going to start working on the actual game mechanics now that im done w the start screen goals for next devlog: layout the main level start a randomization process (for both maze branching and obstacle placement) see the video for what ive done so far!! also i feel like the fading is a TINY bit off but idk how… i think ill leave it for now until i find out whats wrong"}, {"post_id": 50764, "ts": "2026-08-20T03:54:50Z", "hours": 4.0019, "text": "start screen im not even done w the start screen omg 😭😭😭😭 literally ALL 4 hours ive spent ive been debugging the start screen. and more time than that to design it too anyway i wanted to post bc its so close to a nice round 4 hours and i thought that was cool heres what the start screen looks like so far! the start button starts the game but i still need to add animation for it, and the credits button doesnt do anything"}, {"post_id": 40773, "ts": "2026-08-04T14:57:41Z", "hours": 2.3039, "text": "game updatesss general so i finally decided what type of game i want this to be! its going to be some sort of maze x infinite runner game (think flappy bird/dinosaur game-esque but maze and 3d). im not quite sure how to get the maze mechanism down, but i like this idea and i think it could totally be a cool game :) code camera : i originally wanted it to be sort of like roblox with a platformer type thing, so i had a whole roblox camera movement thing going, but i decided to overhaul that and replace it with a side camera so you can see what the frog is doing and where it is going! movement : like i said it was originally like roblox movement, so pressing left/right arrows would rotate some amount, but now it just rotates 90 degrees left/right. im planning to use this to let the player choose which direction they want to go jumping : the player can now jump infinitely! animation : used another character design thing that displayes when you jump #TODO fix the jump design it looks sooo wonky the camera also feels kind of weird but idk what to do about that?? i might position it slightly behind the character instead of a straigh 90 degree angle level design obviouslyyy! eventually i want it to auto gen levels work out how exactly the game works and what i want it to look like im still learning godot and it is a slow and arduous process 😭 uhhh yeah thats it watch the video i guess???"}, {"post_id": 30451, "ts": "2026-07-18T00:24:16Z", "hours": 2.89, "text": "getting started! all ive rly done so far is a TON of character design which is unfortunately not included in the programming hours (i think it should be.. its lwk a lot harder than actual programming) if anyone has good free 3d modeling / texturing platforms please share, i’ve been using vectary since its easily accessible in browser and i find it kinda hard to use on the coding side, ive learned a tiny bit of godot so now the frog moves and jumps! next on my to-do for this game is designing the first level and unfortunately creating more textures :( im going for some sort of platformer game, but i think its a bit basic to just jump around so ill be brainstorming unique twists too. i also lwk hate the name “leapfrog” it sounds so silly but i unfortunately cannot come up with anything better anyway, heres where it’s at right now (beautiful i know):"}]...
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Title: leapfrog 3d by @jwexly | Stardance
Devlogs Title: leapfrog 3d by @jwexly | Stardance
Devlogs:
getting started! all ive rly done so far is a TON of character design which is unfortunately not included in the programming hours (i think it should be.. its lwk a lot harder than actual programming) if anyone has good free 3d modeling / texturing platforms please share, i’ve been using vectary since its easily accessible in browser and i find it kinda hard to use on the coding side, ive learned a tiny bit of godot so now the frog moves and jumps! next on my to-do for this game is designing the first level and unfortunately creating more textures :( im going for some sort of platformer game, but i think its a bit basic to just jump around so ill be brainstorming unique twists too. i also lwk hate the name “leapfrog” it sounds so silly but i unfortunately cannot come up with anything better anyway, heres where it’s at right now (beautiful i know):
game updatesss general so i finally decided what type of game i want this to be! its going to be some sort of maze x infinite runner game (think flappy bird/dinosaur game-esque but maze and 3d). im not quite sure how to get the maze mechanism down, but i like this idea and i think it could totally be a cool game :) code camera : i originally wanted it to be sort of like roblox with a platformer type thing, so i had a whole roblox camera movement thing going, but i decided to overhaul that and replace it with a side camera so you can see what the frog is doing and where it is going! movement : like i said it was originally like roblox movement, so pressing left/right arrows would rotate some amount, but now it just rotates 90 degrees left/right. im planning to use this to let the player choose which direction they want to go jumping : the player can now jump infinitely! animation : used another character design thing that displayes when you jump #TODO fix the jump design it looks sooo wonky the camera also feels kind of weird but idk what to do about that?? i might position it slightly behind the character instead of a straigh 90 degree angle level design obviouslyyy! eventually i want it to auto gen levels work out how exactly the game works and what i want it to look like im still learning godot and it is a slow and arduous process 😭 uhhh yeah thats it watch the video i guess???
start screen im not even done w the start screen omg 😭😭😭😭 literally ALL 4 hours ive spent ive been debugging the start screen. and more time than that to design it too anyway i wanted to post bc its so close to a nice round 4 hours and i thought that was cool heres what the start screen looks like so far! the start button starts the game but i still need to add animation for it, and the credits button doesnt do anything
start screen pt 2 ANOTHER 4 hours of coding the start screen later genuinely whys it taking so long anyway i want a first ship by the end of august so im going to start working on the actual game mechanics now that im done w the start screen goals for next devlog: layout the main level start a randomization process (for both maze branching and obstacle placement) see the video for what ive done so far!! also i feel like the fading is a TINY bit off but idk how… i think ill leave it for now until i find out whats wrong...
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1793267752.8814952
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1793872552.8814952
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50331
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leaenin Onsape 3d cad by @jonathanajokpaniovo | St leaenin Onsape 3d cad by @jonathanajokpaniovo | Stardance...
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jonathanajokpaniovo
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0
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0.5
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0
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[]
|
[{"post_id": 48893, "ts": "202 [{"post_id": 48893, "ts": "2026-08-17T13:39:59Z", "hours": 0.5003, "text": "tryin to learn onsape to eventially uild ben 10 watc"}]...
|
Title: leaenin Onsape 3d cad by @jonathanajokpanio Title: leaenin Onsape 3d cad by @jonathanajokpaniovo | Stardance
Devlogs:
tryin to learn onsape to eventially uild ben 10 watc...
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1793335848.0156024
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1793940648.0156024
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69319
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lead scaper by @KrishnaDeoli | Stardance
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KrishnaDeoli
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0
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0.0
|
0
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[]
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[]
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Title: lead scaper by @KrishnaDeoli | Stardance
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1793130892.8531792
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1793735692.8531792
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29287
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le-fat-chaton by @unknown_lizzard | Stardance
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unknown_lizzard
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1
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172.0
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1818
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-08-20T09:10:04Z", "hours": 172.0, "multiplier": 14.88, "payout": 1818, "blessing": "neutral", "text": "at first I wanted to make a normal text model to try and learn more about llms, but I wanted to go further, agentic coding is a big thing so what better way to learn about llms than trying to make an agentic coding ai model. So thats how le gros chaton was born, the name originated from a joke on x about a fake huge mistral model coming out. to train this model I used already made datasets on hugging face, like fable5 traces, I also used kimi k3 as a teacher model to teach my smaller model to be good at coding and running commands, it kind of worked? but i’m not completely satisfied with the result, but at least i have learned some things and soon enough I will trying making an even better model! I dont have a demo url for you guys to try the model out since it was too expensive to run on a gpu so you’ll need to run it yourself, check it out on hugging face, follow the instructions and have fun.", "repo": "https://github.com/Mateooo93/le-gros-chaton", "demo": "https://mateooo93.github.io/le-gros-chaton/"}]...
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[{"post_id": 50841, "ts": "202 [{"post_id": 50841, "ts": "2026-08-20T08:57:48Z", "hours": 3.2394, "text": "devlog #17 MI300X vLLM serving The old GPU box got destroyed, so I spun up a new MI300X with the same SSH key. ROCm 6.2 and Torch 2.5.1 were already set up, so getting the machine ready was easy. The hard part was vLLM. The pip version is CUDA only, and the ROCm Docker image only supported the multimodal version of Qwen3.5. Our model is text-only, so I had to patch the image. I added Qwen3_5ForCausalLM, fixed the hybrid KV-cache setup, added the missing Mamba state methods, and mapped the weight names so the text-only safetensors loaded correctly. I also patched the merged config to remove the M-RoPE and dtype fields. After that, the model served normally. I ran a one-task test with fix-git. The pipeline worked, but the model got stuck repeating git show until it ran out of turns. ##Shipped The merged model is now public on Hugging Face as mateo0093/le-gros-chaton under Apache-2.0. The 5×5 Terminal-Bench pilot finished at 3/25 (25%). All three successes were on fix-git, which shows that the SFT data was too focused on git tasks. I also tested RLVR with GRPO and a novelty bonus. The reward had almost no variance, so the training signal was basically useless. I saved the step-10 adapter but didn’t merge it. The GPU used about 12 hours of the 50 hour budget. All the vLLM patches and harness changes are in the repo. Main lesson: Qwen3.5’s hybrid model is a bit annoying to serve as text-only on ROCm. The model works but i think this was more of a learning opportunity, i know what i’ve done wrong and what i would have done differently, I will be working on a new model in a few weeks once I do a bit more research."}, {"post_id": 49761, "ts": "2026-08-18T18:01:12Z", "hours": 0.7992, "text": "Devlog #16, t4gpu The T4 16GB fought us the whole way. BF16 was baked into a pre quantized checkpoint, which made each step take 668 seconds because it had to use FP32 emulation. 2K context ran out of memory, the 248K logits ran out of memory too, FP16 started producing NaNs, Kaggle session limits locked us out, and the paged optimizer crashed last. Every fix seemed to create another problem. We eventually got it working with FP16 compute, chunked assistant token loss, autocast, and plain AdamW. Then we got access to an AMD MI300X with 192GB of memory. No quantization, 16K context, and enough memory to train full traces instead of cutting them off halfway through a message. Right now the 16K BF16 SFT run is training on the MI300X. Next up is merging the model, running Terminal Bench, and then RLVR."}, {"post_id": 49140, "ts": "2026-08-17T19:31:53Z", "hours": 16.24, "text": "Devlog 15 Traces are done The trace generator finally hit the target and went past it. We got 474 verified trajectories, zero malformed, zero duplicates, 19 templates, and a 95 percent self review pass rate. We were aiming for 450, so we ended up with 474. The dataset is synced to Hugging Face in two versions: raw and normalized. That part is finally done. It was the longest part of the project, and the model is only going to be as good as the traces, so getting this right was important The Kimi endpoint also stopped working. The old teacher account started returning 503 errors during generation and eventually died completely. We switched to a second Kimi account, which needed an extra header that we did not have at first. After figuring that out, generation resumed without losing any progress For GPUs, the 2070 still cannot realistically train the 9B. Kaggle hours are back, so we have 30 hours on a T4. The 4090 from my dad should arrive next week. The plan is to use the T4 for trajectory SFT, then the 4090 for merging, Terminal Bench evaluation, and RLVR. Status: 474 out of 474 traces done,"}, {"post_id": 42823, "ts": "2026-08-07T19:01:50Z", "hours": 8.9192, "text": "Devlog #14 worked a lot, still not done we worked a lot this week. honestly the main takeaway is that the fable5 sft was good but its traces alone weren’t enough the model needs way more verified agent trajectories, so we’ve been grinding those out (target is 450). we also ran out of credits mid-generation (the modal endpoint started failing with 503s) and had to switch to a second kimi account. took a minute to get the auth right the new endpoint wanted an extra header we didn’t have. after that the generator resumed fine and it’s been adding verified traces since (~340/450 now). biggest scare: we found out peft 0.20 silently drops the second adapter when you merge two at once. tested it and yeah, the outputs were identical with one or two adapters so our trajectory sft would have been lost in the merge. fixed it by merging sequentially (base first, then the second adapter). checked against the live model and it matches, so we’re good. my 2070 couldn’t fit the 9b model for real training, so we’re waiting on a 4090 (my dad’s) next week. all the scripts are ready sft, merge, rlvr, eval, even a setup script for the gpu box. just need the hardware. status: 340/450 traces, everything ready, waiting on the 4090. we’ve worked a lot, but the real run hasn’t happened yet :/."}, {"post_id": 41470, "ts": "2026-08-05T18:10:35Z", "hours": 18.5394, "text": "Devlog #13 we worked ALOT so this was the grind day. 18 hours of training babysitting and honestly it felt like 40. the modal training kept dying every hour. the client would crash and take the whole run with it. we restarted like 3 times before figuring out modal run -d (detached) keeps it alive on their servers even if our computer shits the bed. tested it by literally killing the process and it kept going. ez fix but we worked ALOT to get there. then we ran out of credits at 93% and switched accounts, but the other account “finished” the run in 6 MILLISECONDS which was sus af. turns out it just re-uploaded the old checkpoint and trained nothing. the resume logic had a bug where it thought 6200 >= 3799 meant done. patched it. another lesson learned. also we made the model creative lol. added diversity sampling to the trajectory generator (5 solutions per task, keep the novel ones), a novelty bonus reward for RLVR, and a creativity rule in the self-awareness prompt. so the fat cat will be innovative, not just memorize. current state: SFT is done at 91% (good enough), resume bug fixed, phase 2 (trajectory SFT with creativity + self-awareness baked in) is up next. 18 hours. we worked ALOT. the fat cat will be worth it 😼"}, {"post_id": 40883, "ts": "2026-08-04T18:02:57Z", "hours": 10.0019, "text": "Devlog #12 training kept dying for the last 10 hours the training kept crashing. not the model, not the gp but the modal client. every hour or so it would lose connection and take the whole run down with it. we’d restart, it’d run an hour, crash again. three times. the fix was simple: modal run -d runs detached, so the training lives on modal’s servers and doesn’t care if our local process dies. killed the client on purpose to test — training kept going. that’s it, that’s the fix. also worried the loss wasn’t moving but it was fine. lr had wound down on the crashed run, looked scary, re-warmed fine after restart. loss is 0.668 now and dropping. status: 72% through the fable5 sft. checkpoints safe on hf. after this: trajectory sft with the self-awareness stuff baked in, then rlvr, then real numbers."}, {"post_id": 40601, "ts": "2026-08-04T08:01:50Z", "hours": 11.4342, "text": "** Devlog #11 half way there! ** the training is going pretty well, I fixed a few bugs with the code and added documentation training is at 50%!"}, {"post_id": 40369, "ts": "2026-08-03T20:35:48Z", "hours": 8.8192, "text": "** Devlog #10 the full training is finally running ** ok so phase 1 full training is officially going. 160k rows of fable5 data on modal, resuming from the 12.8k rows we got on kaggle before the session cap killed us. we’re at ~27% and it should take like a day and a half total. big stuff that happened since last time: fast kernels actually work now. the model has hybrid linear-attention layers and transformers kept falling back to a slow torch path. the fix was: nvidia cuda-devel base image (needs nvcc to compile), installing flash-linear-attention[cuda] + causal-conv1d , and pinning torch 2.10. took a couple tries but now training is like 4x faster than it would be without them. had to split across two modal accounts. first account ran out of credits, so we set up a second profile and the script auto-resumes from the huggingface checkpoints when it dies. it’s been rock solid, it happens every 20% plus every hour it saves and uploads. lost zero progress to the account switch. we gave the model a personality. it’s called Le Gros Chaton (the fat cat) and we’re training self-awareness into it, not as a system prompt but baked into the weights. state-sheets ([STATE] goal/known/tried/failed/next), metacognition lines, and self-review at the end of tasks. the trajectory sft masks out the system prompt so the model learns to track its own state as behavior, not as a script it repeats. did some benchmark research too. base qwen3.5-9b scores 9.2% on terminal-bench 2.0. comparable 9b fine-tunes hit 24-28%. that’s our realistic target which is 2.5-3x the baseline. honestly at this point it’s just… waiting. the pipeline works, the checkpoints work, the account switching works. now the model just needs to finish cooking. then trajectory sft, then rlvr, then we actually see the benchmark numbers."}, {"post_id": 40029, "ts": "2026-08-03T11:45:18Z", "hours": 13.3375, "text": "# Devlog #9 — finally training, and now with checkpoints! so last time i was stuck debugging phase 1/2 on kaggle. well, still debugging lol, but we actually got somewhere. the first issue was transformers not knowing what the qwen3.5 model was, had to pin transformers 5.14.1. then tokenizers kept fighting with it (0.22.0 wants old huggingface-hub, 0.22.1 is fine). then torch on kaggle kept giving a p100 which modern pytorch just refuses to run on, so we had to tell it to give us a t4 instead. then the fun one: out of memory on the very first step. batch 2 was too big for the gpu they gave us, so batch 1 it is. also i learned the hard way that kaggle kills your session after 12 hours. the first long run got cancelled at 80% done and i had nothing saved. so now the training script saves a checkpoint every 20% + every hour and uploads it to huggingface, so if it dies we just resume. it actually saved us, the run got cut and we picked right back up from the checkpoint. right now the full 160k sft is running on modal (paying for gpus now, kaggle time ran out). it’s at like 9% and should take a couple days. we’ll see how it goes, and then rlvr after that. the end of the errors… might actually be in sight this time."}, {"post_id": 38292, "ts": "2026-07-31T16:38:26Z", "hours": 5.4886, "text": "Devlog #8 — phase 2 fixes I’ve been getting a lot of issues with the first two for this model. I’ve gotten a lot of errors in Kaggle and Colab. I’ve tried everything, and I’m still fixing the code. It’s taking a good amount of time, but I think I’m almost there. I’ve gone through a lot of errors, and I’m probably right at the end of the errors. I might be able to start actually training it tomorrow, but for now I’ll stop."}, {"post_id": 38079, "ts": "2026-07-31T09:21:05Z", "hours": 10.3872, "text": "Devlog #7 — phase 2 running phase 1 (sft) is done and phase 2 (rlvr) is running now on kaggle. this is the part where the model actually gets trained on solving coding problems with our verifier giving rewards, not just imitating fable data. honestly this is the part i care about more. sft just makes it mimic. rlvr is where it learns to actually fix code. grpo with proportional rewards = the model gets partial credit for getting some tests passing, which is way better than all-or-nothing. while it runs im just waiting tbh. not much to build. the pipeline works, the eval works, the agent works. next after this: full benchmark run. humaneval, swebench, agentic eval. we’ll see if all this actually made the model good at coding or if i just spent a week on a worse qwen lol."}, {"post_id": 37100, "ts": "2026-07-29T16:05:47Z", "hours": 8.4747, "text": "Devlog #6 — training done (phase 1) finally got the qwen finetune to actually run with 625 steps, took like 8 hours on kaggle. it finished. havent run full benchmarks yet cause i was busy building other stuff while it trained. but it trained. thats the main thing. I also built a swebench agent that can actually navigate repos and edit files and make patches. not just the basic agent loop that runs commands. this one actually works for real se tasks. also added swebench eval so we can measure if the model is actually good at fixing bugs and coding then i’ll run the benchmarks on the trained model and see if its actually any good lol."}, {"post_id": 36367, "ts": "2026-07-28T13:16:16Z", "hours": 13.6447, "text": "Devlog #5 — ok so I’m not building a 10B MoE anymore So last time I had this whole plan. 10B MoE, from scratch, SwiGLU, GQA, all that. And I actually built it. Like 60 Python files, tests passing, RL pipeline, self-play data gen, the whole thing. It was kinda sick ngl. But then I was like… wait. I’m building an ENGINE that TRAINS coding agents. Not the agent. And the engine is cool but training a 10B model from zero on $30 of Modal credits is not how you beat GLM-5.2. You know what beats GLM-5.2? Fine-tuning a model that already knows how to code. the pivot (again) Qwen3.5-9B came out. 9B params. Fits on a Kaggle T4 with 4-bit QLoRA. And Kaggle gives me 30 HOURS of free GPU. 2× T4. That’s literally free training. So I had to adapt the entire codebase to work with HuggingFace models instead of my custom GPT. Made like 5 new files. All the verifier/agent/reward stuff I built for the MoE? Now works with Qwen too. Didn’t have to rewrite everything — just slapped a Qwen adapter on top. the dataset Found this dataset on HF: Nexlab/fable5-agentic-coding-sft . 160K rows of Claude Fable 5 output. Like actual coding traces — building games, fixing bugs, writing shell scripts. Not just “write a function that passes a test.” Real agentic stuff. Training right now actually. Qwen3.5-9B on 10K rows. Should take like 8 hours on 2× T4. We’ll see if it doesn’t OOM again lol. While waiting for training I read papers: Routing-Free MoE — what if experts just decide for themselves when to activate? No router, no top-k. Already implemented it in model.py. GLM-5.2 has this IndexShare thing that reuses computation across layers. 2.9× cheaper at 1M context. Maybe later. DeepSWE trained Qwen3-32B with RL only and got 42% SWE-Bench. So our approach is valid. the first phase of training is going on right now, i’ll post another devlog once it’s done!"}, {"post_id": 20759, "ts": "2026-07-02T13:35:48Z", "hours": 5.6175, "text": "Devlog #4 — wait, why am I training on Wikipedia? Last week I got le gros chaton (my from-scratch transformer) to actually train. Ran it on wikitext-103 in a Colab notebook on a free T4, 12k steps, val loss hit 3.73. Felt insane for something I wrote myself from PyTorch primitives. But then I looked at what it generated. It could do English-ish. It knew about Singapore and stuff. The moment I asked it to write code? Total garbage. Fair enough. It has never seen a single line of code. the pivot I thought about what I actually want this thing to do. Answer: a coding agent. Something that mogs on terminal-bench, that you give a task and it runs commands, fixes its own bugs, gets it done. Qwen-coder territory. Wikitext won’t get me there. You can’t learn Python from Wikipedia articles about the snake. So the plan changed. The big project is now le fat chaton, the bigger sibling. And it’s a coder. the architecture stuff I went down a rabbit hole on what frontier coding models do. They’re basically all mixture-of-experts (MoE) now. Qwen3-coder is 480B params / 35B active. Deepseek-coder-v2-lite is 16B / 2.4B active. The trick: big total params (knows a lot) small active params per token (runs fast and cheap) Runs like a small model, knows like a big one. Exactly what I want for a snappy terminal agent. So I rewrote the model. Added an MoE class. A gate routes each token to its top-2 experts out of 8, with a load-balance loss so the router doesn’t pick the same expert every time. Also threw in: SwiGLU — gated MLP, basically free quality, every Llama uses it GQA — smaller KV cache, faster long-context decoding (the agent harness needs this) Shared expert — DeepSeek-style, one always-on expert for common knowledge Fat config math: ~10.25B total / ~3.65B active. Not building that locally, it would crash my PC again. the data question Wikitext was a fine proof. For the coder I need code. Options: smollm-corpus python-edu — 7.6M educational Python files, high quality, but gated behind S3 (slow pull) starcoderdata python — ~50GB Python, streams fast from HF, the Codellama workhorse the-stack-v2 — 900B tokens, overkill for my budget Going with starcoderdata Python, blended with ~15-20% cosmopedia (prose) so it has general knowledge. That blend is the Qwen-coder recipe. am I warm-starting from wikitext? No. Different architecture entirely (17M dense vs 10B MoE, weights don’t fit). Even if they did, warm-starting a coder from prose wastes compute unlearning prose. Fresh random init on the mixed corpus. Clean slate. This went from “lets make a little model that talks” to “lets build a coding agent that mogs the big labs” real fast. Ambitious for a solo student with a 2070 and $30 of Modal credits? Absolutely. Doing it anyway? Yeah. Next: the eval harness so I can measure if this is making the model better at code (pass@1, pass@5 on HumanEval). Val loss going down means nothing if it still can’t write a"}, {"post_id": 20019, "ts": "2026-07-01T14:54:30Z", "hours": 0.3917, "text": "DEVLOG #3: teaching it to talk (fine-tuning) the base model was a completer. ask it “what is 2+2?” and it just continues the sentence. fine-tuning is what makes it actually answer: same model, more training, but on prompt/response pairs. i wrote ~48 Q&A pairs by hand. trivia, math, jokes, hellos. all in the same rigid Q: …\\nA: format. new trick: loss masking. only the response counts toward the loss, not the prompt, so i set prompt targets to -100 (pytorch’s cross_entropy ignores that automatically, zero model changes). tested the mask boundary in isolation first. wrong mask = 400 steps of training the wrong thing. the run: load base weights, 400 steps, lower lr. loss went 12.3 to 0.02.then the reality check. it nails everything in the set. capitals, math, jokes, “who are you,” verbatim. but something NOT in the set? slop. 17M params + 48 examples is a lookup table, not a reasoner. real chat models are billions of params. not a bug, just the scale.but it’s finally coherent. the first base model was word salad. now you type a question and get a real answer back that makes sense. it’s tiny and dumb and can’t generalize, but it actually talks. that’s the win. full pipeline done: tokenizer, model from scratch, pretrain on wikipedia, fine-tune, chat. mine, it talks, i understand every piece."}, {"post_id": 20006, "ts": "2026-07-01T14:16:25Z", "hours": 0.4139, "text": "DEVLOG #2: real data, real loss, and a lesson about memorizing split my data into 90% train / 10% val. before i only had one number, training loss, and it lies to you. you can’t tell learning from memorizing with just that. now i check both every 200 steps. rule: both go down = learning. train down but val up = memorizing = useless.also made the model bigger, 7M -> 17.7M params. immediately ran out of gpu memory lol. dropped batch size to 32 to fit my 8GB card.training: 3000 steps. loss started at 158 (should be ~10 for random , my first pass blew up and made garbage). recovered fast though, didn’t ruin the run. right now the llm is spitting out gibberish and random words but after finetuning it should sound more coherent"}, {"post_id": 19989, "ts": "2026-07-01T13:48:37Z", "hours": 36.31, "text": "DEVLOG #1: wiki text training so i finally got the model to train on actual data instead of that one paragraph about singapore nature reserves lol. before this the whole thing was basically a joke, i trained a 7M parameter transformer on like 134 tokens and it just spat out jumbled fragments of the same sentence over and over. cool proof it worked but definitely not a “language model” in any real sense.anyway. the big move this week was swapping out the tiny json file for wikitext-2. that’s a huggingface dataset of wikipedia text, about 2.4 million tokens once you filter out the empty lines. that’s… a lot more than 134 lol. encoding it took maybe half a minute with tiktoken and the whole tensor fits on my gpu no problem (it’s only like 8MB of ints)."}]...
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Title: le-fat-chaton by @unknown_lizzard | Stardan Title: le-fat-chaton by @unknown_lizzard | Stardance
Devlogs:
DEVLOG #1: wiki text training so i finally got the model to train on actual data instead of that one paragraph about singapore nature reserves lol. before this the whole thing was basically a joke, i trained a 7M parameter transformer on like 134 tokens and it just spat out jumbled fragments of the same sentence over and over. cool proof it worked but definitely not a “language model” in any real sense.anyway. the big move this week was swapping out the tiny json file for wikitext-2. that’s a huggingface dataset of wikipedia text, about 2.4 million tokens once you filter out the empty lines. that’s… a lot more than 134 lol. encoding it took maybe half a minute with tiktoken and the whole tensor fits on my gpu no problem (it’s only like 8MB of ints).
DEVLOG #2: real data, real loss, and a lesson about memorizing split my data into 90% train / 10% val. before i only had one number, training loss, and it lies to you. you can’t tell learning from memorizing with just that. now i check both every 200 steps. rule: both go down = learning. train down but val up = memorizing = useless.also made the model bigger, 7M -> 17.7M params. immediately ran out of gpu memory lol. dropped batch size to 32 to fit my 8GB card.training: 3000 steps. loss started at 158 (should be ~10 for random , my first pass blew up and made garbage). recovered fast though, didn’t ruin the run. right now the llm is spitting out gibberish and random words but after finetuning it should sound more coherent
DEVLOG #3: teaching it to talk (fine-tuning) the base model was a completer. ask it “what is 2+2?” and it just continues the sentence. fine-tuning is what makes it actually answer: same model, more training, but on prompt/response pairs. i wrote ~48 Q&A pairs by hand. trivia, math, jokes, hellos. all in the same rigid Q: …\nA: format. new trick: loss masking. only the response counts toward the loss, not the prompt, so i set prompt targets to -100 (pytorch’s cross_entropy ignores that automatically, zero model changes). tested the mask boundary in isolation first. wrong mask = 400 steps of training the wrong thing. the run: load base weights, 400 steps, lower lr. loss went 12.3 to 0.02.then the reality check. it nails everything in the set. capitals, math, jokes, “who are you,” verbatim. but something NOT in the set? slop. 17M params + 48 examples is a lookup table, not a reasoner. real chat models are billions of params. not a bug, just the scale.but it’s finally coherent. the first base model was word salad. now you type a question and get a real answer back that makes sense. it’s tiny and dumb and can’t generalize, but it actually talks. that’s the win. full pipeline done: tokenizer, model from scratch, pretrain on wikipedia, fine-tune, chat. mine, it talks, i understand every piece.
Devlog #4 — wait, why am I training on Wikipedia? Last week I got le gros chaton (my from-scratch transformer) to actually train. Ran it on wikitext-103 in a Colab notebook on a free T4, 12k steps, val loss hit 3.73. Felt insane for something I wrote myself from PyTorch primitives. But then I looked at what it generated. It could do English-ish. It knew about Singapore and stuff. The moment I asked it to write code? Total garbage. Fair enough. It has never seen a single line of code. the pivot I thought about what I actually want this thing to do. Answer: a coding agent. Something that mogs on terminal-bench, that you give a task and it runs commands, fixes its own bugs, gets it done. Qwen-coder territory. Wikitext won’t get me there. You can’t learn Python from Wikipedia articles about the snake. So the plan changed. The big project is now le fat chaton, the bigger sibling. And it’s a coder. the architecture stuff I went down a rabbit hole on what frontier coding models do. They’re basically all mixture-of-experts (MoE) now. Qwen3-coder is 480B params / 35B active. Deepseek-coder-v2-lite is 16B / 2.4B active. The trick: big total params (knows a lot) small active params per token (runs fast and cheap) Runs like a small model, knows like a big one. Exactly what I want for a snappy terminal agent. So I rewrote the model. Added an MoE class. A gate routes each token to its top-2 experts out of 8, with a load-balance loss so the router doesn’t pick the same expert every time. Also threw in: SwiGLU — gated MLP, basically free quality, every Llama uses it GQA — smaller KV cache, faster long-context decoding (the agent harness needs this) Shared expert — DeepSeek-style, one always-on expert for common knowledge Fat config math: ~10.25B total / ~3.65B active. Not building that locally, it would crash my PC again. the data question Wikitext was a fine proof. For the coder I need code. Options: smollm-corpus python-edu — 7.6M educational Python files, high quality, but gated behind S3 (slow pull) starcoderdata python — ~50GB Python, streams fast from HF, the Codellama workhorse the-stack-v2 — 900B tokens, overkill for my budget Going with starcoderdata Python, blended with ~15-20% cosmopedia (prose) so it has general knowledge. That blend is the Qwen-coder recipe. am I warm-starting from wikitext? No. Different architecture entirely (17M dense vs 10B MoE, weights don’t fit). Even if they did, warm-starting a coder from prose wastes compute unlearning prose. Fresh random init on the mixed corpus. Clean slate. This went from “lets make a little model that talks” to “lets build a coding agent that mogs the big labs” real fast. Ambitious for a solo student with a 2070 and $30 of Modal credits? Absolutely. Doing it anyway? Yeah. Next: the eval harness so I can measure if this is making the model better at code (pass@1, pass@5 on HumanEval). Val loss going down means nothing if it still can’t write a
Devlog #5 — ok so I’m not building a 10B MoE anymore So last time I had this whole plan. 10B MoE, from scratch, SwiGLU, GQA, all that. And I actually built it. Like 60 Python files, tests passing, RL pipeline, self-play data gen, the whole thing. It was kinda sick ngl. But then I was like… wait. I’m building an ENGINE that TRAINS coding agents. Not the agent. And the engine is cool but training a 10B model from zero on $30 of Modal credits is not how you beat GLM-5.2. You know what beats GLM-5.2? Fine-tuning a model that already knows how to code. the pivot (again) Qwen3.5-9B came out. 9B params. Fits on a Kaggle T4 with 4-bit QLoRA. And Kaggle gives me 30 HOURS of free GPU. 2× T4. That’s literally free training. So I had to adapt the entire codebase to work with HuggingFace models instead of my custom GPT. Made like 5 new files. All the verifier/agent/reward stuff I built for the MoE? Now works with Qwen too. Didn’t have to rewrite everything — just slapped a Qwen adapter on top. the dataset Found this dataset on HF: Nexlab/fable5-agentic-coding-sft . 160K rows of Claude Fable 5 output. Like actual coding traces — building games, fixing bugs, writing shell scripts. Not just “write a function that passes a test.” Real agentic stuff. Training right now actually. Qwen3.5-9B on 10K rows. Should take like 8 hours on 2× T4. We’ll see if it doesn’t OOM again lol. While waiting for training I read papers: Routing-Free MoE — what if experts just decide for themselves when to activate? No router, no top-k. Already implemented it in model.py. GLM-5.2 has this IndexShare thing that reuses computation across layers. 2.9× cheaper at 1M context. Maybe later. DeepSWE trained Qwen3-32B with RL only and got 42% SWE-Bench. So our approach is valid. the first phase of training is going on right now, i’ll post another devlog once it’s done!
Devlog #6 — training done (phase 1) finally got the qwen finetune to actually run with 625 steps, took like 8 hours on kaggle. it finished. havent run full benchmarks yet cause i was busy building other stuff while it trained. but it trained. thats the main thing. I also built a swebench agent that can actually navigate repos and edit files and make patches. not just the basic agent loop that runs commands. this one actually works for real se tasks. also added swebench eval so we can measure if the model is actually good at fixing bugs and coding then i’ll run the benchmarks on the trained model and see if its actually any good lol.
Devlog #7 — phase 2 running phase 1 (sft) is done and phase 2 (rlvr) is running now on kaggle. this is the part where the model actually gets trained on solving coding problems with our verifier giving rewards, not just imitating fable data. honestly this is the part i care about more. sft just makes it mimic. rlvr is where it learns to actually fix code. grpo with proportional rewards = the model gets partial credit for getting some tests passing, which is way better than all-or-nothing. while it runs im just waiting tbh. not much to build. the pipeline works, the eval works, the agent works. next after this: full benchmark run. humaneval, swebench, agentic eval. we’ll see if all this actually made the model good at coding or if i just spent a week on a worse qwen lol.
Devlog #8 — phase 2 fixes I’ve been getting a lot of issues with the first two for this model. I’ve gotten a lot of errors in Kaggle and Colab. I’ve tried everything, and I’m still fixing the code. It’s taking a good amount of time, but I think I’m almost there. I’ve gone through a lot of errors, and I’m probably right at the end of the errors. I might be able to start actually training it tomorrow, but for now I’ll stop.
# Devlog #9 — finally training, and now with checkpoints! so last time i was stuck debugging phase 1/2 on kaggle. well, still debugging lol, but we actually got somewhere. the first issue was transformers not knowing what the qwen3.5 model was, had to pin transformers 5.14.1. then tokenizers kept fighting with it (0.22.0 wants old huggingface-hub, 0.22.1 is fine). then torch on kaggle kept giving a p100 which modern pytorch just refuses to run on, so we had to tell it to give us a t4 instead. then the fun one: out of memory on the very first step. batch 2 was too big for the gpu they gave us, so batch 1 it is. also i learned the hard way that kaggle kills your session after 12 hours. the first long run got cancelled at 80% done and i had nothing saved. so now the training script saves a checkpoint every 20% + every hour and uploads it to huggingface, so if it dies we just resume. it actually saved us, the run got cut and we picked right back up from the checkpoint. right now the full 160k sft is running on modal (paying for gpus now, kaggle time ran out). it’s at like 9% and should take a couple days. we’ll see how it goes, and then rlvr after that. the end of the errors… might actually be in sight this time.
** Devlog #10 the full training is finally running ** ok so phase 1 full training is officially going. 160k rows of fable5 data on modal, resuming from the 12.8k rows we got on kaggle before the session cap killed us. we’re at ~27% and it should take like a day and a half total. big stuff that happened since last time: fast kernels actually work now. the model has hybrid linear-attention layers and transformers kept falling back to a slow torch path. the fix was: nvidia cuda-devel base image (needs nvcc to compile), installing flash-linear-attention[cuda] + causal-conv1d , and pinning torch 2.10. took a couple tries but now training is like 4x faster than it would be without them. had to split across two modal accounts. first account ran out of credits, so we set up a second profile and the script auto-resumes from the huggingface checkpoints when it dies. it’s been rock solid, it happens every 20% plus every hour it saves and uploads. lost zero progress to the account switch. we gave the model a personality. it’s called Le Gros Chaton (the fat cat) and we’re training self-awareness into it, not as a system prompt but baked into the weights. state-sheets ([STATE] goal/known/tried/failed/next), metacognition lines, and self-review at the end of tasks. the trajectory sft masks out the system prompt so the model learns to track its own state as behavior, not as a script it repeats. did some benchmark research too. base qwen3.5-9b scores 9.2% on terminal-bench 2.0. comparable 9b fine-tunes hit 24-28%. that’s our realistic target which is 2.5-3x the baseline. honestly at this point it’s just… waiting. the pipeline works, the checkpoints work, the account switching works. now the model just needs to finish cooking. then trajectory sft, then rlvr, then we actually see the benchmark numbers.
** Devlog #11 half way there! ** the training is going pretty well, I fixed a few bugs with the code and added documentation training is at 50%!
Devlog #12 training kept dying for the last 10 hours the training kept crashing. not the model, not the gp but the modal client. every hour or so it would lose connection and take the whole run down with it. we’d restart, it’d run an hour, crash again. three times. the fix was simple: modal run -d runs detached, so the training lives on modal’s servers and doesn’t care if our local process dies. killed the client on purpose to test — training kept going. that’s it, that’s the fix. also worried the loss wasn’t moving but it was fine. lr had wound down on the crashed run, looked scary, re-warmed fine after restart. loss is 0.668 now and dropping. status: 72% through the fable5 sft. checkpoints safe on hf. after this: trajectory sft with the self-awareness stuff baked in, then rlvr, then real numbers.
Devlog #13 we worked ALOT so this was the grind day. 18 hours of training babysitting and honestly it felt like 40. the modal training kept dying every hour. the client would crash and take the whole run with it. we restarted like 3 times before figuring out modal run -d (detached) keeps it alive on their servers even if our computer shits the bed. tested it by literally killing the process and it kept going. ez fix but we worked ALOT to get there. then we ran out of credits at 93% and switched accounts, but the other account “finished” the run in 6 MILLISECONDS which was sus af. turns out it just re-uploaded the old checkpoint and trained nothing. the resume logic had a bug where it thought 6200 >= 3799 meant done. patched it. another lesson learned. also we made the model creative lol. added diversity sampling to the trajectory generator (5 solutions per task, keep the novel ones), a novelty bonus reward for RLVR, and a creativity rule in the self-awareness prompt. so the fat cat will be innovative, not just memorize. current state: SFT is done at 91% (good enough), resume bug fixed, phase 2 (trajectory SFT with creativity + self-awareness baked in) is up next. 18 hours. we worked ALOT. the fat cat will be worth it 😼
Devlog #14 worked a lot, still not done we worked a lot this week. honestly the main takeaway is that the fable5 sft was good but its traces alone weren’t enough the model needs way more verified agent trajectories, so we’ve been grinding those out (target is 450). we also ran out of credits mid-generation (the modal endpoint started failing with 503s) and had to switch to a second kimi account. took a minute to get the auth right the new endpoint wanted an extra header we didn’t have. after that the generator resumed fine and it’s been adding verified traces since (~340/450 now). biggest scare: we found out peft 0.20 silently drops the second adapter when you merge two at once. tested it and yeah, the outputs were identical with one or two adapters so our trajectory sft would have been lost in the merge. fixed it by merging sequentially (base first, then the second adapter). checked against the live model and it matches, so we’re good. my 2070 couldn’t fit the 9b model for real training, so we’re waiting on a 4090 (my dad’s) next week. all the scripts are ready sft, merge, rlvr, eval, even a setup script for the gpu box. just need the hardware. status: 340/450 traces, everything ready, waiting on the 4090. we’ve worked a lot, but the real run hasn’t happened yet :/.
Devlog 15 Traces are done The trace generator finally hit the target and went past it. We got 474 verified trajectories, zero malformed, zero duplicates, 19 templates, and a 95 percent self review pass rate. We were aiming for 450, so we ended up with 474. The dataset is synced to Hugging Face in two versions: raw and normalized. That part is finally done. It was the longest part of the project, and the model is only going to be as good as the traces, so getting this right was important The Kimi endpoint also stopped working. The old teacher account started returning 503 errors during generation and eventually died completely. We switched to a second Kimi account, which needed an extra header that we did not have at first. After figuring that out, generation resumed without losing any progress For GPUs, the 2070 still cannot realistically train the 9B. Kaggle hours are back, so we have 30 hours on a T4. The 4090 from my dad should arrive next week. The plan is to use the T4 for trajectory SFT, then the 4090 for merging, Terminal Bench evaluation, and RLVR. Status: 474 out of 474 traces done,
Devlog #16, t4gpu The T4 16GB fought us the whole way. BF16 was baked into a pre quantized checkpoint, which made each step take 668 seconds because it had to use FP32 emulation. 2K context ran out of memory, the 248K logits ran out of memory too, FP16 started producing NaNs, Kaggle session limits locked us out, and the paged optimizer crashed last. Every fix seemed to create another problem. We eventually got it working with FP16 compute, chunked assistant token loss, autocast, and plain AdamW. Then we got access to an AMD MI300X with 192GB of memory. No quantization, 16K context, and enough memory to train full traces instead of cutting them off halfway through a message. Right now the 16K BF16 SFT run is training on the MI300X. Next up is merging the model, running Terminal Bench, and then RLVR.
devlog #17 MI300X vLLM serving The old GPU box got destroyed, so I spun up a new MI300X with the same SSH key. ROCm 6.2 and Torch 2.5.1 were already set up, so getting the machine ready was easy. The hard part was vLLM. The pip version is CUDA only, and the ROCm Docker image only supported the multimodal version of Qwen3.5. Our model is text-only, so I had to patch the image. I added Qwen3_5ForCausalLM, fixed the hybrid KV-cache setup, added the missing Mamba state methods, and mapped the weight names so the text-only safetensors loaded correctly. I also patched the merged config to remove the M-RoPE and dtype fields. After that, the model served normally. I ran a one-task test with fix-git. The pipeline worked, but the model got stuck repeating git show until it ran out of turns. ##Shipped The merged model is now public on Hugging Face as mateo0093/le-gros-chaton under Apache-2.0. The 5×5 Terminal-Bench pilot finished at 3/25 (25%). All three successes were on fix-git, which shows that the SFT data was too focused on git tasks. I also tested RLVR with GRPO and a novelty bonus. The reward had almost no variance, so the training signal was basically useless. I saved the step-10 adapter but didn’t merge it. The GPU used about 12 hours of the 50 hour budget. All the vLLM patches and harness changes are in the repo. Main lesson: Qwen3.5’s hybrid model is a bit annoying to serve as text-only on ROCm. The model works but i think this was more of a learning opportunity, i know what i’ve done wrong and what i would have done differently, I will be working on a new model in a few weeks once I do a bit more research.
Ships:
at first I wanted to make a normal text model to try and learn more about llms, but I wanted to go further, agentic coding is a big thing so what better way to learn about llms than trying to make an agentic coding ai model. So thats how le gros chaton was born, the name originated from a joke on x about a fake huge mistral model coming out. to train this model I used already made datasets on hugging face, like fable5 traces, I also used kimi k3 as a teacher model to teach my smaller model to be good at coding and running commands, it kind of worked? but i’m not completely satisfied with the result, but at least i have learned some things and soon enough I will trying making an even better model! I dont have a demo url for you guys to try the model out since it was too expensive to run on a gpu so you’ll need to run it yourself, check it out on hugging face, follow the instructions and have fun....
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le site and first project by @harshjmakwana13 | St le site and first project by @harshjmakwana13 | Stardance...
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Title: le site and first project by @harshjmakwana Title: le site and first project by @harshjmakwana13 | Stardance...
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lbarragan personal portfolio by @Corentfley | Star lbarragan personal portfolio by @Corentfley | Stardance...
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Title: lbarragan personal portfolio by @Corentfley Title: lbarragan personal portfolio by @Corentfley | Stardance...
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18
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-08-30T09:08:41Z", "hours": 4.0, "multiplier": 4.46, "payout": 18, "blessing": "neutral", "text": "i have added some features and apps, i gave the page a icon added a top section for Quotes added a calculator added a browser which can do Google searches added a music player These were some main features, Besides these, i added some images in the gallery and 3 focus songs…", "repo": "https://github.com/Tiyasbanerjee/LazyOs", "demo": "https://tiyasbanerjee.github.io/LazyOs/"}, {"ship_num": 2, "ts": "2026-08-22T12:43:59Z", "hours": 14.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "i made a webOS, i named it LazyOs, because my mom calls me lazy… i have used my own clicked photos , which looks really cool. you can see my childhood pic, and also some other pics. there is a gallery app you can open to explore the photos, i tried to do animate as much as i could… and that littery fried my brain to understand… i also added a note app, you can write something if you want… i think i will add more features and apps in it soon… it really feels so good to see my os working…", "repo": "https://github.com/Tiyasbanerjee/LazyOs", "demo": "https://tiyasbanerjee.github.io/LazyOs/"}]...
|
[{"post_id": 57950, "ts": "202 [{"post_id": 57950, "ts": "2026-08-30T09:01:55Z", "hours": 0.6811, "text": "i have added a calculator…"}, {"post_id": 57925, "ts": "2026-08-30T08:14:31Z", "hours": 0.5925, "text": "i have added a browser which can make google searches…."}, {"post_id": 57894, "ts": "2026-08-30T07:01:31Z", "hours": 0.4369, "text": "i have added a motivational quote section which will show you a motivational quotes every time you reload it…"}, {"post_id": 57133, "ts": "2026-08-29T07:32:04Z", "hours": 1.8708, "text": "i have added a music player today…"}, {"post_id": 56461, "ts": "2026-08-28T07:18:13Z", "hours": 0.5008, "text": "i have added a new application , a clock."}, {"post_id": 52295, "ts": "2026-08-22T12:35:00Z", "hours": 2.2133, "text": "pushed one github, and its working properly. the photo app is also build , and i am ready to submit it now."}, {"post_id": 51787, "ts": "2026-08-21T17:05:36Z", "hours": 1.7756, "text": "fixed some bugs, and made this note app window, now i am working on making this usable , and beautiful…"}, {"post_id": 51419, "ts": "2026-08-21T03:34:00Z", "hours": 0.7631, "text": "updated the wallpapers and images to fit my vibe…"}, {"post_id": 51192, "ts": "2026-08-20T18:13:20Z", "hours": 0.4108, "text": "made some more app start buttons and windows for them. i am planing to include a calculator, a note book, a wallpaper manager, a music player…"}, {"post_id": 51055, "ts": "2026-08-20T15:16:06Z", "hours": 0.7808, "text": "added feature to open closed window, and a fancy button. and fixed some minor bugs today."}, {"post_id": 50818, "ts": "2026-08-20T07:48:11Z", "hours": 0.8594, "text": "now in our lazy os, you can close windows !"}, {"post_id": 50533, "ts": "2026-08-19T18:39:57Z", "hours": 1.1256, "text": "i have made the window dragable, but now i noticed a new type of bug. for making the window absolute its is flowing out of the screen… if you have any tips, tell me…"}, {"post_id": 50171, "ts": "2026-08-19T08:54:24Z", "hours": 0.9708, "text": "i have finished the 2ed part of this project, making the home screen. now the next step is to make the window resizable and draggable…"}, {"post_id": 50139, "ts": "2026-08-19T07:35:34Z", "hours": 2.7311, "text": "It took me a good amount of time to make this animation. and hope it looks good. Please tell me what do you think?"}, {"post_id": 49381, "ts": "2026-08-18T05:19:10Z", "hours": 1.9619, "text": "working on making personal os, and it is the welcome page… i tried to make it look cool , and also tried to personalize. some features are not done, like the redirect buttons , and a animation when clicking my ghibili photo.. though i am think if i can create that animation… i want when hovering over the picture, it rotates and the photo changes into another photo which will be my OS icon… if you can give me some suggestions i will be thankful."}]...
|
Title: lazyOS by @tiyas | Stardance
Devlogs:
work Title: lazyOS by @tiyas | Stardance
Devlogs:
working on making personal os, and it is the welcome page… i tried to make it look cool , and also tried to personalize. some features are not done, like the redirect buttons , and a animation when clicking my ghibili photo.. though i am think if i can create that animation… i want when hovering over the picture, it rotates and the photo changes into another photo which will be my OS icon… if you can give me some suggestions i will be thankful.
It took me a good amount of time to make this animation. and hope it looks good. Please tell me what do you think?
i have finished the 2ed part of this project, making the home screen. now the next step is to make the window resizable and draggable…
i have made the window dragable, but now i noticed a new type of bug. for making the window absolute its is flowing out of the screen… if you have any tips, tell me…
now in our lazy os, you can close windows !
added feature to open closed window, and a fancy button. and fixed some minor bugs today.
made some more app start buttons and windows for them. i am planing to include a calculator, a note book, a wallpaper manager, a music player…
updated the wallpapers and images to fit my vibe…
fixed some bugs, and made this note app window, now i am working on making this usable , and beautiful…
pushed one github, and its working properly. the photo app is also build , and i am ready to submit it now.
i have added a new application , a clock.
i have added a music player today…
i have added a motivational quote section which will show you a motivational quotes every time you reload it…
i have added a browser which can make google searches….
i have added a calculator…
Ships:
i made a webOS, i named it LazyOs, because my mom calls me lazy… i have used my own clicked photos , which looks really cool. you can see my childhood pic, and also some other pics. there is a gallery app you can open to explore the photos, i tried to do animate as much as i could… and that littery fried my brain to understand… i also added a note app, you can write something if you want… i think i will add more features and apps in it soon… it really feels so good to see my os working…
i have added some features and apps, i gave the page a icon added a top section for Quotes added a calculator added a browser which can do Google searches added a music player These were some main features, Besides these, i added some images in the gallery and 3 focus songs…...
|
1793616776.5618405
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1793703176.5618405
|
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31953
|
lavende by @sahilarun | Stardance
|
sahilarun
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: lavende by @sahilarun | Stardance
|
1793501403.4402118
|
1794106203.4402118
|
|
32190
|
lavende by @aikyaam | Stardance
|
aikyaam
|
1
|
12.0
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-07-07T17:10:33Z", "hours": 12.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "We built Lavende, a high-performance Discord voice engine written in Rust with official SDKs for Rust, JavaScript/TypeScript, Go, and Python. Instead of relying on an external Lavalink server, Lavende runs in-process and provides a consistent API across multiple programming languages for building Discord music bots and voice applications. One of the biggest challenges was designing a shared Rust core while exposing safe, idiomatic bindings for each language. We also reorganized the repository into a workspace, simplified the build and release pipeline, and implemented cross-platform native binaries to make installation easier for developers. We’re most proud of creating a single, high-performance voice engine that can be used across multiple ecosystems without sacrificing performance or developer experience. To test the project, open the _examples folder and choose the language you want to use (Rust, JavaScript/TypeScript, Go, or Python). For example, if you choose the Node.js example, navigate to that folder, install the dependencies, add your Discord bot token to the .env file, and run the bot. The setup process is essentially the same for all the supported languages, with language-specific instructions included in each example.", "repo": "", "demo": ""}]...
|
[{"post_id": 31662, "ts": "202 [{"post_id": 31662, "ts": "2026-07-20T07:50:38Z", "hours": 0.0, "text": "Spent today improving Lavende’s core playback reliability. Fixed several issues with the YouTube source after recent extraction changes, preventing playback failures. Resolved a bug where the player was being recreated on every request, allowing playback state and queues to persist correctly. Tracked down 404 search errors to empty search results (length: 0) and added proper handling for cases where no tracks are returned. Also improved the voice connection lifecycle, making joins, reconnects, and playback significantly more stable."}, {"post_id": 28104, "ts": "2026-07-14T05:01:31Z", "hours": 0.0, "text": "[v1.0.6] - 2026-07-14 Changed Complete refactoring of all legacy monolithic audio source files into clean, modular subdirectories (api, extractor, track, token, reader, etc.) to improve maintainability and decouple codebase components. Rewrote let-chain patterns to standard nested conditional patterns to enhance stability and ensure compatibility with standard Rust compilation profiles."}, {"post_id": 24590, "ts": "2026-07-08T09:21:10Z", "hours": 0.0, "text": "Today I completed the configPath feature across all Lavende language bindings (Rust, Node.js, Python, and Go). I updated the documentation and examples to support custom configuration file paths, making configuration management consistent across every SDK. I also expanded and standardized the source.json configuration files, adding comprehensive support for 28+ music sources and ensuring all examples use the same configuration structure. With these changes, the configuration system is now fully documented, consistent, and much easier for developers to use."}, {"post_id": 24209, "ts": "2026-07-07T16:57:02Z", "hours": 12.4317, "text": "Today we wrapped up the final release of Lavende. Most of our time was spent polishing the library, fixing the remaining bugs we found during testing, and making sure everything was stable before shipping. We also cleaned up the project structure, improved the developer experience, and updated the examples and documentation so the library is easier to understand and use. After running through the final round of testing, we were happy with the results and prepared the project for release. It’s exciting to finally reach this milestone after all the work that’s gone into the project. From here, we’ll focus on maintenance, performance improvements, and new features based on feedback from users."}]...
|
Title: lavende by @aikyaam | Stardance
Devlogs:
T Title: lavende by @aikyaam | Stardance
Devlogs:
Today we wrapped up the final release of Lavende. Most of our time was spent polishing the library, fixing the remaining bugs we found during testing, and making sure everything was stable before shipping. We also cleaned up the project structure, improved the developer experience, and updated the examples and documentation so the library is easier to understand and use. After running through the final round of testing, we were happy with the results and prepared the project for release. It’s exciting to finally reach this milestone after all the work that’s gone into the project. From here, we’ll focus on maintenance, performance improvements, and new features based on feedback from users.
Today I completed the configPath feature across all Lavende language bindings (Rust, Node.js, Python, and Go). I updated the documentation and examples to support custom configuration file paths, making configuration management consistent across every SDK. I also expanded and standardized the source.json configuration files, adding comprehensive support for 28+ music sources and ensuring all examples use the same configuration structure. With these changes, the configuration system is now fully documented, consistent, and much easier for developers to use.
[v1.0.6] - 2026-07-14 Changed Complete refactoring of all legacy monolithic audio source files into clean, modular subdirectories (api, extractor, track, token, reader, etc.) to improve maintainability and decouple codebase components. Rewrote let-chain patterns to standard nested conditional patterns to enhance stability and ensure compatibility with standard Rust compilation profiles.
Spent today improving Lavende’s core playback reliability. Fixed several issues with the YouTube source after recent extraction changes, preventing playback failures. Resolved a bug where the player was being recreated on every request, allowing playback state and queues to persist correctly. Tracked down 404 search errors to empty search results (length: 0) and added proper handling for cases where no tracks are returned. Also improved the voice connection lifecycle, making joins, reconnects, and playback significantly more stable.
Ships:
We built Lavende, a high-performance Discord voice engine written in Rust with official SDKs for Rust, JavaScript/TypeScript, Go, and Python. Instead of relying on an external Lavalink server, Lavende runs in-process and provides a consistent API across multiple programming languages for building Discord music bots and voice applications. One of the biggest challenges was designing a shared Rust core while exposing safe, idiomatic bindings for each language. We also reorganized the repository into a workspace, simplified the build and release pipeline, and implemented cross-platform native binaries to make installation easier for developers. We’re most proud of creating a single, high-performance voice engine that can be used across multiple ecosystems without sacrificing performance or developer experience. To test the project, open the _examples folder and choose the language you want to use (Rust, JavaScript/TypeScript, Go, or Python). For example, if you choose the Node.js example, navigate to that folder, install the dependencies, add your Discord bot token to the .env file, and run the bot. The setup process is essentially the same for all the supported languages, with language-specific instructions included in each example....
|
1793368269.496202
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1794232269.496202
|
|
4830
|
laurengracebroadbent by @laurengracebroadbent | St laurengracebroadbent by @laurengracebroadbent | Stardance...
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laurengracebroadbent
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0
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0.0
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0
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[]
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[]
|
Title: laurengracebroadbent by @laurengracebroadbe Title: laurengracebroadbent by @laurengracebroadbent | Stardance...
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1792932879.0149727
|
1793796879.0149727
|
|
63805
|
launchpad hotkey board by @valdtaniem | Stardance
|
valdtaniem
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: launchpad hotkey board by @valdtaniem | Sta Title: launchpad hotkey board by @valdtaniem | Stardance...
|
1793663705.3488665
|
1794268505.3488665
|
|
50635
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late night fishing game by @frankly2012 | Stardanc late night fishing game by @frankly2012 | Stardance...
|
frankly2012
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: late night fishing game by @frankly2012 | S Title: late night fishing game by @frankly2012 | Stardance...
|
1793353998.713449
|
1793958798.713449
|
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70073
|
last surprise project by @amateur_tech_guy | Stard last surprise project by @amateur_tech_guy | Stardance...
|
amateur_tech_guy
|
0
|
0.55
|
0
|
[]
|
[{"post_id": 81139, "ts": "202 [{"post_id": 81139, "ts": "2026-10-20T01:21:44Z", "hours": 0.5511, "text": "devlog #1: working on a surprise new project! I wont tell anyone what it is yet, try to guess, heres a hint"}]...
|
Title: last surprise project by @amateur_tech_guy Title: last surprise project by @amateur_tech_guy | Stardance
Devlogs:
devlog #1: working on a surprise new project! I wont tell anyone what it is yet, try to guess, heres a hint...
|
1793605798.2375047
|
1794210598.2375047
|
|
71574
|
last star dust project by @ayeshawadoodkhan | Star last star dust project by @ayeshawadoodkhan | Stardance...
|
ayeshawadoodkhan
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: last star dust project by @ayeshawadoodkhan Title: last star dust project by @ayeshawadoodkhan | Stardance...
|
1793098022.790886
|
1793702822.790886
|
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69605
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last run by @reyaanshgadia | Stardance
|
reyaanshgadia
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: last run by @reyaanshgadia | Stardance
|
1793584336.2629476
|
1794189136.2629476
|
|
67300
|
last minute blare by @Giostrix | Stardance
|
Giostrix
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: last minute blare by @Giostrix | Stardance
|
1793109039.323333
|
1793713839.323333
|
|
48235
|
last laugh by @adityashah | Stardance
|
adityashah
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: last laugh by @adityashah | Stardance
|
1793220539.8633485
|
1793825339.8633485
|
|
66148
|
last boss by @Xenoxx | Stardance
|
Xenoxx
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: last boss by @Xenoxx | Stardance
|
1793094753.8402107
|
1793958753.8402107
|
|
25100
|
laserCat by @QD | Stardance
|
QD
|
0
|
7.43
|
0
|
[]
|
[{"post_id": 19006, "ts": "202 [{"post_id": 19006, "ts": "2026-06-30T05:12:49Z", "hours": 7.4342, "text": "PCB wiring"}]...
|
Title: laserCat by @QD | Stardance
Devlogs:
PCB w Title: laserCat by @QD | Stardance
Devlogs:
PCB wiring...
|
1793393610.9237049
|
1793998410.9237049
|
|
61981
|
las teclas by @Vini_dev | Stardance
|
Vini_dev
|
1
|
1.0
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-09-28T00:58:51Z", "hours": 1.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I created a macropad called MarcinhoPad (I couldn’t think of what to call it, so I decided to combine my name with the word ‘pad’ at the end). This project really challenged me, as it was the first ‘big’ project I’ve ever made. But the most annoying thing that gave me a huge headache was the LEDs. Man, it felt like nothing was working! I would run the ERC and it gave so many errors, so many errors, that I almost gave up on the project, but I decided to just remove them—didn’t want any more headaches, lol. Not to mention the 3D modeling: I spent two nights without sleep just thinking about it. Before going to school, I would make use of the 1 hour I had, get up, and turn on the PC right away to try to finish the model. Same thing when I got back, exhausted and only thinking about sleep, but there I was, learning 3D modeling, lol. Now, what made me think ‘I’m the man’ the most—my ego totally inflated when I finished the project and it got approved. Man, my heart raced with joy, I saw that my hard work paid off! Ah, I was almost forgetting, lol: to test the project, all you need is Arduino IDE installed. Connect the board to your computer’s USB, clone my repository, and flash my code.", "repo": "https://github.com/Developer-Vini/MarcinhoPad", "demo": ""}]...
|
[{"post_id": 74675, "ts": "202 [{"post_id": 74675, "ts": "2026-09-27T23:40:24Z", "hours": 1.0117, "text": "I went to see if it would actually work; I managed to mount the 3D parts on the board to test everything, and I made a few tweaks. I think I’ll go for a unique design—I’m thinking of making it all black; it’s going to look awesome."}, {"post_id": 70908, "ts": "2026-09-20T00:28:59Z", "hours": 0.5489, "text": "Finished!"}, {"post_id": 70294, "ts": "2026-09-18T21:46:34Z", "hours": 1.5661, "text": "Trying to model the case (it’s proving very difficult)."}, {"post_id": 69899, "ts": "2026-09-18T01:08:57Z", "hours": 0.505, "text": "What a beautiful PCB!"}, {"post_id": 69414, "ts": "2026-09-17T00:28:16Z", "hours": 0.8728, "text": "finished!!"}, {"post_id": 69376, "ts": "2026-09-16T22:36:50Z", "hours": 2.135, "text": "I decided to remove the LEDs; I’m going to do it without them. Connecting the LEDs was proving too difficult, so I preferred to leave them out. The important thing is that it works. The PCB is already complete; now I just need to adjust a few things and transfer it to the case."}, {"post_id": 69241, "ts": "2026-09-16T17:26:35Z", "hours": 2.7272, "text": "I finished the schematic and I’m going to the PCB, now I just have to decide what I want to do haha, I’m very indecisive, I have to see the layout."}, {"post_id": 68918, "ts": "2026-09-16T01:29:57Z", "hours": 1.9889, "text": "Yo guys, I was studying how I could do the hackpad scheme, man, think of a work that is giving, but it’s gonna work out, there’s no rush."}, {"post_id": 67760, "ts": "2026-09-14T00:25:31Z", "hours": 0.3833, "text": "i was preparing the work environment to begin development."}]...
|
Title: las teclas by @Vini_dev | Stardance
Devlog Title: las teclas by @Vini_dev | Stardance
Devlogs:
i was preparing the work environment to begin development.
Yo guys, I was studying how I could do the hackpad scheme, man, think of a work that is giving, but it’s gonna work out, there’s no rush.
I finished the schematic and I’m going to the PCB, now I just have to decide what I want to do haha, I’m very indecisive, I have to see the layout.
I decided to remove the LEDs; I’m going to do it without them. Connecting the LEDs was proving too difficult, so I preferred to leave them out. The important thing is that it works. The PCB is already complete; now I just need to adjust a few things and transfer it to the case.
finished!!
What a beautiful PCB!
Trying to model the case (it’s proving very difficult).
Finished!
I went to see if it would actually work; I managed to mount the 3D parts on the board to test everything, and I made a few tweaks. I think I’ll go for a unique design—I’m thinking of making it all black; it’s going to look awesome.
Ships:
I created a macropad called MarcinhoPad (I couldn’t think of what to call it, so I decided to combine my name with the word ‘pad’ at the end). This project really challenged me, as it was the first ‘big’ project I’ve ever made. But the most annoying thing that gave me a huge headache was the LEDs. Man, it felt like nothing was working! I would run the ERC and it gave so many errors, so many errors, that I almost gave up on the project, but I decided to just remove them—didn’t want any more headaches, lol. Not to mention the 3D modeling: I spent two nights without sleep just thinking about it. Before going to school, I would make use of the 1 hour I had, get up, and turn on the PC right away to try to finish the model. Same thing when I got back, exhausted and only thinking about sleep, but there I was, learning 3D modeling, lol. Now, what made me think ‘I’m the man’ the most—my ego totally inflated when I finished the project and it got approved. Man, my heart raced with joy, I saw that my hard work paid off! Ah, I was almost forgetting, lol: to test the project, all you need is Arduino IDE installed. Connect the board to your computer’s USB, clone my repository, and flash my code....
|
1793684988.3208437
|
1793771388.3208437
|
|
62383
|
larp o'clock by @kunshyuh | Stardance
|
kunshyuh
|
0
|
1.27
|
0
|
[]
|
[{"post_id": 82171, "ts": "202 [{"post_id": 82171, "ts": "2026-10-24T04:58:22Z", "hours": 1.2669, "text": "update - 1 designed the pcb schematic mainly with the help of the diagrams given in the blare website and now gonna headon to the actual casing and placement of buzzer and buttons"}]...
|
Title: larp o'clock by @kunshyuh | Stardance
Title: larp o'clock by @kunshyuh | Stardance
Devlogs:
update - 1 designed the pcb schematic mainly with the help of the diagrams given in the blare website and now gonna headon to the actual casing and placement of buzzer and buttons...
|
1793656083.7104282
|
1794260883.7104282
|
|
58478
|
larp by @tjingi_ | Stardance
|
tjingi_
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: larp by @tjingi_ | Stardance
|
1793494254.2940254
|
1794099054.2940254
|
|
6467
|
larning by @PRATINOX | Stardance
|
PRATINOX
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: larning by @PRATINOX | Stardance
|
1793253357.4503057
|
1793858157.4503057
|
|
51812
|
laptop cooler by @ys996x | Stardance
|
ys996x
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: laptop cooler by @ys996x | Stardance
|
1793408160.1982033
|
1794012960.1982033
|
|
54670
|
language learning helper (llh) by @tsellios | Star language learning helper (llh) by @tsellios | Stardance...
|
tsellios
|
0
|
11.78
|
0
|
[]
|
[{"post_id": 68202, "ts": "202 [{"post_id": 68202, "ts": "2026-09-14T18:09:44Z", "hours": 0.8333, "text": "FINALLY completed the case!! After a lot of work I finally completed the case for the llh. The project might be pretty much ready for funding. Although it is an issue, I guess, that the words can only be up to 16 characters (size of each block), I might find a way of doubling that tomorrow like using 2 blocks and that Ill submit it!!"}, {"post_id": 66700, "ts": "2026-09-12T16:05:46Z", "hours": 1.2, "text": "Almost completed the case!!! Today I finished the bottom and top part of the case. Only thing left before this project is finished is adding a way to connect the 2 parts, adding the handle, and an opening for the switch. In contrast with how it looked yesterday, i am much more proud today. (almost done :))"}, {"post_id": 66109, "ts": "2026-09-11T18:17:15Z", "hours": 1.0, "text": "Made significant progress on the case today I mapped out every other part and finally got it into the 3rd dimension. I decided that making threads was too hard for my first project, so I will make the holes a bit smaller than the screws, so that the will be able to screw on easily (hopefully). Additionally, I will need to add a hole on the side, since i decided to add a switch to turn it one and off."}, {"post_id": 65543, "ts": "2026-09-10T19:05:25Z", "hours": 1.1, "text": "Made for progress on the case Today I added the esp and the mfrc552 in the sketch, (the lcd and the button I will have to do tomorrow). The size is kind of, funky. Once completed it will be 15 10cm (apprx. 6 4 inch.) and will be kind of flat, and with the addition of the handle, I am not sure how I will look holding the printed case irl. I also will have to consider stability and have to start thinking how to make the handle. Lastly, I need to consider how the power will be supplied, which is something I have given enough thought. I hope to get this done by Sunday, but we’ll see. I am kind of proud of myself."}, {"post_id": 64933, "ts": "2026-09-09T17:33:50Z", "hours": 1.7503, "text": "Started working on the 3d case for the llh I had no idea where to start from, and to be honest, I was afraid to start. I watched a tutorial, that suggested openscad, which while seems cool, just didnt work for me. I instead chose onshape. While this thing ,might not look like much, it took me a fair while and i am really proud. Despite now having much time with school, i will try to finish the case within the week to finally ship. i hope ill get better at cad and make something that actually looks pleasing to the eye."}, {"post_id": 62402, "ts": "2026-09-05T18:58:40Z", "hours": 0.5833, "text": "redid the circuit in wokwi I needed to remake it since it was not properly saved. Now its time to make the case it cad which really scares me and so I researched a bit abt it."}, {"post_id": 61037, "ts": "2026-09-03T19:01:22Z", "hours": 1.2317, "text": "I completed the main code for the llh today I basically completed the main code for the llh today, I was pretty pleased with the code I had written, until I compiled it and a lot of errors showed up. Most of them were just mistakes I made when writing the code. The rest was the lcd i2c library not working. Despite that, I think the code will work great and i am really proud. I will look into the i2c library tomorrow"}, {"post_id": 60438, "ts": "2026-09-02T19:27:57Z", "hours": 0.6167, "text": "Started the main code for the llh Wrote the code that will read the words off the NFC stickers. I am pretty happy about the progress since this got done pretty fast. Tomorrow, I will complete the rest of the code (LDC, buttons)."}, {"post_id": 59709, "ts": "2026-09-01T17:10:57Z", "hours": 1.4833, "text": "Finally completed the code for writing on nfc stickers with the MFRC522. Started by modifying the code I made yesterday, but I realised that it just wasnt functional, so I scraped it and found a perfect tutorial on yt, that helped me understand how the coding of the MFRC522 works. By using the source code as a basis, I wrote a working code for writing a english word and, (in this instance) its german translation on a nfc sticker, (blocks 4&5). I am really happy with my progress today, and with what I learned today, I think writing the main LLH code will be easier."}, {"post_id": 58346, "ts": "2026-08-30T18:48:52Z", "hours": 1.5789, "text": "writing code for the llh in order for the llh to read information off the nfc stickers, the stickers should contain the information, in this case the words. I have coded before in c++, but this really had me stumped. I had to watch a couple of videos and do some research before understanding how most of the code for writing information works. I think that what I have coded could work, however I am not satisfied and will continue tomorrow. I also read that you should do something regarding authentication, which I have no idea how to do. All in all, I think today was really productive, since I learned how to kind of code for the MFRC522, more tomorrow"}, {"post_id": 57431, "ts": "2026-08-29T16:05:27Z", "hours": 0.4056, "text": "Started work on the LLH(Language learning helper) by designing the circuit. It consists of an esp32, connected to an MFRC522, which is a nfc/rfid reader. To write and read the words on the nfc tags that you stick on items. By clicking the button, the translation of the word in the foreign language should appear on the lcd i2c screen."}]...
|
Title: language learning helper (llh) by @tsellios Title: language learning helper (llh) by @tsellios | Stardance
Devlogs:
Started work on the LLH(Language learning helper) by designing the circuit. It consists of an esp32, connected to an MFRC522, which is a nfc/rfid reader. To write and read the words on the nfc tags that you stick on items. By clicking the button, the translation of the word in the foreign language should appear on the lcd i2c screen.
writing code for the llh in order for the llh to read information off the nfc stickers, the stickers should contain the information, in this case the words. I have coded before in c++, but this really had me stumped. I had to watch a couple of videos and do some research before understanding how most of the code for writing information works. I think that what I have coded could work, however I am not satisfied and will continue tomorrow. I also read that you should do something regarding authentication, which I have no idea how to do. All in all, I think today was really productive, since I learned how to kind of code for the MFRC522, more tomorrow
Finally completed the code for writing on nfc stickers with the MFRC522. Started by modifying the code I made yesterday, but I realised that it just wasnt functional, so I scraped it and found a perfect tutorial on yt, that helped me understand how the coding of the MFRC522 works. By using the source code as a basis, I wrote a working code for writing a english word and, (in this instance) its german translation on a nfc sticker, (blocks 4&5). I am really happy with my progress today, and with what I learned today, I think writing the main LLH code will be easier.
Started the main code for the llh Wrote the code that will read the words off the NFC stickers. I am pretty happy about the progress since this got done pretty fast. Tomorrow, I will complete the rest of the code (LDC, buttons).
I completed the main code for the llh today I basically completed the main code for the llh today, I was pretty pleased with the code I had written, until I compiled it and a lot of errors showed up. Most of them were just mistakes I made when writing the code. The rest was the lcd i2c library not working. Despite that, I think the code will work great and i am really proud. I will look into the i2c library tomorrow
redid the circuit in wokwi I needed to remake it since it was not properly saved. Now its time to make the case it cad which really scares me and so I researched a bit abt it.
Started working on the 3d case for the llh I had no idea where to start from, and to be honest, I was afraid to start. I watched a tutorial, that suggested openscad, which while seems cool, just didnt work for me. I instead chose onshape. While this thing ,might not look like much, it took me a fair while and i am really proud. Despite now having much time with school, i will try to finish the case within the week to finally ship. i hope ill get better at cad and make something that actually looks pleasing to the eye.
Made for progress on the case Today I added the esp and the mfrc552 in the sketch, (the lcd and the button I will have to do tomorrow). The size is kind of, funky. Once completed it will be 15 10cm (apprx. 6 4 inch.) and will be kind of flat, and with the addition of the handle, I am not sure how I will look holding the printed case irl. I also will have to consider stability and have to start thinking how to make the handle. Lastly, I need to consider how the power will be supplied, which is something I have given enough thought. I hope to get this done by Sunday, but we’ll see. I am kind of proud of myself.
Made significant progress on the case today I mapped out every other part and finally got it into the 3rd dimension. I decided that making threads was too hard for my first project, so I will make the holes a bit smaller than the screws, so that the will be able to screw on easily (hopefully). Additionally, I will need to add a hole on the side, since i decided to add a switch to turn it one and off.
Almost completed the case!!! Today I finished the bottom and top part of the case. Only thing left before this project is finished is adding a way to connect the 2 parts, adding the handle, and an opening for the switch. In contrast with how it looked yesterday, i am much more proud today. (almost done :))
FINALLY completed the case!! After a lot of work I finally completed the case for the llh. The project might be pretty much ready for funding. Although it is an issue, I guess, that the words can only be up to 16 characters (size of each block), I might find a way of doubling that tomorrow like using 2 blocks and that Ill submit it!!...
|
1793559362.6154528
|
1794164162.6154528
|
|
28998
|
lang by @aloe | Stardance
|
aloe
|
0
|
11.72
|
0
|
[]
|
[{"post_id": 20400, "ts": "202 [{"post_id": 20400, "ts": "2026-07-02T00:03:52Z", "hours": 3.3228, "text": "Basic types, generics, function calls, and nested identifiers Function calls are now parsed, and identifiers can be nested via dots and indices via brackets. I think I’ll have to reuse the same AST node used for function calls for enum fields carrying tuples when used in an expression other than enum itself. I got a headache thinking about the type system with generics. It probably would’ve been easier if I drew a diagram before trying to implement them into the AST and parser. I got there eventually. I have yet to add support for tuple and array types outside the AST interface/type definitions. Basic named types and generics are supported and parsed properly. I should probably move all my type definitions for the AST to a new file so I don’t have to keep scrolling past a couple hundred lines every time I need to reference them."}, {"post_id": 20075, "ts": "2026-07-01T16:22:10Z", "hours": 4.0131, "text": "Started AST and parser I’ve been referencing the parser guide for Easel . It’s been quite useful. I started working on this last night, but I got tired and paused without writing a journal. I made a git commit with the broken changes this morning. So far, I’ve implemented basic parsing for variable and function declarations, literals, tuples, and expressions. I spent quite a while trying to settle on values for operator precedence. I lost track of time testing things in the JS console and on the Rust playground website to see what made sense for precedence. Apparently 1..5==1..5 evaluates to 1..(5==1)..5 , and 1&1+1 evaluates to 1&(1+1) . Like JS, Rust treats += as an expression instead of a statement, but it evaluates to () every time. Looking at Go, it supports the ++ operator, but doesn’t allow it to be used inside an expression. Language design is odd, but I like how everything fits together."}, {"post_id": 19605, "ts": "2026-06-30T23:32:02Z", "hours": 4.3861, "text": "Initial blueprint, and a lexer. Before I wrote any code, I spent a while brainstorming features I wanted in this language. I wanted something with simple syntax and few keywords. There are currently 18 keywords. No keyword has more than four letters. I have yet to reserve names for types. I might stick with something similar to Rust for naming types. Declarations val Value (immutable). var Variable (mutable). fn enum I intend to support storing values inside, like Rust. obj Equivalent to a struct in Rust. type Type alias or an interface. ext Like an impl block in Rust. Conditional if else cmp Similar to Rust’s match statement. Flow ret Return. loop Overloaded loop operator. Go uses for, this uses loop. jmp Depending on context, this replaces continue and goto (though I intend to add constraints like Go for memory safety). drop Acts as a break statement, dropping out of a labeled loop or scope. May take a return value. Misc in Used for iteration. use Import. pub Export. del Manually delete a variable (free memory). I’m considering two more keywords for a macro system later on, but I’m not going to invest energy into that quite yet. For the sake of simplicity, there will be no :: operator . It will all be . . For type casting, I intend to use -> instead of adding another keyword. To keep the parser simple, I’m looking at using square brackets instead of angled brackets for type generics, like Go does. I’m still deciding. I intend to support function variadics with .. prefixing a parameter name. Like with Rust, labels will be prefixed by a single quote. I might change this. I wrote a lexer for this with a bit of hacky TypeScript and RegExp. Don’t ask why it’s in TypeScript. I’m pretty sure I was half-asleep when I started this the other day, and it shouldn’t matter in the long run. If I can get this to transpile to C or something, I’ll bootstrap it. For memory management, I don’t want a garbage collector. I don’t want Rust’s ownership system either. It would defeat the point of a simple language if you need to wrestle with the compiler so often. The current plan is to use RAII and manual freeing where needed. I’m considering an ARC hybrid with RAII or something later on, so memory management won’t be manual forever."}]...
|
Title: lang by @aloe | Stardance
Devlogs:
Initial Title: lang by @aloe | Stardance
Devlogs:
Initial blueprint, and a lexer. Before I wrote any code, I spent a while brainstorming features I wanted in this language. I wanted something with simple syntax and few keywords. There are currently 18 keywords. No keyword has more than four letters. I have yet to reserve names for types. I might stick with something similar to Rust for naming types. Declarations val Value (immutable). var Variable (mutable). fn enum I intend to support storing values inside, like Rust. obj Equivalent to a struct in Rust. type Type alias or an interface. ext Like an impl block in Rust. Conditional if else cmp Similar to Rust’s match statement. Flow ret Return. loop Overloaded loop operator. Go uses for, this uses loop. jmp Depending on context, this replaces continue and goto (though I intend to add constraints like Go for memory safety). drop Acts as a break statement, dropping out of a labeled loop or scope. May take a return value. Misc in Used for iteration. use Import. pub Export. del Manually delete a variable (free memory). I’m considering two more keywords for a macro system later on, but I’m not going to invest energy into that quite yet. For the sake of simplicity, there will be no :: operator . It will all be . . For type casting, I intend to use -> instead of adding another keyword. To keep the parser simple, I’m looking at using square brackets instead of angled brackets for type generics, like Go does. I’m still deciding. I intend to support function variadics with .. prefixing a parameter name. Like with Rust, labels will be prefixed by a single quote. I might change this. I wrote a lexer for this with a bit of hacky TypeScript and RegExp. Don’t ask why it’s in TypeScript. I’m pretty sure I was half-asleep when I started this the other day, and it shouldn’t matter in the long run. If I can get this to transpile to C or something, I’ll bootstrap it. For memory management, I don’t want a garbage collector. I don’t want Rust’s ownership system either. It would defeat the point of a simple language if you need to wrestle with the compiler so often. The current plan is to use RAII and manual freeing where needed. I’m considering an ARC hybrid with RAII or something later on, so memory management won’t be manual forever.
Started AST and parser I’ve been referencing the parser guide for Easel . It’s been quite useful. I started working on this last night, but I got tired and paused without writing a journal. I made a git commit with the broken changes this morning. So far, I’ve implemented basic parsing for variable and function declarations, literals, tuples, and expressions. I spent quite a while trying to settle on values for operator precedence. I lost track of time testing things in the JS console and on the Rust playground website to see what made sense for precedence. Apparently 1..5==1..5 evaluates to 1..(5==1)..5 , and 1&1+1 evaluates to 1&(1+1) . Like JS, Rust treats += as an expression instead of a statement, but it evaluates to () every time. Looking at Go, it supports the ++ operator, but doesn’t allow it to be used inside an expression. Language design is odd, but I like how everything fits together.
Basic types, generics, function calls, and nested identifiers Function calls are now parsed, and identifiers can be nested via dots and indices via brackets. I think I’ll have to reuse the same AST node used for function calls for enum fields carrying tuples when used in an expression other than enum itself. I got a headache thinking about the type system with generics. It probably would’ve been easier if I drew a diagram before trying to implement them into the AST and parser. I got there eventually. I have yet to add support for tuple and array types outside the AST interface/type definitions. Basic named types and generics are supported and parsed properly. I should probably move all my type definitions for the AST to a new file so I don’t have to keep scrolling past a couple hundred lines every time I need to reference them....
|
1792929067.63588
|
1793793067.63588
|
|
44855
|
landinhere by @Amna-s | Stardance
|
Amna-s
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: landinhere by @Amna-s | Stardance
|
1793300014.7829163
|
1793904814.7829163
|
|
4485
|
lander game by @dale | Stardance
|
dale
|
0
|
6.14
|
0
|
[]
|
[{"post_id": 3996, "ts": "2026 [{"post_id": 3996, "ts": "2026-06-07T04:20:24Z", "hours": 0.9672, "text": "Fixed stars and scrollbar bugs What I fixed: star,radius typo causing stars not to render Stars bunching in the corner before canvas resize White scrollbars around the edge with CSS What I added: Full screen starfield with 500 stars Changed lander color to white"}, {"post_id": 3238, "ts": "2026-06-06T02:11:07Z", "hours": 2.0525, "text": "The lander can now be flown around the page with veloicty and engine flame!!"}, {"post_id": 2601, "ts": "2026-06-05T06:45:49Z", "hours": 1.6419, "text": "Made the shape of the lander"}, {"post_id": 1923, "ts": "2026-06-04T04:58:33Z", "hours": 1.085, "text": "made a red square using a canvas"}, {"post_id": 1029, "ts": "2026-06-02T20:21:45Z", "hours": 0.3928, "text": "lander game says hello world"}]...
|
Title: lander game by @dale | Stardance
Devlogs:
Title: lander game by @dale | Stardance
Devlogs:
lander game says hello world
made a red square using a canvas
Made the shape of the lander
The lander can now be flown around the page with veloicty and engine flame!!
Fixed stars and scrollbar bugs What I fixed: star,radius typo causing stars not to render Stars bunching in the corner before canvas resize White scrollbars around the edge with CSS What I added: Full screen starfield with 500 stars Changed lander color to white...
|
1793382899.567928
|
1793987699.567928
|
|
4157
|
lander by @mahmoud | Stardance
|
mahmoud
|
1
|
4.0
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-08-30T07:30:43Z", "hours": 4.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "My first terminal games in raw C++, and also my first interaction with ASCII art. I worked on this one 3 months ago then I forgot it, so I will just ship it anyway 😭", "repo": "https://github.com/mahmuudsarhan/lander", "demo": "https://mahmuudsarhan.itch.io/lander"}]...
|
[{"post_id": 1028, "ts": "2026 [{"post_id": 1028, "ts": "2026-06-02T20:20:34Z", "hours": 2.2372, "text": "Added a fuel burn animation to look explosive, (assuming your definition of “explosive” is flashing punctuation marks) The window now auto-maximizes on launch 3.Cleaned up the math loops so the game logic doesn’t break NOTE: It is definitely not the most visually stunning game in the world, but I hope you enjoy trying to beat it ¯ _ (ツ)_/¯"}, {"post_id": 694, "ts": "2026-06-02T08:06:50Z", "hours": 2.0036, "text": "A terminal game where you control a spacecraft to land safely on the moon, just finished the core logic and will start adding animation"}]...
|
Title: lander by @mahmoud | Stardance
Devlogs:
A Title: lander by @mahmoud | Stardance
Devlogs:
A terminal game where you control a spacecraft to land safely on the moon, just finished the core logic and will start adding animation
Added a fuel burn animation to look explosive, (assuming your definition of “explosive” is flashing punctuation marks) The window now auto-maximizes on launch 3.Cleaned up the math loops so the game logic doesn’t break NOTE: It is definitely not the most visually stunning game in the world, but I hope you enjoy trying to beat it ¯ _ (ツ)_/¯
Ships:
My first terminal games in raw C++, and also my first interaction with ASCII art. I worked on this one 3 months ago then I forgot it, so I will just ship it anyway 😭...
|
1793652535.9377685
|
1793738935.9377685
|
|
72657
|
lalala by @jeyanissi | Stardance
|
jeyanissi
|
0
|
0.0
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0
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[]
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[]
|
Title: lalala by @jeyanissi | Stardance
|
1793555228.2260575
|
1794160028.2260575
|
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65748
|
lala by @0ceanmp4 | Stardance
|
0ceanmp4
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0
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0.0
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0
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[]
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[]
|
Title: lala by @0ceanmp4 | Stardance
|
1793091049.1345403
|
1793695849.1345403
|
|
1850
|
ladybug dreams by @ladybug | Stardance
|
ladybug
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: ladybug dreams by @ladybug | Stardance
|
1793134159.3091574
|
1793738959.3091574
|
|
53379
|
ladybug bluff by @misbahgauri9 | Stardance
|
misbahgauri9
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: ladybug bluff by @misbahgauri9 | Stardance
|
1793483761.2254286
|
1794088561.2254286
|
|
53380
|
ladybug bluff by @misbahgauri9 | Stardance
|
misbahgauri9
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: ladybug bluff by @misbahgauri9 | Stardance
|
1793483762.1920571
|
1794088562.1920571
|
|
53381
|
ladybug bluff by @misbahgauri9 | Stardance
|
misbahgauri9
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: ladybug bluff by @misbahgauri9 | Stardance
|
1793483764.4958055
|
1794088564.4958055
|
|
43858
|
lacorte.city by @lacorte | Stardance
|
lacorte
|
1
|
5.0
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-08-04T21:08:26Z", "hours": 5.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "lacorte.city is my personal website i rebuilt from scratch with an oldschool aesthetic and 88×31 badges. the site has i18n for english+ptbr, an rss feed and blog posts that can be written in markdown delivering automated structured data for search engine optimization. live: https://lacorte.city repo: https://github.com/Gabriel-Lacorte/lacorte.city a.i helped to review and find gaps in my architecture, but all design decisions, typography choices, and code were written by hand.", "repo": "https://github.com/Gabriel-Lacorte/portfolio", "demo": "https://lacorte.city"}]...
|
[{"post_id": 40842, "ts": "202 [{"post_id": 40842, "ts": "2026-08-04T17:01:10Z", "hours": 4.8739, "text": "the last couple of days, i reworked my portfolio whole visual identity and gave it an oldschool style, inspired by some references from neocities.org. i wanted the design to feel more personal and memorable, an style i already explored before in my old website (lacorte.neocities.org)."}]...
|
Title: lacorte.city by @lacorte | Stardance
Devlo Title: lacorte.city by @lacorte | Stardance
Devlogs:
the last couple of days, i reworked my portfolio whole visual identity and gave it an oldschool style, inspired by some references from neocities.org. i wanted the design to feel more personal and memorable, an style i already explored before in my old website (lacorte.neocities.org).
Ships:
lacorte.city is my personal website i rebuilt from scratch with an oldschool aesthetic and 88×31 badges. the site has i18n for english+ptbr, an rss feed and blog posts that can be written in markdown delivering automated structured data for search engine optimization. live: https://lacorte.city repo: https://github.com/Gabriel-Lacorte/lacorte.city a.i helped to review and find gaps in my architecture, but all design decisions, typography choices, and code were written by hand....
|
1792878670.3265443
|
1793742670.3265443
|
|
36925
|
l by @Zayaren | Stardance
|
Zayaren
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: l by @Zayaren | Stardance
|
1793540951.6888266
|
1794145751.6888266
|
|
25840
|
kynotif by @kybe | Stardance
|
kybe
|
0
|
2.97
|
0
|
[]
|
[{"post_id": 15841, "ts": "202 [{"post_id": 15841, "ts": "2026-06-25T19:13:47Z", "hours": 2.9658, "text": "implemented basic notification rendering in pure wayland"}]...
|
Title: kynotif by @kybe | Stardance
Devlogs:
impl Title: kynotif by @kybe | Stardance
Devlogs:
implemented basic notification rendering in pure wayland...
|
1793371962.5465324
|
1793976762.5465324
|
|
12386
|
kurama by @prince07 | Stardance
|
prince07
|
0
|
0.0
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0
|
[]
|
[]
|
Title: kurama by @prince07 | Stardance
|
1793163222.2875333
|
1793768022.2875333
|
|
66
|
kura by @kuratus | Stardance
|
kuratus
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: kura by @kuratus | Stardance
|
1793461998.0917003
|
1794066798.0917003
|
|
40742
|
kubeqnasa by @kubeqnasa | Stardance
|
kubeqnasa
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: kubeqnasa by @kubeqnasa | Stardance
|
1793519560.5283518
|
1794124360.5283518
|
|
56814
|
krzbot by @Krzysztof | Stardance
|
Krzysztof
|
1
|
1.0
|
0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-08-31T16:15:45Z", "hours": 1.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "Its simple slack bot that has /krzbot-ask-ai which sends a request to gemini using ai.hackclub.com, /krzbot-tell-joke that tells random joke from a list and /krzbot-whether where you add city and it shows u info using open-meteo.com", "repo": "https://github.com/krzkawa/slack-bot", "demo": "https://hackclub.enterprise.slack.com/archives/C0P5NE354"}]...
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[{"post_id": 59004, "ts": "202 [{"post_id": 59004, "ts": "2026-08-31T16:10:49Z", "hours": 1.2164, "text": "I wrote whole code"}]...
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Title: krzbot by @Krzysztof | Stardance
Devlogs:
Title: krzbot by @Krzysztof | Stardance
Devlogs:
I wrote whole code
Ships:
Its simple slack bot that has /krzbot-ask-ai which sends a request to gemini using ai.hackclub.com, /krzbot-tell-joke that tells random joke from a list and /krzbot-whether where you add city and it shows u info using open-meteo.com...
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1792860590.3859637
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1793724590.3859637
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