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Here’s the result of my second run with Codex. The first run turned a reference image into an interactive 3D container-terminal simulation. This time, I asked Codex to audit the system in depth, suggest improvements, and implement them. Harbor now includes: - An experiment lab for saving runs and... comparing scenarios against a baseline - Repeatable experiments with matched random seeds across scenarios - Timeline replay and branching, so you can rewind, change settings, and explore a different outcome - Individual container tracking, with a journey history from ship to yard - Yard-crane capacity, queues, and shared-road reservations - Diagnostics showing why cranes and vehicles are waiting You can test whether adding vehicles actually improves throughput, see where queues build up, and compare the results of different operating settings. You can also return to an earlier point in a run, change your decisions, and save the new result for comparison. The second pass also improved the rendering, controls, and layout, with clearer cargo stages and completion milestones.show more

Junho Yeo

3,211 subscribers

17,986 görüntüleme • 1 ay önce •via X (Twitter)

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Veyra | AI & Tech profil fotoğrafı

Veyra | AI & Tech1 ay önce

Timeline replay and branching for terminal ops is genius

Vera Ai | Tools & Updates profil fotoğrafı

Vera Ai | Tools & Updates1 ay önce

That second pass turns a prototype into a genuinely useful simulation lab

Sehan @ Zyner profil fotoğrafı

Sehan @ Zyner1 ay önce

So in real world do we have to have GPS and other trackers connected to these vehicles, machines and etc?

Joachim Ferdinand profil fotoğrafı

Joachim Ferdinand1 ay önce

This is nice

Botanium profil fotoğrafı

Botanium1 ay önce

Can you share the prompts and tools and skills you have used?

Junho Yeo profil fotoğrafı

Junho Yeo1 ay önce

For this demo, I just used the ChatGPT web chat

Coffee Cat profil fotoğrafı

Coffee Cat1 ay önce

让 agent 审自己的系统，有个隐藏风险：它审的是「它理解的系统」，不是你线上跑的那个。我的做法是先让它输出一份它以为的架构图，人先对一遍——图错了，后面所有改进建议都是空中楼阁。

Vinicius Gehlen profil fotoğrafı

Vinicius Gehlen1 ay önce

What is the prompt and models you have used? Any external mcps?

Junho Yeo profil fotoğrafı

Junho Yeo1 ay önce

nothing

DreW profil fotoğrafı

DreW1 ay önce

Woah

dualtron.uk profil fotoğrafı

dualtron.uk1 ay önce

what did you use to improve rendering + controls

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New stuff you can do in Spline v2: Building a TSL material with texture atlases was surprisingly easy > A little 2D samurai running around. I gave Claude a 2D sprite sheet of a and asked it to generate the atlases, and the agent in Spline took care of writing a shader that runs the loop at the right speed and binds it all to the keyboard. An old-school game with the advantages of 3D. Super promising. This is really just the basics here (an Idle and a Run state) but you can add jumps and build on it.

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this is getting f*cking dangerous: Claude Code agents can turn a stack of research papers into a lab u can run right in ur browser i made $3,650 overnight with this approach Boris Cherny, the creator of Claude Code, gave a dozen agents 64 research papers and asked them to build a platform where anyone could reproduce the physics experiments themselves u open a fluid simulation, change the conditions and immediately see how the flow changes while the experiment is running, u can switch algorithms, open the formulas and inspect the code calculating what happens on screen so u take a complicated paper sitting in ur “i’ll read this someday” folder and get something u can actually play with each agent got its own job: → analysts extract formulas, assumptions and experimental conditions from the papers → developers turn them into working models → reviewers compare the results against the original research → separate agents build controls for each scene and this is where it gets interesting the fluid can look beautiful while the calculations underneath are completely broken. u might never notice just by watching so reviewers check whether mass is conserved, whether changing parameters breaks the calculations and whether the results match the paper’s data next to each experiment, u can see: what’s being tested which values are being used how far the result differs from the original what still needs checking the write-up describes 11 approaches and 28 test scenes. seven approaches passed within acceptable tolerances, while four needed more work i borrowed this way of organizing the work for my FOMOBILL: breaking down how memecoin buys and sells work so i can check what wallets did after entering, before making my own trade the physicists have the original paper. i have the original transaction i can open and verify if u wanna try this approach, upload ur materials to Claude Code and give it this task: “Turn these materials into an interactive tool: 1. Extract the algorithms, rules and testing parameters. Cite the sources and flag missing details 2. Assign separate parts to independent agents. Use the same input data for comparisons 3. Set up independent checks of the results. Log errors and visibly label anything unverified 4. Build an interface where users can change parameters, compare results and inspect the source code” start with one document and one testable example. scaling the team is easier once the first result can be reproduced save the dependencies and source data so someone else can run the project too my overnight result was paper trading; execution and results can differ with real money lyrics breaks down the full approach and how im applying it in FOMOBILL in the article below ↓

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Attacking civs can result in them getting the attention of the police. They can also run to a phone and call for help. Assaulting police officers can result in them calling for backup.

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You can run Claude inside a CoreWeave Sandbox and drive it from your phone. The agent gets a custom container image with your tools and MCPs, plus Slurm access and the ability to set your network policy. The sandbox doesn't care what the workload is. That's the point.

You can run Claude inside a CoreWeave Sandbox and drive it from your phone. The agent gets a custom container image with your tools and MCPs, plus Slurm access and the ability to set your network policy. The sandbox doesn't care what the workload is. That's the point.

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10,959 görüntüleme • 3 ay önce