Everyday Unity
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A game developer and tech lead in a top grossing company posting Unity, programming, and gamedev related stuff that I find interesting Website: https://gamedev.center Most used tags are: #performance #shader #interview Author: @alexmtr
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频道帖子
How Claude Code Uses Prompt Caching
I believe it's important to know what prompt caching is and how it helps save costs.
On this page, I would pay attention to what resets the cache, how agents affect it, how to check your cache usage, and TTL.
One advice I didn't follow before:
Compaction works in your favor when the context you discard is content you no longer need. To choose when its overhead happens, run /compact at a natural break in your work, such as between tasks, instead of waiting for auto-compaction to trigger mid-task. If you’ve gone down a path you want to abandon entirely, /rewind to an earlier turn instead. Rewinding truncates back to a prefix that is already cached, rather than building a new one as compaction does.https://code.claude.com/docs/en/prompt-caching #ai
| 2 |  Meet the Unity CLI: manage Unity from your terminal
I had multiple posts about how I used godot because of great cli tools and now its time to test if Unity can match it. Seems like it doesn't have a lot of stuff yet, but it allows agents to eval any code without full recompilation and domain reload. So in theory agents can do any custom work with this command.
Has anyone tested it already?
https://unity.com/blog/meet-the-unity-cli
#cli | 330 |
| 3 |  I transitioned my roguelike game from 2D to 3D to test Sol Ultra when it was released 1.5 weeks ago.
I def can say it was a successful experiment. The game was working, but lacked a few animations I had before.
I initially used original sprites as billboards in 3D world, but then eventually swapped it with very simple models. The game transformed from a simple 2d board to a stylized 3d after I threw in a few shaders and post effects.
And of course the game again became slower to load.
So I ran the same profiling with tracy and got the faster loading in just 5 mins.
Cannot recommend it more. | 331 |
| 4 |  Just now Open AI temporarily removed the 5h limit.
It's an interesting addition to the morning discussion we had here about hitting the 5h limit with sol ultra in 18-40 mins.
I hit the 5h limit twice today and have only 32% of a weekly limit left. Thanks Open AI, now I can spend my weekly limit in around 1.5 hours 💪💀 | 566 |
| 5 | I have been testing 5.6 Sol lately and haven't seen a really big difference to the old model when I used it with medium, high, extra high effort.
The only thing that surprised me was a co-op bot for my roguelike game. You press a bot run button on the host and it runs kinda optimal strategy and plays the game from all clients. It was done in around 2 prompts and works very well.
I was able to catch around 6 bugs already with it.
Then I added auto mode for LLM, it launches multiple clients each with their own set of launch args. And then LLM reads the console every 5 mins for each client to find anomalies or bugs. It also found a few bugs which led to an incorrect loss.
Apart from that other tasks were the same in terms of speed and quality as 5.5.
This morning I wanted to test 5.6 ultra and compare it against Fable 5, which I used at work to create a pretty big feature on which it worked for 2 days straight with pauses when it was hitting the 5 hour limit of $200 subscription.
So I selected ultra effort, started to write a prompt and then I saw the new update available. It must make things better, right?
I hit it, codex restarted, and the ultra mode is now gone 💀
Do you still have ultra effort on the latest codex version?
And have you tested it against Fable? Which one is better for you?
Drop 💯 if you want to hear more about my Fable experience and how it completed the feature in 2 days on its own. | 543 |
| 6 | 12-Factor Agents for development workflows
It is mostly a guide, not a library you install and build your game on top of. There are some supporting packages and workshops in the repo, but the core value is the principles for building reliable agents.
The guide pushes against the "big prompt + tools + loop until done" approach.
I have been using AI coding workflows for multiple years already and that's the part where things usually break on big project. It might work for a demo or prototype. But in real Unity projects with long import times, slow build pipelines, and old god singletons no one wants to touch, suddenly LLM even with agents needs logs, state, approvals, retries, and boring deterministic scripts and tools instead of a magic AI button.
Few points I would steal for my game dev agents:
Own the prompts.
If an agent works on my project, I don't want the important prompt hidden inside a framework. I want it in the repo near requirements, diagrams, and maybe even next to scripts it can call. Same reason I like PlantUML: it can be reviewed, changed, reused.
Tools are just structured outputs.
"Run tests" should call a script. "Build WebGL" should call a script. "Check Addressables" should call a script. The LLM can choose what to try next, but it should not invent whether the build succeeded. Deterministic code should return the result.
Pause when action is risky.
An agent can prepare a PR, but I don't want it to push to master or upload a public build without explicit approval. Same for deleting assets, migrations, changing live configs, save compatibility, etc. It might sound obvious, but a lot of agent demos skip exactly this boring part.
Keep the state inspectable.
When an agent fails and retries, I want to see why. Unity has enough "works on my machine" mystery already. If the agent changed a prefab, fixed one error, then broke another platform, I need a history that can be inspected later.
Make agents small.
One agent for "prepare playable build" is okay. One for "investigate this crash report" is okay. A single agent that can modify code, assets, configs, CI, store metadata, and production data is a nice way to lose control. However I am wondering how many tokens can be wasted if there are too many small agents for each small step. Something I would like to test.
Of course, the repo is written mostly from SaaS/product experience, not Unity production. But I think the principles fit game dev really well, because our pipelines are slow, stateful, full of tools, and full of things that should not be changed by "vibes".
I am using my agent team at work daily and already modified it a few times based on the experience. Today I updated it according to 12-factor-agents principles, lets see if it yields better results or just turns into a bigger token drain with no significant benefits.
Have you already built any agent around your game project workflow? Not just coding in Cursor/Claude, but something that runs tests, checks logs, prepares builds, or validates assets?
My unity agents:
https://github.com/AlexMerzlikin/unity-agent-team
12 factor agents:
https://github.com/humanlayer/12-factor-agents
#agent | 436 |
| 7 | Since May I have been working on a roguelike prototype, first in Three.js and now in Godot.
I started with Three.js because it was the fastest way to check the idea. After a small playtest with my friends, when I verified that it is fun at least for me in coop, I decided to move it to a real engine. I picked Godot, even though it is my first game with it.
And then I saw a long loading time.
Of course, the first temptation is to ask an LLM to "optimize the game" and hope for magic. But the better loop is still the old reliable one: profile first, then optimize if needed.
I checked the docs and found that Godot can be connected to Tracy. So I fed the docs to Codex and in one prompt it:
- downloaded Tracy
- set it up for the project
- made a capture
- analyzed the result
- proposed fixes
Then I asked it to apply the fixes, run a review with my functionality reviewer agent, and profile with Tracy again.
The biggest visible win was exiting the game to the lobby. Before it took around 3-5 seconds. Now it is basically immediate.
The complete result is in the pic
This is not a "LLM solved performance" story. More like: LLM made the profiling loop cheaper and faster.
Have you already used LLMs together with real profilers, not just for random code cleanup?
Give 🔥 if you want to hear what it was like for me to port the game from Three.js to Godot.
#performance #profiling #godot #tracy | 457 |
| 8 |  没有文字... | 459 |
| 9 | Antigravity 2.0 update after a small real test.
I finished 2 small tasks on my relatively small prototype with it. Nothing huge: 2 PRs, around +250 and +50 lines of code, with code review by 4 agents. Gemini 3.5 high.
The result was useful, but the cost in limits was not that inspiring: around 80% of the 5h limit used on the $20 Google AI Pro subscription.
It feels close to the painful Claude limits problem. And ngl, Antigravity limits were already very unclear and a sad experience for me in the past. First it looked like only 5h limits, then after reaching it a few times it changed to weekly limits. What is more, those weekly limits were updating to 1 more week when I was almost near the weekly reset, even without using Antigravity. Happened multiple times in a row until I stopped even checking it.
Of course, this is not a benchmark. Just one small evening with a small prototype. But for game dev prototypes, predictable limits matter a lot. If the tool stops exactly when you found the flow, it becomes hard to trust it as a real part of the workflow.
Will keep using it a bit and update whether this part is fixed or not.
Have you tried Antigravity 2.0 already? Are the limits clear for you? | 447 |
| 10 |  +1Find 5 differences | 440 |
| 11 | I switched to Codex a while ago because Claude limits were brutal for my workflow.
Not even coding at first. I was hitting the 5h limit after 4-5 prompts about my GDD. For a small prototype. Opus was basically no-go for me, and Sonnet was useful, but not producing the same level of results for the work I needed.
Then Codex mobile landed, and it closed the only big gap in my workflow. I could continue the same "write from phone, let the agent work on desktop" loop I had before, but inside Codex.
My current experience:
$20 subscription was already enough for steady progress.
I finished more tasks than before, especially smaller prototype tasks and planning cleanups.
For active weekend development I moved to the $100 plan.
So far I am not even close to limits. I don't know if this would survive full-time work, but for weekend projects it is more than enough for me.
Claude might be better now, but I haven't re-tested it yet.
I heard Anthropic increased limits on their subs, so take my comparison with a grain of salt. My old frustration may already be outdated.
Antigravity is the interesting competitor now.
I tried the new Antigravity 2.0 after Google I/O, and the shape is very familiar - basically Codex-like agent work, but without the mobile access I rely on. I need to test it more, because Gemini 3.5 Flash might be strong enough to make the tradeoff less obvious.
For game dev specifically, mobile access became much more important than I expected. It lets me keep momentum when I have a small pocket of time, and for hobby projects momentum is often the bottleneck, not raw model benchmark score.
What do you use nowadays? | 421 |
| 12 | A follow-up on my /grill-me post from last week.
After using it for about 7 days, a few observations.
It asks a lot more questions than /brainstorming. Like, significantly more. I had one session with 60 questions, and I was answering them for 1.5 hours. The original task was pretty small initially.
But the result? Complete set of requirements, implementation came out bug-free, following the existing project architecture. So it was time-consuming but very effective.
After a few more tasks like this I changed the skill to "self-grill". Now the AI asks all those questions itself and gives me a decision list in seconds. I just scan the decisions, adjust what looks wrong, and proceed.
Of course the effectiveness is lower compared to going through the full /grill-me flow properly. But for most tasks it is a much better trade-off from a time-result balance perspective.
If I had to frame it: /grill-me is worth it when scope is unclear and getting it wrong is expensive. Self-grill is for everything else.
Have you tried building requirements this way before coding? I am curious how others are managing the thoroughness-vs-speed trade-off in their AI workflows.
#ai | 675 |
