Using ChatGPT to Create the “Perfect Dirt/Erode Preset”
Posted: Sun Aug 17, 2025 8:23 pm
Using ChatGPT to Create the “Perfect Dirt/Erode Preset” in MX Simulator
Hello!
I wanted to share a really unique experience I’ve had recently while working on my track in MX Simulator. As most of you know, dialing in tileinfo can be a pretty frustrating process. You have dozens of settings to play with, and it’s not always obvious what numbers will give you the feel you’re after. For me, friction and erode are the two biggest pieces that make or break how fun a track is to ride.
I decided to take a different approach: I brought ChatGPT (AI) into the process to help me design and refine a completely new traction/erode preset. After a lot of back-and-forth — and a lot of testing — I ended up with what I’m calling my “Perfect Dirt/Erode Preset.” It feels completely unique compared to the usual stuff, and honestly, I don’t think I could have gotten here without the help of AI.
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1) Teaching ChatGPT About Tileinfo
The first thing I did was feed ChatGPT the forum post that explains tileinfo in detail. I wanted to make sure it fully understood how friction and erode actually work in MX Sim.
Once it was clear that it could explain back to me what each setting does, I started describing what I wanted the dirt to feel like — not just numbers, but actual rider feedback:
“I want the dirt to feel tacky and supportive, like you can just lean the bike and trust it.”
“I don’t want it slick anywhere, but I don’t want it so grippy that you’re wheelying everywhere.”
“I want the ruts to form skinny and deep, but flowy — not choppy or bumpy.”
“When I rail a corner, I want the berm to actually build up taller so I can lean more into it.”
The cool part was that ChatGPT was able to take those plain-language descriptions and convert them into usable tileinfo values.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
2) Iterating and Refining the Feel
The first few friction curves it gave me were close, but not quite what I was looking for.
I’d test them in-game and then give feedback like:
“This one feels too slick mid-corner.”
“I want the dirt to be more consistent at different speeds.”
“It feels good wide open, but I’m still sliding out when I roll on the throttle slow.”
Each time, ChatGPT adjusted the numbers just slightly — tightening the friction spread, making the traction more supportive, smoothing how the grip transitioned across slip speeds.
The same went for erosion. At first, it was forming ruts too wide or too shallow. I told it: “I want the rut to be skinny, deeper, and the berm to build taller on the outside.” It tweaked erode_depth, erode_displacement, and erode_lateral_scale until the results matched what I was describing.
This back-and-forth process was honestly the most fun I’ve had working on traction. Instead of blindly guessing numbers, I was basically “coaching” the AI with how the dirt should feel, and it gave me the numbers to make that happen.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3) The Final Result: "Perfect Dirt/Erode Preset"
After refining and testing, I ended up with a traction/erode combo that I absolutely love. It’s unique, supportive, tacky, but not over-grippy. The erosion makes ruts build naturally and berms form with flow, instead of making the track unrideable.
Here’s the final preset if you want to try it yourself:
name Perfect Dirt/Erode Preset
friction 1.20 0.0
friction 1.19 0.5
friction 1.18 1.0
friction 1.17 2.0
friction 1.17 3.5
friction 1.16 5.0
friction 1.15 7.0
friction 1.14 10.0
roll_resist 52.0 77.0 37.0
roll_resist 62.0 87.0 47.0
erode_depth 5.50
erode_displacement 3.17
erode_radius 3.17
erode_inner_depth 3.17
erode_inner_radius 2.5
erode_lower 35.0
erode_upper 125.0
erode_off_speed 8.0
erode_on_speed 14.0
erode_slip_base_scale 1.0
erode_slip_scale 1.08
erode_slip_lower 0.0
erode_slip_upper 4.0
erode_min_slope -0.4
erode_max_slope 0.5
erode_project_to_ground 1.0
erode_downhill_scale 0.0
erode_front_scale 0.80
erode_lateral_scale 2.8
erode_limit 0.0 1.0 1.0
erode_limit 0.4 0.95 0.95
erode_limit 0.75 0.75 0.75
erode_limit 1.0 0.55 0.55
Copy/paste that into your tileinfo and give it a try.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
4) Why This Is Exciting
What makes this so exciting to me is that it shows how AI can help evolve MX Sim in ways we haven’t explored yet. Normally, getting traction right is hours (or days) of guesswork. But by using ChatGPT, I was able to shortcut a lot of that — not by skipping testing, but by making each test meaningful.
I’d ride, describe what I felt, and get back new numbers that directly addressed that feedback. The end result wasn’t just faster — it was better than what I could have done alone.
And honestly? This “Perfect Dirt/Erode Preset” feels like nothing else I’ve ridden in the game before. It’s unique, fun, and makes riding aggressive lines feel incredible.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
5) Final Thoughts
If you’ve been hesitant to mess with tileinfo, I really recommend giving it a shot. And if you’re open to experimenting, try involving AI in your workflow. For me, it turned what’s normally a frustrating trial-and-error process into a creative collaboration.
I think this is just the start. Imagine using AI not only for traction, but also for designing realistic erode profiles, tuning suspension to match surfaces, or even helping brainstorm track layouts. It’s a tool that can help push MX Sim forward in really exciting ways.
So yeah — that’s my story. AI helped me create a traction setup that I’m genuinely stoked on, and I think this kind of experimentation could open up a lot of possibilities for the community.
Would love to hear your thoughts if you give the preset a try.
– Cody B
Hello!
I wanted to share a really unique experience I’ve had recently while working on my track in MX Simulator. As most of you know, dialing in tileinfo can be a pretty frustrating process. You have dozens of settings to play with, and it’s not always obvious what numbers will give you the feel you’re after. For me, friction and erode are the two biggest pieces that make or break how fun a track is to ride.
I decided to take a different approach: I brought ChatGPT (AI) into the process to help me design and refine a completely new traction/erode preset. After a lot of back-and-forth — and a lot of testing — I ended up with what I’m calling my “Perfect Dirt/Erode Preset.” It feels completely unique compared to the usual stuff, and honestly, I don’t think I could have gotten here without the help of AI.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
1) Teaching ChatGPT About Tileinfo
The first thing I did was feed ChatGPT the forum post that explains tileinfo in detail. I wanted to make sure it fully understood how friction and erode actually work in MX Sim.
Once it was clear that it could explain back to me what each setting does, I started describing what I wanted the dirt to feel like — not just numbers, but actual rider feedback:
“I want the dirt to feel tacky and supportive, like you can just lean the bike and trust it.”
“I don’t want it slick anywhere, but I don’t want it so grippy that you’re wheelying everywhere.”
“I want the ruts to form skinny and deep, but flowy — not choppy or bumpy.”
“When I rail a corner, I want the berm to actually build up taller so I can lean more into it.”
The cool part was that ChatGPT was able to take those plain-language descriptions and convert them into usable tileinfo values.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
2) Iterating and Refining the Feel
The first few friction curves it gave me were close, but not quite what I was looking for.
I’d test them in-game and then give feedback like:
“This one feels too slick mid-corner.”
“I want the dirt to be more consistent at different speeds.”
“It feels good wide open, but I’m still sliding out when I roll on the throttle slow.”
Each time, ChatGPT adjusted the numbers just slightly — tightening the friction spread, making the traction more supportive, smoothing how the grip transitioned across slip speeds.
The same went for erosion. At first, it was forming ruts too wide or too shallow. I told it: “I want the rut to be skinny, deeper, and the berm to build taller on the outside.” It tweaked erode_depth, erode_displacement, and erode_lateral_scale until the results matched what I was describing.
This back-and-forth process was honestly the most fun I’ve had working on traction. Instead of blindly guessing numbers, I was basically “coaching” the AI with how the dirt should feel, and it gave me the numbers to make that happen.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3) The Final Result: "Perfect Dirt/Erode Preset"
After refining and testing, I ended up with a traction/erode combo that I absolutely love. It’s unique, supportive, tacky, but not over-grippy. The erosion makes ruts build naturally and berms form with flow, instead of making the track unrideable.
Here’s the final preset if you want to try it yourself:
name Perfect Dirt/Erode Preset
friction 1.20 0.0
friction 1.19 0.5
friction 1.18 1.0
friction 1.17 2.0
friction 1.17 3.5
friction 1.16 5.0
friction 1.15 7.0
friction 1.14 10.0
roll_resist 52.0 77.0 37.0
roll_resist 62.0 87.0 47.0
erode_depth 5.50
erode_displacement 3.17
erode_radius 3.17
erode_inner_depth 3.17
erode_inner_radius 2.5
erode_lower 35.0
erode_upper 125.0
erode_off_speed 8.0
erode_on_speed 14.0
erode_slip_base_scale 1.0
erode_slip_scale 1.08
erode_slip_lower 0.0
erode_slip_upper 4.0
erode_min_slope -0.4
erode_max_slope 0.5
erode_project_to_ground 1.0
erode_downhill_scale 0.0
erode_front_scale 0.80
erode_lateral_scale 2.8
erode_limit 0.0 1.0 1.0
erode_limit 0.4 0.95 0.95
erode_limit 0.75 0.75 0.75
erode_limit 1.0 0.55 0.55
Copy/paste that into your tileinfo and give it a try.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
4) Why This Is Exciting
What makes this so exciting to me is that it shows how AI can help evolve MX Sim in ways we haven’t explored yet. Normally, getting traction right is hours (or days) of guesswork. But by using ChatGPT, I was able to shortcut a lot of that — not by skipping testing, but by making each test meaningful.
I’d ride, describe what I felt, and get back new numbers that directly addressed that feedback. The end result wasn’t just faster — it was better than what I could have done alone.
And honestly? This “Perfect Dirt/Erode Preset” feels like nothing else I’ve ridden in the game before. It’s unique, fun, and makes riding aggressive lines feel incredible.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
5) Final Thoughts
If you’ve been hesitant to mess with tileinfo, I really recommend giving it a shot. And if you’re open to experimenting, try involving AI in your workflow. For me, it turned what’s normally a frustrating trial-and-error process into a creative collaboration.
I think this is just the start. Imagine using AI not only for traction, but also for designing realistic erode profiles, tuning suspension to match surfaces, or even helping brainstorm track layouts. It’s a tool that can help push MX Sim forward in really exciting ways.
So yeah — that’s my story. AI helped me create a traction setup that I’m genuinely stoked on, and I think this kind of experimentation could open up a lot of possibilities for the community.
Would love to hear your thoughts if you give the preset a try.
– Cody B