“Just use ChatGPT” is a comment we see almost daily when ECU tuning comes up, but is it actually viable?
In this video, a professional tuner with over 20 years of real-world experience puts that idea to the test and finds out whether AI is genuinely a threat to his job. The brief is simple: generate the three core tables you would normally rely on to get a car up and running safely, volumetric efficiency (VE), target lambda, and ignition timing.
Along the way, ChatGPT does show some strengths. It asks sensible setup questions, understands high-level engine behaviour, and can explain tuning concepts clearly when challenged. It also proves useful as a discussion tool when reviewing logs and thinking through possible changes.
Where things start to unravel is in the details. Table breakpoints do not line up with the ECU, pressure axes are supplied in the wrong format, VE values are capped unrealistically low for a modern turbocharged four-valve engine, and target lambda under boost ends up leaner than most tuners would be comfortable with. Even when ignition timing lands close to a workable region, the overall shape and level of conservatism raise questions about how safe a true “base map” really is.
The dyno testing makes the risks clear. Large closed-loop fuel trims are required just to keep the engine near target, and without them, the tune would be nowhere near safe. When a data log is fed back into ChatGPT for corrections, it initially struggles to interpret what is actually happening until significant context is provided.
If you have ever wondered whether artificial intelligence can replace real calibration experience, this video shows exactly what happens when you put it in front of the software and the dyno.
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TIMESTAMPS
0:00 - Will AI Replace Tuners?
0:45 - Can ChatGPT Tune A Haltech Elite
1:18 - Asking For A Base Map
2:45 - Our Car Setup
3:04 - ChatGPT’s Advice Is Sketchy
4:29 - Let's Get Started
5:00 - Voice Mode vs Text Mode Output
6:38 - The Three Tables That Matter Most
7:09 - The NSP File Claim And AI Hallucination
8:24 - VE Table In Excel | First Red Flags
9:06 - Why Low VE Numbers Can Run The Engine Lean
10:28 - MAP Axis Problems | Gauge vs Absolute
11:16 - Correct Breakpoints/Resolution
12:00 - Flipping The Load Axis For NSP
12:39 - Copy And Paste Into NSP | The Table Breaks
13:46 - First Start Problems
14:22 - VE Table Shape | This Is BAD
15:23 - The 90% VE Cap Argument Falls Apart
16:12 - Realistic Turbo VE Numbers
17:53 - Target Lambda Table Analysis
19:41 - Comparing Against 'Human' AFR Targets
21:39 - Pasting The AI Lambda Table | Still Not Happy
22:17 - GhatGPT's Base Ignition Table
25:02 - Did ChatGPT Get Base Ignition Timing Right?
27:21 - Dyno Test Begins | Watching Lambda And Fuel Trims
27:51 - Part Throttle Reality Check | Trims Are Working Hard
28:23 - Closed Loop Limits Hit | Still Lean
28:44 - Increasing Trim Authority To 25%
29:16 - Into Boost | 23% Trim To Hold Target
29:23 - Idle vs Cruise | Rich Here, Lean There
30:12 - Attempting A Ramp Run Anyway
30:54 - Dyno Plot Review | Power, Boost, Lambda
31:21 - Why Closed Loop Saved The Engine
32:08 - Log Review | Target vs Actual Lambda
32:39 - Peak Boost While Near Lambda 1
33:03 - Fuel Trim Pegged At 25% Through The Run
33:41 - Can ChatGPT Fix It From A Data Log?
34:10 - Exporting Haltech Logs To CSV
34:30 - Asking ChatGPT To Analyse The Ramp Run
35:07 - Missing Headers | Feeding The Correct Labels
35:28 - Wrong Corrections | Not Accounting For Closed Loop
36:14 - Adding Fuel Trim Channel And Clarifying Units
36:41 - ChatGPT Tries To Pull Fuel From A Lean Map
37:07 - Coaching The Model | The Penny Drops
37:36 - New VE Numbers | Now In The Ballpark
38:08 - The “Mount Everest” VE Table Problem
39:12 - Second Ramp Run With The AI Corrections
39:42 - Better In Places | Ugly In Others
40:01 - Data Log Review | Closer To Target
40:20 - Trims Still Working Hard
40:44 - Summary | All Three Tables Were Questionable
41:22 - The Real Risk For New Tuners
41:53 - Will This Change In 12 To 24 Months?
42:16 - AI Learns From The Internet | Mixed Quality Inputs
42:39 - Andre’s Verdict | Feeling Safe In The Job
42:44 - Learn To Tune Safely
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