Retrieving the file
Live· 4,218,906 positions deprecated· 4,218,906 deprecated· 1,284 today
Average time-to-redundancy: 11.3 months
Know before your role does.
pssst. this is to sign up for updates on the game ;)
Will AI replace Inference Kernel Engineer jobs? · Latest report #mdd2nzny
Your job has an expiration date
October 21, 2027
In 12 monthsYou are literally optimizing the very thing that is deleting you.
Professional ghost-writer for silicon and cache hierarchies.
Check another roleComment your opinionor JOIN THE RESISTANCE!
One human is building a game about fighting back.
Hand-tuned performance for free, forever.
ow.you▸ KERNELOPTIMIZER AI V4▸ RARITY · COMMON▸ DEPRECATION IN 12 MONTHSAI's Special Power
autogenerates optimal cuda kernels instantly
You spend your life manually unrolling loops and tuning memory strides for GPU kernels. It is a slow, dying art of writing assembly-adjacent code for tensors.
The one thing AI can't do
You can still explain exactly why a specific hardware cache line causes that weird race condition.
Your enemy, your name, your date. Post it.
Step by step, from the first quiet change to Deprecation Day.
Day 10
The system begins identifying your most redundant loop-unrolling patterns automatically.
Month 3
Neural compilers generate hand-optimized assembly code faster than you can open a terminal.
Month 6
Your custom hardware-specific tweaks are replaced by adaptive cross-platform orchestration layers.
Month 9
Manual kernel deployment is replaced by real-time model-to-hardware compilation pipelines.
Month 12 · D-Day
The inference stack is now fully self-optimizing and requires no human kernel engineers.
What you cost, what the machine costs, and what you get on the way out.
Per year
Savings: 97.8%
99.9% wasted
Manual Kernel Cycles
Sub-millisecond
Average Latency
Non-zero
Human Error Rate
Your severance
A lifetime subscription to cloud-based GPU clusters.
Discussion
