Dodge the AI Infrastructure Tax Like a Billionaire

<div class="text-align-center">This article was originally posted on our Substack, The AI Loop.</div>
<div class="button-group is-center"><a class="button" target="_blank" href="https://unionailoop.substack.com/">Follow The AI Loop</a></div>
Nobody likes paying taxes. But what’s the worst kind? The one you don’t even know you’re paying.
Believe it or not, that’s what’s happening to most AI teams today. They think the cost to train and ship AI is set and unavoidable. And by accepting that, they incur the AI Infrastructure Tax. And like real taxes, some teams pay it blindly while others act like a billionaire and find metaphorical loopholes, shelters, and accountants.
How to Calculate Your Infrastructure Tax
Here’s a simple way to think about the infrastructure tax many pay rather than avoid:
- Compute Waste = the cost of idle or overprovisioned compute + the cost of recomputation when a workflow breaks and needs to restart
- Extra Infra Maintenance = the ongoing drain on engineering time devoted to keeping AI infra running, especially platform engineering on-call pains and roadmap distractions
- Savings from Self-Managing Infra = the skipped cost of a managed orchestration platform
Let’s try an example with sample numbers. Say a team runs 10,000 jobs per month. If 15% fail late in the pipeline, that’s 1,500 reruns. At 3 GPU-hours each × $4/hour, the team just incurred an Infrastructure Tax of $18,000/month before even considering labor cost of maintenance. Multiply that across a quarter, and they’ve burned through more than some teams’ entire compute budget.
Three Contributors to the Tax, and Shelters to Avoid Them

If you’ve worked around production AI systems, you’ve probably seen some version of this story.
- Pilot phase: $5k/month in compute… manageable.
- Early production: $20k/month... You’re in a new tax bracket now. You’re raising eyebrows, but still defensible.
- A year in: a compute bill of $100k+… Oof, you just blew the whole budget for the year, and too much of it was on avoidable stuff. Not very billionaire of you.
It’s the AI equivalent of filing your taxes every year without taking any deductions. Legal? Sure. But not savvy.

1. Reliability — the tax multiplier
In pilots, failure is just a nuisance. Someone restarts the job, manually retries with more compute, and moves on. But in production, failure is a tax multiplier:
Every failure means wasted compute spend. Every restart resets the clock. Every brittle workflow distracts teams from the roadmap and creates on-call headaches.
Sometimes teams will use an old-school data orchestrator to head this off. This is like trying to file your taxes with basic tax software. Failures happen in the compute layer, but the orchestrator can’t see why because it’s not infra-aware like AI-native orchestrators are. It just retries, usually from the beginning.
Tax Shelter #1: Infra-aware, AI-native orchestration treats failures like a dynamic decision point: did we not provision enough compute? Retry with more automatically. Was it a network error? Resume mid-run using automatic recovery.
Reliability issues burn through cash and morale when the system stumbles. An AI-native orchestration approach to your infrastructure avoids those costs.
3. Missing cost optimizations — the silent surcharge
A single, misallocated GPU doesn’t feel like much until you multiply it across thousands of runs. That’s when the hidden surcharge shows up on your bill: jobs that never scale down to zero, humming in the background like forgotten subscriptions. Low-latency inference accidentally running on a $4/hr node when a $0.12 CPU would do. Paying to spin up identical containers for matching tasks.
One team told us their bill went from the equivalent of a “Netflix subscription” → “car payment” → “mortgage” in a matter of months. That’s the infra tax sneaking up in real time.
Tax Shelter #2: You need to be thinking about the collection of optimizations that can make your systems production-ready. Whether you build these optimizations yourself or use a managed platform, these steps are necessary. Reusable containers to drop task startup time below 100ms. Auto-scaling and scale-to-zero. The list goes on.
3. Stack Complexity — the paperwork problem
AI teams, and especially platform engineers, know the pain of a fragmented infra stack full of point solutions. When half the repo exists just to keep workflows glued together, you’re doing the equivalent of a whole bunch of paperwork that should be handled by your accountant.
Six failure logs, three observability dashboards, two data processing tools, and a partridge in a pear tree. Debugging means spelunking through logs scattered across half a dozen tools, and every pipeline update feels like filing an amendment with the IRS: time-consuming, risky, and hard to explain to your boss.
Tax Shelter #3: AI-native stacks should have a unified development layer, which brings together data, models, and compute infrastructure into a single pane of glass. One place to manage workflows from training and fine-tuning, to inference, to observability. Like hiring a killer accountant and saying, “you handle it.”
The Billionaire Playbook

Whether you like it or not, billionaires are unbelievably savvy in their approach to avoiding taxes. This is because they understand the value of investing in a good strategy. They hire accountants, find loopholes, and design structures that make the rules work for them instead of against them.
AI infrastructure works the same way. Just because you have to pay the AI Infrastructure tax doesn’t mean you can’t minimize it. You can structure your strategy so you’re netting a lower cost in both cash and labor.
Let’s revisit our formula:
Savvy AI engineering teams are using tax shelters, and usually those come from deploying a managed platform to minimize compute waste and labor cost of infra maintenance. To demonstrate, they might use a formula closer to this:
The AI Infrastructure Tax is real. Some teams pay it blindly, others pay it strategically. Treat infra costs like billionaires treat taxes, as a system that can be engineered to work in your favor.
<div class="button-group is-center"><a class="button" target="_blank" href="https://unionailoop.substack.com/p/dodge-the-ai-infrastructure-tax-like?utm_source=substack&utm_medium=email&utm_content=share&action=share">Share</a></div>