Food Systems Are Outrunning Food Stories

Something has shifted in food, nutrition, and health over the last few years, and most of the public conversation has not caught up.

Consider ultra filtered milk.

A decade ago it was a processing novelty. Today it is a multi billion dollar category backed by Coca Cola’s patent estate, sold on protein claims that legacy dairy law was never designed to evaluate.

This is not a one off. It is happening across the food system.

We are arguing louder, filing more lawsuits, publishing more opinion pieces, and drawing firmer conclusions, even as the systems underneath those arguments are getting more complex and less well understood.

Processing has changed.
Manufacturing has changed.
Capital flows have changed.
Data availability has changed.

But we are still using mental models built for a simpler era and then acting surprised when nothing seems to make sense.

We lean on classifications and shorthand because they feel manageable.

They compress complexity into something people can argue about.

But compression does not just simplify reality. It warps it.

When foods become fractionated, optimized, recombined, or algorithmically designed, the old categories stop working.

They still feel satisfying, which is why they stick around, but they do not predict risk, benefit, or behavior particularly well anymore.

This is why so many current debates go nowhere.

People are not arguing in bad faith.
They are arguing about the wrong things.

We are fighting about labels when we should be looking at systems.

We are asking courts, journalists, and consumers to settle questions that science has not figured out yet.

Protein is treated as settled.

High protein is good.
More is better.
Claims are easy to make and hard to check.

But the moment protein is concentrated, fractionated, reformulated, or optimized by algorithm, confidence starts to outpace evidence.

Metrics designed to describe nutritional adequacy, like PDCAAS, DIAAS, and digestibility coefficients, get turned into performance claims.

Legal frameworks built for whole foods get applied to engineered ones.

The technology keeps moving, and the conversation pretends nothing fundamental has changed.

That gap between what we can actually measure and what we imply is exactly where regulatory and legal risk is piling up.

Carbohydrates present the opposite problem.

They are everywhere, deeply consequential, and poorly understood.

Glycemic index, net carbs, resistant starch, prebiotics: all stand ins for systems we barely map.

We figured out protein sequencing before we understood how carbohydrates actually behave at scale.

That gap is now running headlong into personalized nutrition promises that assume we know more than we do.

Fiber follows the same pattern.

Important concept.
Shaky definitions.
Oversold confidence.

Fermentability is poorly characterized at the individual level, and microbiome variability makes blanket claims hard to defend.

It feels familiar, which makes it easy to talk about, but the science is still unsettled in ways that matter for both operations and legal exposure.

Machine learning is already shaping how foods get designed, optimized, and positioned.

AI is good at finding patterns in whatever data you feed it.

It is not good at telling you where that data stops being reliable.

When models train on incomplete, biased, or proxy datasets, they do not slow down.

They speed up.

They get more confident.

This is how you end up with formulations that are statistically optimized but biologically ambiguous, carrying claims that sound precise but rest on thin evidence.

The gap between computational speed and scientific certainty is not a future problem.

This is where friction turns into lawsuits, policy reversals, and public confusion.

Not because companies are being reckless, but because the frameworks are out of step with what they are supposed to govern.

When that happens, the hard questions land in the wrong places.

Courts end up ruling on nutrition science.
Journalists become de facto process experts.
Consumers are expected to read risk off labels that were never built for that job.

Capital plays a bigger role here than people acknowledge.

Undercapitalized companies simplify aggressively because nuance is expensive and narrative is cheap.

Claims get made earlier.
Testing gets skipped.
Complexity gets papered over.

Companies with more runway buy time, rigor, and flexibility.

That difference shows up later as product quality, scientific caution, and regulatory posture.

But we rarely talk about it.

We judge the outcomes and ignore the systems that produced them.

What connects all of this is not one ingredient, one technology, or one business model.

It is the widening gap between how fast systems are changing and how slowly our ways of talking about them are updating.

The point is not to find villains.

It is to slow down enough to ask better questions.

What do our metrics actually measure versus what do they imply?
Where are we trading accuracy for convenience?
Who bears the consequences of these decisions and who is insulated from them?

The cracks showing up across the industry are not random.

They are telling us something.

The risk is not missing the signals.

It is moving too fast, locking in the wrong answers, and realizing it only after the damage is done.

Mark Haas is the founder and CEO of RegulateCPG, an AI-powered compliance infrastructure platform designed to democratize regulatory expertise for food and beverage companies. With 35 years of experience navigating food safety regulation, manufacturing operations and multi-jurisdiction compliance, Mark has formulated over 200 brands representing more than $2 billion in market value. His work spans conventional, plant-based and emerging protein technologies across FDA, USDA, CFIA and EU regulatory frameworks, with deep expertise in using sophisticated amino acid analysis and PDCAAS methodology to create litigation-proof label claims for alternative protein companies.

For more insights on using regulatory compliance as competitive advantage, visit regulatecpg.com or connect with Mark on LinkedIn.

Legal Disclaimer:
This article discusses regulatory strategy and compliance approaches but does not constitute legal advice. Companies should consult qualified food law attorneys and regulatory counsel for guidance on specific labeling decisions and regulatory interpretations applicable to their products.