How a Vibecoded Newsletter Is Making the Hay Market More Transparent
Bloomberg's Odd Lots podcast interviews Aiden Johnson, a 20-year-old college student who used AI and vibe coding to build Haywire, a newsletter that aggregates USDA hay price data and auction house information to bring transparency to the opaque U.S. hay market. The conversation covers hay market structure, rising prices driven by drought, and the broader implications of AI-enabled niche data businesses.
Summary
Tracy Alloway and Joe Weisenthal interview Aiden Johnson, founder of Haywire (haywireag.com), a market intelligence newsletter focused on U.S. hay prices. The episode originated when Tracy discovered posts about rising hay prices on the Homestead subreddit, where someone recommended the podcast cover the topic.
Aiden, a 20-year-old college basketball player at the University of Jamestown, explains that the idea came from his father, who was researching raw material costs for an alfalfa cube startup and couldn't easily find hay prices. Aiden and his co-founder Cole built Haywire using AI and vibe coding — starting as a simple website project and evolving into a more sophisticated agentic automation system. The business model centers on pulling public USDA NASS data via direct API integration, which publishes weekly auction prices across regions in hard-to-find PDFs, then converting that data into plain-English newsletters. They also partner with Rock Valley Hay Auction in Iowa, one of the largest hay auctions in the country, for on-the-ground pricing intelligence.
The hosts discuss how the hay market is highly fragmented and hyperlocal due to high transportation costs ($5–$8 per mile), meaning regional prices don't easily arbitrage with one another. Current USDA data shows hay at $180/ton (up from $167 in March) and alfalfa at $185/ton (up from $175). A key market stress is that 46% of U.S. alfalfa acreage is currently under drought conditions, particularly in western states, which Haywire hypothesizes is pushing demand eastward — what they call the 'Missouri Pattern.'
The conversation covers hay quality metrics, specifically Relative Feed Value (RFV), a score based on 100 that measures protein and fiber content. Higher-quality hay (higher RFV, more leaf content) goes to dairy cows and horses, while lower-quality hay feeds beef cattle. Dairies are managing high prices by mixing premium alfalfa with lower-quality hay to stretch rations.
Second-order effects of high hay prices include increased horse boarding costs, horse sanctuaries facing closure, and farmers withholding hay from auctions anticipating further price increases. Carryover hay from 2025 is described as essentially gone, and first cuts are producing light yields.
Joe raises the point that Haywire exemplifies a business model he has long advocated: finding publicly available but obscure data, aggregating it, and building a user-friendly layer on top. The hosts draw parallels to scrap metal pricing (where brokers historically called junkyards), LIBOR, and Flight Radar 24. Both hosts note this type of business would have been impractical before AI reduced the labor cost of data ingestion and newsletter generation.
Aiden identifies commodity brokers and middlemen as the parties most threatened by increased price transparency, since they currently benefit from buyers and sellers operating without reliable benchmarks. He also discusses potential future directions: expanding to more auction house data partnerships, offering API access to businesses, and potentially becoming a reference benchmark for a tradable hay instrument — though he notes hay's dependence on weather makes standardization challenging. The alfalfa market alone is valued at $8 billion annually, making it the fourth most valuable U.S. crop, across 49–50 million acres of hay acreage nationally.
About this episode
<p>The hay market is not a transparent market: It is very fractured by types of hay, whether it is alfalfa or clover hay. There are a few opaque, illiquid markets like this — scrap metal for instance — that require some hands-on investigating to figure out. Aiden Johnson is co-founder and CEO of the <em>HayWire</em> newsletter, which aims to make the hay market more transparent: He and co-founder Cole Glasgow use an AI model to mine public data sources — like USDA reports on auction prices across different regions — to produce a weekly newsletter on the hay market. On this episode, we speak with Johnson as he explains why he chose hay over other kinds of markets, how <em>HayWire</em> was made possible through vibecoding, networking with hay farmers, why the ROI of owning a horse is dropping with hay prices spiking, and why hay demand keeps on tightening.</p><p>See <a href="https://omnystudio.com/listener">omnystudio.com/listener</a> for privacy information.</p>
Key Insights
- Aiden Johnson argues that the U.S. hay market is fundamentally untransparent because USDA auction price data is published weekly in buried PDFs that most buyers and sellers never find or use, leaving them to negotiate prices blindly.
- Johnson claims that transportation costs of $5–$8 per mile make it uneconomical to ship hay across large distances, which is why the hay market fragments into hyperlocal regional markets that don't naturally arbitrage with one another.
- Johnson reports that 46% of U.S. alfalfa acreage is currently under drought conditions, carryover hay from 2025 is essentially depleted, and first-cut yields are running light — conditions he says are tightening supply significantly.
- Haywire identified what they call the 'Missouri Pattern,' a hypothesis that western drought conditions are pushing hay buyers eastward, evidenced by sequential weekly price spikes first in Missouri and then at Rock Valley Auction in Iowa.
- Johnson argues that commodity brokers and middlemen stand to lose the most from hay price transparency, since they currently profit from buyers and sellers who lack reliable benchmark data and negotiate without reference prices.
- Johnson observes that dairies are responding to high hay prices by mixing premium high-RFV alfalfa with lower-quality hay to stretch rations and control feed costs, rather than simply absorbing higher input prices.
- Joe Weisenthal argues that this business model — finding publicly available but obscure government data, aggregating it, and presenting it in a user-friendly format — is a viable entrepreneurial strategy that AI has made newly accessible to individuals rather than requiring large teams.
- Johnson notes that agricultural land is now competing not only with data centers for physical acreage but also with data centers for water in western states, since alfalfa is a water-intensive crop and air-cooled data centers are being sited in drought-prone regions.
Topics
Transcript
Odd Lots is brought to you by VanEck. For years, investors basically forgot about real assets, energy, gold, and infrastructure. But look what's driving markets now. Central banks loading up on gold, massive CapEx cycles, currencies doing weird things. These assets are at the center of it. Rax, the VanEck Real Asset ETF, is an actively managed one-stop shop for real assets spanning gold, commodities, natural resource equities, and more. Go to vanek.com slash RAAXpod to learn more. Fun disclosures later in this episode. The thing about AI for business, it may not automatically fit the way your business works. At IBM, we've seen this firsthand. But by embedding AI across HR, IT, and procurement processes, we've reduced costs by…
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