ET Mueller

The Safe Hire Trap

I’ve been thinking about how trading companies hire. Every job post is a checklist. If you don’t hit 9 out of 10 requirements, you don’t stand a chance. The industry is specialized, margins are thin, and firms want people who can deliver from day one. But does our fear of false positives (bad hires) cost us more through false negatives (great candidates rejected)? I’ll try to steelman that case. In Job Market Signaling, Michael Spence described hiring as “inefficiently mimetic,” where everyone copies the same signals even when those signals have weak predictive power. HC Group recently noted that “a consistent core of elite institutions… continue to dominate the feeder school landscape.” That’s signaling in action. A similar dynamic shows up in Akerlof’s The Market for Lemons. Buyers can’t distinguish good cars from bad ones, so they lower their bids just in case. The result: good cars vanish from the market, leaving mostly lemons. Hiring can fall into the same trap. Employers can’t know everything about a candidate, so they rely on proxies—pedigree, credentials, referrals. Since these signals are easy to mimic, firms respond by raising the bar or over-relying on word-of-mouth. The outcome is a labor market full of “safe” choices, but not necessarily the best people. This conformity produces Institutional Isomorphism. Cultures start to look the same across the industry. Innovation drops. Talent moves more easily. Because if every company feels identical, why stay at any of them? Taking seriously the maxim that Culture is Strategy in Commodity Trading means starting with how people are hired. Here are a few practices worth drawing from:

No HR filter: Let hiring managers screen first, like at SpaceX, where engineers interview engineers.
Real problem-solving: IDEO candidates sketch and co-create with the team, revealing how they collaborate under uncertainty.
Behavioral observation: One famous manager asked candidates to assemble IKEA furniture to test composure and teamwork.
Outside-the-interview cues: Zappos evaluates how candidates treat drivers, receptionists, and waitstaff—the “airport test.”
Reasoning tests: Jane Street uses logic and probability puzzles to see how people think under pressure.
Make it fun: Google once posted a math puzzle on a billboard that led solvers to a hidden application page.

Skills also travel better than most org charts suggest. Google’s Career Dreamer shows how expertise transfers across domains. Maybe an unemployed software developer would excel as a paper trader. Maybe a frustrated journalist should become a cargo operator. And avoiding Phil Ensor’s Functional Silo Syndrome is another reason to rethink hiring. Silos tend to turn inward, ignore the wider business, and amplify conflict—creating a negative feedback loop that poisons culture. None of this means ditching diversity. It means anchoring it in meritocracy. Diversity of thinking and experience is essential for traders who want to make sharper decisions and build innovative businesses. The best physical traders started in operations. Great risk managers were once traders. Top accountants came from IT. Astute operators once worked in trade finance. And the most successful managers know when to act differently—and when doing so is worth it.

Quality Mgmt is Risk Mgmt

In many trading firms, people spend an extraordinary amount of time firefighting avoidable errors. Hedges are put on the wrong way. Recaps miss key terms. Demurrage claims are time-barred. Invoices go out with incorrect prices. Each mistake consumes hours of energy that should be spent on analysis, execution, and strategy. The antidote to these operational risks is a consistent focus on quality—so long as the cost of implementing controls stays below the value of the errors prevented. But quality management is hard. It is slow, unglamorous, and easy to abandon after a few half-hearted attempts. Yet when practiced with discipline, its benefits compound. A major obstacle is incentives. If the people who create errors do not bear their costs, the errors persist. Misaligned incentives let mistakes spread like weeds. The “broken windows” theory—contested in criminology but still powerful as metaphor—illustrates how small failures left unaddressed normalize substandard behavior. Standards slip, errors multiply, and quality erodes. The escape from that downward spiral is the upward spiral of Kaizen. Quality management follows a rhythm: plan improvements, put them into practice, check the results, and adjust. Over time, errors decline, processes accelerate, and the most precious resource—people’s time—is freed for higher-value work. That reclaimed time sharpens situational awareness, lifts morale, and creates a flywheel in which fewer errors lead to fewer new errors. When people operate inside a high-quality process, they contribute more, stay longer, and care more deeply. The sentence “I’m not sure that’s my problem” disappears. A state of flow becomes possible: a seamless integration of action and awareness. A Michelin-starred restaurant offers the purest analogy. Excellence is systemic. Mise en place ensures every ingredient, tool, and station is ready before service. Timing, temperature, plating, lighting—every detail matters. One weak link can spoil the entire experience. Trading firms are no different. Quality must run through the entire deal lifecycle: contract drafting, risk checks, vessel nominations, LC issuance, and final settlement. When it does, counterparties notice. Just as diners return to restaurants that execute flawlessly, clients return to traders who operate with precision. Quality management is Reinforcement Learning applied to organizations. Machines learn through feedback—not by avoiding mistakes, but by making them, measuring them, and adjusting their policy. In actor–critic algorithms, the actor chooses actions, the critic evaluates them, and the model improves. If computers can repeatedly cycle through error and refinement to master complex environments, trading firms can do the same—and more.

Situational Awareness

Situational awareness is the ability to understand the environment, its key elements, and how it changes over time and under the influence of external factors. It develops in three ascending levels: Perception — noticing and identifying relevant signals. Comprehension — understanding how those signals fit together. Projection — anticipating how the situation will evolve (see Endsley, 1995). When situational awareness breaks down, failures follow. In the recent Potomac River collision, pilots appear to have misjudged their positions. In the 2003 Northeast blackout, operators lacked real-time system visibility. The pattern is the same: the signals were there, but the ability to integrate them was missing. Trading offers similar examples. In 2006, Amaranth Advisors believed they were taking acceptable risks with long U.S. natural gas time spreads. What they failed to anticipate were shifting weather patterns, the resulting storage imbalance, and evaporating liquidity. Within weeks, over $6 billion vanished. The data existed. The awareness did not. Strong situational awareness, on the other hand, has always been a competitive advantage. Marc Rich built his empire by cultivating dense information networks that allowed his firm to spot disruptions and arbitrage opportunities faster than competitors. Today, high-performing trading firms cultivate situational awareness deliberately. They do it by: • Experience — training teams to recognize patterns and anomalies quickly. • Language — standardizing vocabulary across trading, risk, finance, and operations. • Communication — establishing routines like morning calls and end-of-day recaps. • Proximity — keeping teams close to strengthen feedback loops. • Culture — encouraging early flagging of concerns and open challenge. • Roles — dividing responsibilities so no one carries an impossible cognitive load. • Trust — ensuring information flows freely; as Navy SEALs note, trust beats performance. • Rotation — moving staff across functions to deepen shared context. • Systems — applying systems thinking internally and externally. • Technology — using ETRM and analytics to surface what truly matters. Looking forward, artificial intelligence will push situational awareness into a new dimension. Used well, AI can extend perception, sharpen comprehension, and improve projection by detecting patterns no human could. But if traders fail to evolve and integrate these tools into their craft, AI may not just augment them — it may replace them.

Culture Is Strategy in Commodity Trading

Culture is strategy in commodity trading.

While cultures vary across the industry—shaped by origin stories, management styles, and risk appetites—successful trading firms tend to share a recognizable cultural architecture.

Good trading cultures focus on:

Great trading cultures raise the game:

Culture is a river—always moving. You can’t stop its flow; you can only shape its path. Political philosopher James Tully notes that cultures are “continuously contested, imagined and reimagined, transformed and negotiated” (Strange Multiplicity, 1995). Culture is not static. It is lived daily through decisions, habits, and how teams respond under pressure.

As Harvard Business Review has argued, culture doesn’t change through slogans. It changes when systems change. When leaders demonstrate the norms they claim to value. When behaviors are reinforced consistently—not just announced.

The same holds in trading. A new ETRM platform or AI model is only as good as the culture that surrounds it. Tools enable performance, but culture determines whether that performance compounds.

Skills Matter More Than Knowledge in Commodity Trading

In commodity trading, skills matter more than knowledge.

The same is true in artificial intelligence. As Andrew Ng reminds us in The Batch, AI is an applied discipline — driven not by theory alone, but by experimentation, iteration, and the ability to translate ideas into working systems.

Focusing on skills is good for organizations as well as individuals. Companies that hire for skills inevitably build more meritocratic cultures — places where the best ideas win, not just the best résumés.

Both trading business models and AI models thrive through the same mechanism: people (or agents) who build, tinker, and refine until the results speak for themselves.

When I hire, I look for the 5 Cs of commodity-trading skills:

In the classic communication model, a sixth C is often added: Considerate. That matters everywhere. But in trading teams, I look for one more: Compatibility — the unique value someone adds to the group. When the skills in a team align and complement one another, the total is greater than the sum of the parts.

The same principle underlies modern machine learning. Deep Reinforcement Learning is not RL plus DL — it is the powerful interaction between them. Trading teams work the same way: skills that reinforce one another create an edge that no single trait could achieve in isolation.

The Rivers of Money

You can learn a great deal about commodity trading from The Rivers of Money by Adi Imsirovic and Colin Bryce. At its core, the book explains how traders create value through optionality and arbitrage, especially in complex markets and during moments of large structural change. No matter the environment, successful trading firms “operate with urgency and precision” — perhaps like Winston Wolfe in Pulp Fiction.

Oil trading demands the intellect of Magnus Carlsen, the cool of Phil Ivey, and the nerves of Evel Knievel. The pressures and pleasures bring out both the best and worst in people. You’re all in, every hand. In the sitcom version of the book, Dani Rojas would shout: “Trading is life!”

The early chapters may feel familiar to readers who know the history of oil trading from books like The Prize, The King of Oil, or The World for Sale. But the book shines in its contemporary stories of late 20th-century lore (see also “40 Classic Crude Trades”). There’s Bridie Tobin calmly downing vodka to counter a bad oyster before returning to “complete a full day’s work,” and Andy Whitrow’s perfect line: “Oil traders are like football managers — they fail, but someone always wants to hire them.”

A marketer might wish the authors had gone with a simpler subtitle (“Inside the World of Oil Trading”), while a social scientist might quibble with the boundaries of “social and economic history.” In truth, this is part history, part memoir, part essay — a hybrid that works.

It is not an exposé in the style of The World for Sale, though it does engage with the darker sides of the industry. A sequel could go further by proposing structural solutions. Most traditional regulatory solutions won’t work. How do we create incentives for these optimal “norms, values, and ethical boundaries” to become self-reinforcing?

The World for Sale

The World for Sale by Javier Blas and Jack Farchy is well-researched, well-written, and — for good reason — widely read. The authors argue that the largest commodity trading firms have:

But the full story is more nuanced. The reflections below aim to give readers outside the industry a broader understanding of how commodity trading actually works.

1) The book focuses on the giants.
The narrative centers on the largest trading houses. Much less is said about the many niche traders who quietly compete — and often win — in difficult markets.

2) Some markets are oligopolies; many are highly competitive.
While certain supply chains are dominated by a few players, many commodity markets resemble near-perfect competition. Returns are generally commensurate with the risks taken.

3) Traders thrive in upheaval.
The most successful traders are fundamentally entrepreneurial. They succeed during the four major market disruptions highlighted in the book because they can act decisively when the world becomes uncertain.

4) The fundamentals still matter.
Low prices, reliable execution, and trust remain the cornerstones of the business.

5) Power must be used.
As Jeffrey Pfeffer writes in 7 Rules of Power, “power unused is power lost.” Traders deploy influence and relationships to win business — or they lose it to competitors who will.

6) The industry demands resilience.
Traders operate in what Byung-Chul Han calls “an excess of stimuli, information, and impulses” (The Burnout Society). Thriving in this environment requires unusual psychological stamina.

7) Commodities are money.
The authors close by advocating tighter U.S. oversight of dollar flows in trading. But stricter enforcement could accelerate non-dollar trade and raise long-term borrowing costs for the United States.

8) Traders dislike transparency — like magicians.
Magic tricks look trivial once slowed down or explained step-by-step. Traders feel similarly about revealing their edge.

9) Sometimes traders really do perform magic.
When crises emerge, traders often solve problems no one else can — at a price. Take it or leave it.

10) Don’t count out trading.
Traders play a critical role in keeping global commodities moving. You take the good with the bad — because without them, the system stops.

Hedges Are Like Pets

Hedges are like pets.

Simple breeds are usually best. Exotic ones may look impressive, but they require constant care — and can turn on you when you least expect it.

Sizing matters. A small dog might not deter an intruder; a large one can overwhelm a small apartment. Oversized hedges create the same problems: strain on liquidity, credit limits, and operational capacity, especially during stress events.

Pets aren’t cheap. Neither are hedges once execution costs, clearing fees, margin requirements, and roll maintenance are factored in.

Both need grooming. Pets need brushing and exercise; hedges need ratio adjustments, roll management, and regular reporting. Neglect the pet and the carpet pays the price. Neglect a hedge and the consequences are far worse.

And just as a family shares responsibility for a pet, effective hedging requires coordination across front office, middle office, and back office. A clear policy is essential. As John Hull reminds us in Options, Futures, and Other Derivatives:

“Senior management should issue a clear and unambiguous policy statement about how derivatives are to be used and the extent to which it is permissible for traders to take positions.”

Clear policy. Disciplined execution. Consistent care. When managed properly, a hedge offers the same thing a well-trained pet does: comfort.

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