When Automation Met Hollywood: How a 1980s Hacker Rewired Wall Street and Foreshadowed the AI Age

Before Trading Places became a cult-classic about a hustler and a broker swapping fortunes, it began with a wager over dinner between a boisterous Hollywood producer and his companion, a future FinTech billionaire who at the time was quietly reinventing Wall Street.

This fateful dinner took place in the early 1980s, when unassuming Hungarian engineer Thomas Peterffy sat across from film producer Aaron Russo in a New York restaurant. Russo was fascinated by Peterffy’s claim that his trading floor ran so efficiently on computers that, with the right training, almost anyone could step in and make successful markets. Peterffy wasn’t exaggerating, he had built one of the first semi-automated trading systems in the industry, which was a precursor to the algorithmic engines that would later define global finance.

Amused, Russo joked that even his friend, the filmmaker Melvin Van Peebles, could handle the job. Peterffy called his bluff and a $10,000 bet was made. Van Peebles joined Peterffy’s firm, learned the ropes, and reportedly did just fine. Not long after, Russo produced Trading Places, a film whose central wager mirrored the very bet he’d made at that dinner table.

Hollywood spun it into comedy, but Peterffy’s version was pure revolution. While everyone else was shouting orders across the pit, he was wiring up machines to outthink them, turning Wall Street chaos into code. His firm, Timber Hill, became Interactive Brokers, one of the first to automate trading end-to-end.

In other words, while Trading Places joked that opportunity could make anyone rich, Peterffy was busy proving that automation could change the game entirely.

It’s a story Syfre loves because it sits right at the edge where humans and systems meet. Russo saw a punchline about opportunity. Peterffy saw the future: a world where automation doesn’t replace people, it amplifies their capacity. 

Stepping out on his own

Peterffy began his career in the late 1960s as a computer programmer for a commodities trading firm. By 1977 he was ready to take a risk. He bought a seat on the American Stock Exchange and stepped onto the trading floor as an independent options trader.

The floor was fast, loud, and entirely manual. Traders yelled prices across crowded pits and scribbled on scraps of paper. Peterffy quickly saw what others ignored: chaos was opportunity. If he could bring logic and speed to it, he could win.

He began by writing simple programs that calculated the fair price of options based on stock prices, volatility, and expiry. But the real challenge was data. To trade intelligently, he needed prices in real time.

Feeding the machine with live data

In the 1970s, market data was not digital. Prices came through ticker tapes and terminals designed for human eyes, not for machines. There was no direct way to stream prices into a computer.

So Peterffy built a device that could.

He wired a small computer to read the electrical impulses from the ticker, translating them into signals his software could understand. Each time a trade occurred, the ticker sent out a pulse. His homemade circuit converted those pulses into live data, feeding his program a real-time stream of prices.

That connection turned his computer into one of the first automated pricing engines in the world.
While other traders were still scribbling numbers on notepads, Peterffy’s system was continuously scanning the market, comparing spreads, and printing out opportunities the instant they appeared.

It was not elegant, but it worked, and it marked the true beginning of automated trading.

The keyboard that typed by itself

The biggest obstacle came next, and it was less an issue of technology than one of governance. 
Even though Peterffy’s program could identify trades automatically, the exchange refused to let computers place orders directly. Every order had to be typed in by a person sitting at a terminal.

Peterffy argued that it made no sense. The trades were valid, accurate, and fair. The only difference was that a machine had calculated them. In frustration, he even offered to use a mannequin if it helped meet the rule that a “human” had to be present. The exchange was not amused.

So he found another way.

Peterffy wired an electromechanical keyboard to his computer. When his program found a trade, the machine physically pressed the keys to enter the order. To everyone else, it just looked like a very fast trader hammering at a keyboard.

When officials eventually discovered what he had done, they banned mechanical devices. Peterffy modified the circuitry to make the machine behave more like a person, adding random pauses, uneven key timing, and imperfect rhythm.

It fooled the system completely, and the orders kept flowing.

In doing so, Peterffy created one of the earliest models of human-like automation. His computer didn’t just execute instructions, it performed them as if it were human in order to stay compliant.

The hacker mindset before APIs

Peterffy’s experiments didn’t stop with tickers and keyboards. He eventually: 

• Built circuits that translated trading signals into machine-readable data
• Created colour-coded displays so traders could interpret information faster
• Wrote continuous-loop programs that analysed prices and printed anomalies automatically

These are the same principles that continue to drive automation today: sense, analyse, act. He just did it with wires instead of APIs.

It was messy, improvised, and entirely human. The original version of building in public.

From hardware hacks to AI agents

The tools have changed, but the instinct remains.
Where Peterffy soldered wires, we design AI agents that make decisions and take action intelligently.
Where he timed solenoids, we orchestrate APIs.
Where he mimicked human keystrokes, we build systems that handle context, timing, and logic automatically.

AI now gives anyone the power to create what Peterffy once built by hand. You can automate workflows, decision points, and entire business functions without touching a circuit board. Months of engineering work can now be done in minutes.

The story hasn’t changed, only the medium. What was once built in copper is now written in code.

Automation as a creative act

Peterffy did not invent automation for efficiency. He did it to stay in the game.
His machines were not replacements for people, they were extensions of them.

That same mindset defines modern AI.
Every great automation starts with a constraint, a problem, or a frustration that pushes someone to say, “There has to be a better way.”

At Syfre, that belief drives our work, using AI to design smarter systems that help people focus on what matters most.

Because the most powerful automations don’t start with machines.
They start with humans who refuse to stand still.

Closing thought

Peterffy’s story is not just a footnote in trading history. It is a reminder that automation is, at its heart, a creative act.
From mechanical keyboards to AI agents, the tools have changed, but the impulse has not.

Automation has always been a human story.