How AI is Shaping Smarter Investing: Insights from Options Trader Erik Smolinski

Erik Smolinski, a full-time options trader, sees the use of AI in his field not as a luxury but as a necessity. For years, he's relied on data and historical trends to outpace the S&P 500, achieving what many aspire to: financial independence. Yet, the resources required to build such a system have traditionally been beyond the reach of the average investor. Expensive datasets and coding skills once acted as barriers to entry.

Now, the landscape is changing as AI levels the playing field. Smolinski is spearheading Project No Code, an ambitious venture involving an AI-assisted research database that's already amassed over 700 million lines of data. From options to stocks and economic indicators, the breadth is staggering. While Smolinski's setup involves massive data storage, think hundreds of terabytes, his overarching goal is clear: enable investors to make informed decisions without the need for coding expertise.

The AI Toolkit for Investors

AI tools, Smolinski isn't shy about choosing favorites. As of May 2026, he highlights Claude, Claude Code, Codex, and Gemini as his top picks. For those engaged in advanced research, Claude Code and Codex offer solid coding assistance, enabling users to execute complex projects without a technical background. While Gemini provides a broader data review, Smolinski asserts that the combination of Claude Code and Codex suffices for most needs.

But what about the everyday investor? Smolinski suggests starting simple. Basic chatbots like Claude or ChatGPT can provide valuable insights when investors articulate their goals in straightforward language. The aim is clear: empower investors to define their objectives, whether that's beating market averages, stabilizing returns, or preparing for retirement.

AI as a Thinking Partner

Smolinski is a firm believer in using AI to challenge his investment assumptions. He routinely asks AI to scrutinize his strategies, testing the validity of his market hypotheses. This approach isn't limited to seasoned traders. Everyday investors can also use AI to question the risks in their investment theses or to identify sector overexposure.

However, there's a caveat. AI is a tool, not a substitute for human judgment. As Smolinski cautions, models can err, data can be misinterpreted, and outputs can be flawed. Nevertheless, disregarding AI's potential isn't an option. In a world where technology advances at breakneck speed, investors must adapt or risk being left behind. The real world is coming industry, one asset class at a time.

Ultimately, the road forward is clear: embrace AI as a partner, not a panacea, in the quest for smarter investing.