Boost your investment strategy with ChatGPT: Top 5 AI tips that work

Dubai: AI is no longer a futuristic add-on in finance—it’s becoming the core of smart investing. At the forefront of this shift is Edward Frank Morris, CEO of Enigmatica and one of the world’s leading minds in Prompt Engineering.

Morris doesn’t just use ChatGPT—he builds sophisticated systems around it. From tripling his returns on ARM’s IPO to simulating investor personas with AI, he’s showing the world what happens when deep financial thinking meets cutting-edge generative tools.

"Get used to the way it works. Understand the quirks. Understand the limitations and patterns."

Morris compares interacting with AI to conversing with a human being—it requires intuition, repetition, and context. Simply reading about prompting isn’t enough. You need to develop a working relationship with the model.

By using ChatGPT daily, you learn:

·         How it interprets vague vs. specific questions

·         Which phrasing leads to shallow vs. insightful responses

·         Where its memory limitations and biases show up

For investors, this familiarity means better prompts, sharper research, and faster time-to-insight. It also means avoiding generic outputs and zeroing in on high-value perspectives.

Takeaway: Treat AI like a business partner—build trust through practice.

2. Prompt frameworks are just the beginning — It’s the mindset that matters

"Frameworks like Role-Task-Format are a start. But 60 per cent of the work is about refining prompts and troubleshooting why they fail."

Early-stage users often get stuck on prompt formats and templates. Morris argues that while foundational structures matter (like Microsoft’s GCE or OpenAI’s Role/Goal syntax), true value comes from thinking like an engineer.

He emphasizes:

·         Iteration: Prompting is a process, not a one-shot task.

·         Diagnosis: When results aren’t right, you must debug the prompt like code.

·         Creativity: Subtle changes in language can shift outputs dramatically.

Takeaway: Frameworks help you start. Engineering mindset gets you results.

3. Use AI's deep research tools to create information funnels

"Look beyond prompts. Use platform-specific tools to gather insights, then distill them."

For investment due diligence, surface-level search isn’t enough. Morris recommends using “Deep Research” features available on major AI platforms (like ChatGPT's browsing tools) to:

·         Pull the latest news on target companies and sectors

·         Track adjacent industry developments and regulatory shifts

·         Uncover hidden variables that could impact valuations

Once this raw intel is gathered, it’s refined using targeted prompting to produce clear, concise reports, saving hours of manual research.

Takeaway: Use AI to gather wide and refine narrow.

4. Build digital twins of investors — simulate with perspective

"Don’t just create roles. Create investor personas with traits, preferences, and emotional logic."

This is Morris at his most innovative. He encourages investors to build Digital Twins—AI personas that simulate real-world investor archetypes.

Rather than a generic "Investment Manager" prompt, you design a persona with:

·         A background (school, work history, sector focus)

·         A style (risk-averse, contrarian, ESG-focused, etc.)

·         A voice and emotional filter

You can then run decisions through these AI personas to stress test your thinking—getting responses that mimic real strategic investors like Warren Buffett or Cathie Wood.

Takeaway: Add human-like perspective to machine logic for richer insights.

5. Context is king — go deep or get generic

"If you ask it to act as an investor, what does that actually mean? Don’t let AI make assumptions for you."

Morris insists that most prompts fail due to lack of context. Users ask the AI to be a "financial advisor" or "analyst" without defining what that means—leading to bland or inaccurate responses.

He recommends:

·         Specifying education, experience, style, and objectives

·         Clarifying what the AI should care about in a scenario

·         Giving real-world examples, if needed, to guide tone and logic

This level of detail removes ambiguity and leads to significantly higher-quality output, especially when evaluating complex investment opportunities.

Takeaway: Don’t just tell AI what to be—tell it who, how, and why.

For those dipping their toes into AI-powered investing, Morris offers these four golden rules:

Morris is bullish on AI’s potential to revolutionize finance—but he’s realistic too. “AI won’t do the hard thinking for you,” he says. “But it will reward those who put in the work—with it.”

As GenAI tools mature and more investors wake up to their potential, Morris believes we’re only at the beginning of a new decision-making era—one where those who understand how to wield the tools will lead the next generation of financial innovation.

Morris’s strategies represent a shift from treating AI as a search engine to using it as a thinking partner. By combining daily use, engineering logic, persona simulation, and deep context, investors can go beyond dashboards and data feeds—to something more insightful, efficient, and ultimately more profitable.