In 2022, JPMorgan Chase CEO Jamie Dimon called cryptocurrency “decentralized Ponzi schemes” at a U.S. House Financial Services Committee hearing. “I’m a major skeptic on crypto tokens, which you call currency, like Bitcoin,” he said at the time.

But on Monday at JPMorgan’s annual investor day, Dimon said that JPMorgan Chase, the U.S.’s largest bank, will allow its clients to buy Bitcoin, per CNBC.

Related: JPMorgan Chase Says AI Could Cut Headcount By 10% in Some Divisions: ‘We Will Deliver More’

“We are going to allow you to buy it,” Dimon said. “We’re not going to custody it. We’re going to put it in statements for clients.”

^{JPMorgan Chase CEO Jamie Dimon delivers a speech during the Global Markets Conference, ahead of the Choose France summit, in Paris, on May 15, 2025. MICHEL EULER/POOL/AFP | Getty}

Rival Morgan Stanley has allowed clients to buy bitcoin ETFs since August 2024.

Dimon has long cited the risks of bitcoin, including money laundering. At Davos last year, he called it a “pet rock” that “does nothing.”

Related: ‘This Has to Stop’: JPMorgan CEO Jamie Dimon Outlines How to Run a Successful Meeting

But that doesn’t mean he is going to hold other people back from making their own financial choices.

“I don’t think you should smoke, but I defend your right to smoke,” Dimon said. “I defend your right to buy bitcoin.”

Since President Trump first announced new tariffs on U.S. trading partners in April, with frequent revisions ever since, American businesses of all sizes have been caught in a whirlwind of uncertainty. For entrepreneurs relying on foreign suppliers, sudden spikes in raw material costs can force a frantic reevaluation of longterm strategies and pricing models. These constantly shifting tariffs have upended months, even years, of planning across operations, production, supply chains, and competitive positioning, leaving many entrepreneurs stuck in near paralysis.

Most imported products face a baseline duty of at least 10%, but that number is subject to change with little warning. Trump announced much larger reciprocal tariffs on dozens of countries in April before instituting a 90-day pause. Trump also raised tariffs on China to 145% before lowering them back to 30% for most Chinese goods for at least 90 days starting in May. To handle the tariff whiplash and survive in today’s volatile political and economic climate, you need to navigate constant uncertainty and adjust to frequent disruptions. If you’re not able to pivot quickly as changes arise, you may have to pass rising costs onto consumers, putting your business at risk of losing them entirely.

Related: Walmart Is Raising Prices, According to the Company’s CEO. Here’s When.

To stay ahead of these constant changes, business owners need to regularly explore a range of “what-if” scenarios. For example, if tariffs rise on a key supplier, how quickly should I adjust prices? Or, what are my options for switching to a supplier in a country with lower tariffs? With so many moving parts, AI can make this easier. Tools like ChatGPT make it simple to start using AI for financial modeling and supply chain analysis —helping you stay agile while navigating unpredictable tariffs.

How small businesses can use AI for smarter scenario planning and future-proof decisions

Earlier in my career, I helped large oil companies and financial institutions optimize their supply chains for better efficiency and lower costs. Traditionally, creating these models required complicated Excel spreadsheets and some proficiency in mathematics. Not only has AI made the modeling process more accessible, even for non-technical business owners, but it has also provided business owners with an essential tool for scenario planning that is adaptable in real time.

Tariffs are fundamentally unpredictable, especially today, so AI can’t predict what tariffs will be tomorrow, next week or next month. It can, however, help your business prepare for the unknown and make smarter decisions faster by running dozens of those “what-if” scenarios in seconds. That’s why it’s best to understand and use AI as an optimization model instead of a one-time solution.

Here’s how the optimization model works and how you can use it to build a pricing and procurement strategy that will help your business stay on top of 2025 tariffs:

Step 1: Provide your AI tool with data

Start by entering the key details into your AI tool—some of which your Large Language Model (LLM) may already know. An LLM is a type of AI that understands and creates human-like text by learning from vast amounts of writing.

Include information like:

• Current and projected tariff rates
• Domestic and international costs of goods
• Inventory holding periods
• Revenue per unit

This data is likely already available in your balance sheet, which you can quickly upload to your AI tool like ChatGPT or source through simple research. The AI’s goal is to optimize for a combination of these variables that yields the highest profitability at the lowest cost at any given point.

Related: What Is a Tariff? Here’s an Overview of the Basics.

Step 2: Use AI to model supply chain alternatives

AI can scan trade databases and tariff announcements in real time, constantly updating teams in need. As tariffs fluctuate and updates are tracked, your optimization model will shift and evolve.

For example, if tariffs rise and the cost of overseas products increases, you may look to purchase goods domestically and ask your AI system to recommend sourcing alternatives. AI can even compare the benefits, drawbacks and long-term implications of sourcing from various countries.

While AI can’t provide specific pricing or shipping estimates, it drastically reduces the time it takes to evaluate new options. Once you find the rest of the information you need, by researching online or calling the suggested companies directly, feed it into your model to update your strategy in real-time.

Step 3: Use AI to explore multiple scenarios and identify the best path forward

Beyond just helping with sourcing decisions, AI can also recommend how much you can raise your prices to stay profitable without driving customers away. For example, your business might absorb a 5% to 10% tariff increase through modest price hikes, but a 15% increase could start to push customers away. AI can simulate different pricing strategies to help you find the perfect balance for your unique situation.

Ask your AI tool questions such as:

• How much would I lose if tariffs remain between 10% and 15% over the next 60 days?
• When does buying from international suppliers become economically unviable?
• How much would I need to raise prices if tariffs increase to 20%?
• What’s the best price increase to keep my revenue steady while covering costs?

AI can help pinpoint various thresholds and calculate your options. These actionable insights can be life-saving for businesses lacking the time, energy and resources for trial and error.

Think of AI as a personal financial analyst that works around the clock and costs a fraction of a human hire. Regardless of your business, integrating AI into your operational toolkit and interacting with it daily can help you prepare for an unpredictable market.

While the future of tariffs remains uncertain, their impact is very real today. Instead of freezing up from uncertainty or making hasty decisions, AI empowers business owners to stay proactive and ready for whatever comes next.

Behind every digital product — whether it’s a mobile app, a web platform or a SaaS tool — lies a foundation of tools and technologies that determine how it’s built, how it scales and how it survives. This combination is known as the technology stack: programming languages, frameworks, infrastructure, databases and more.

It’s not an exaggeration to say that the choice of tech stack is just as critical as the product idea itself. No matter how innovative the concept, poor technical implementation can quietly — and quickly — destroy it.

For non-technical founders, the tech stack can feel like a black box — something the dev team just “handles.” But here’s the trap: early choices often seem fine. Then months later, you realize you’ve built something fragile — a product that’s hard to scale, expensive to maintain and nearly impossible to upgrade without breaking everything.

Founders often make early tech decisions based on what feels most practical — what’s fast, affordable, or easy to build with. And in the short term, that works. But the real danger shows up later: when the product can’t scale, breaks under pressure or becomes too costly to maintain.

Here are four common traps I see founders fall into — and how to avoid them before they slow you down.

The clock is ticking

Roughly one-third of the product rescues we’ve handled stemmed from stack-related issues, and the next case of a proptech startup is not an exception

This startup had chosen Rust for its core logic and Xamarin for its mobile app. Rust, while powerful and high-performing, isn’t well-suited for products that require fast iteration and flexibility. Xamarin, meanwhile, was discontinued in 2023, meaning the app was essentially outdated before launch.

Worse still, the architecture relied on heavy client-side processing instead of server-side logic, leading to major bottlenecks as usage grew. Performance dropped, data became fragmented across devices and the system started to fall apart.

Their options? Rebuild the system entirely — or replatform with a different stack. Both costly. Both painful.

How bad stack choices show up

By the time stack-related issues become visible, the damage has often already spread to other parts of the business. Here’s what that looks like:

• It’s difficult to attract and retain talent. There are very few developers using this outdated/rare language or framework. Another option — they are either incompetent or overprice the services due to the shortage of skilled specialists in the market.
• There’s no room for future startup scaling. One day, you find that the tech stack you used to build the minimal viable product (MVP) or prototype suddenly becomes unsuitable for adding new functionalities, increasing users or handling server load.
• You’re patching holes instead of building. While you’re constantly fixing bugs and makeshift solutions due to poor documentation or lack of community support, you’re not investing in new features. This directly impacts your time-to-market and gives competitors a head start.

Related: You Can Unleash Maximum Efficiency and Streamline Your Processes By Doing This One Thing

4 stack traps to avoid

Too often, stack decisions are made for short-term reasons — cost, speed and convenience. But the real threat is long-term: lack of scalability, maintainability and flexibility. These are the four most common patterns I see founders fall into:

1. Choosing familiarity over expertise

Many founders default to working with friends, former colleagues or the most “comfortable” dev team — even if they’re not experts in the tech their product really needs.

The result? Outdated or inappropriate tools get used because “that’s what we know.” When things start to break, personal relationships make it harder to course-correct. Loyalty shouldn’t outweigh good judgment.

2. Chasing trends without understanding

Just because a language or framework is trendy doesn’t mean it’s right for your product. Some technologies surge in popularity but lack mature ecosystems or long-term support.

When hype-driven choices meet real-world complexity, things fall apart. And if your core developers leave, finding replacements becomes a scramble — or worse, impossible.

3. Overengineering or cutting too many corners

Founders usually fear one extreme but ignore the other. On one end: slap-together MVPs that don’t scale. On the other hand: overly complex architectures (like microservices for a simple app) that waste time and money.

Either way, you end up with tech debt that drains resources or forces a total rebuild — both of which are avoidable with better planning.

4. Letting budget dictate your stack

Early-stage startups naturally watch every dollar. But choosing the “cheapest” path — low-code tools, no-code platforms, or underqualified vendors — often costs more down the line.

Some dev shops push specific technologies not because they’re right for your product, but because they’ve got idle teams waiting to use them. That misalignment leads to slow progress, mounting technical debt, and brittle systems.

Related: Why Your Business Should Simplify and Consolidate Its Tech Stack

Final words

If your startup has high stakes — whether it’s investor commitments, aggressive scaling plans or a complex product roadmap — don’t gamble on guesswork. I always recommend consulting an experienced chief technical officer (CTO) or technical advisors before making irreversible decisions. In technology, as in business, making informed choices from the start is what separates success from failure.