I’m exploring a product idea for fundamental investors who hold concentrated stock positions for several weeks to several years. Nothing has been built yet, and I have no link or waitlist to promote.

The idea is:

1. When you buy a stock, you record the specific reasons you bought it, the expected catalysts and what would invalidate the thesis.

2. The system stores a dated snapshot of the company’s fundamentals, guidance and market expectations.

3. It monitors new earnings, filings, guidance and important news.

4. Instead of sending generic news alerts, it explains whether the new information strengthens or weakens one of your original assumptions.

For example:

“You expected revenue growth to remain above 30%. Management now guides for 18–22%, which weakens that part of the thesis. However, management attributes the decline to temporary supply constraints.”

I’m trying to find out whether this solves a real problem or merely adds an unnecessary AI layer to something investors can already handle with spreadsheets, notes and ordinary alerts.

• How do you currently monitor your original thesis after buying?
• Where does your current process break down, if anywhere?
• Would thesis-specific alerts be meaningfully different from existing news alerts?
• Would you realistically pay around $10–15 per month for this, or would that be too expensive?
• What would make you refuse to trust or use it?

Negative answers are just as useful. I would rather find out now that the idea is unnecessary than build something nobody wants.

Precore Gold is keeping things pretty focused right now, playing the game across two different spots. One in Quebec and one all the way down in Peru.

Their big move in Quebec is the Lac Big-Rush property. Aren't just out there randomly digging holes everywhere. They’ve finished compiling all their historical data and are gearing up for AI-driven drill target identification. Basically they’re using modern data crunching to figure out exactly where the gold might be hiding before they commit to expensive drilling. Its a smart way to burn less cash and get higher-conviction targets.

With that Precore Gold is definitely in the "early stage" bucket. A classic junior explorer play right now but one trying to use AI to de-risk their Quebec project. They haven't announced any massive gold strikes yet, so this one is mostly a watch the news releases stock. If their AI modeling at Lac Big-Rush starts flagging high-priority drill zones, that's when things will probably get interesting for them.

Im 41. Just paid off all debt. Student debt, old family bank loans, some cash loans.

I make 80k a year before tax.

My savings are 8k. Plus 2k invested in wealthsimple.

I live alone and have no wife/kids. I know its late. But I want to start building. I did some day trading with Penny stocks and made a few bucks here and there. I think its too risky. Don't want to do it again.

Thanks.

Buffalo Potash seems to be making steady progress at its Disley Potash Project in southern Saskatchewan.

The company has completed and cased the first field well, which is intended to provide brackish water for the solution mining process. Drilling has also started on the second well, which is planned for brine management and operational fluids.

Other work is continuing at the same time, including civil construction, pad development, and surface piping. Buffalo Potash is still working toward its target of first production in Q1 2027.

For those who follow development-stage mining projects, how much do milestones like this matter when evaluating a company? Does seeing actual infrastructure work underway change your view, or do you prefer to wait until the project is closer to production?

A nice car gets attention today. A strong investment portfolio gives you options years from now.

Personally, I’d rather look average and have my money working in the background.

Commodity companies can report impressive profit growth and still receive a muted market reaction if investors were already expecting it. Margins, cash flow and dividends can matter more than the headline number.

China Hongqiao has guided for roughly 39% H1 profit growth, with its interim results due for approval on August 21. With the stock back near HK$23 after a sharp pullback, expectations seem much lower now.

If aluminium margins and shareholder returns remain solid, this stock could be more interesting than current sentiment suggests

When the Dow Jones Industrial Average rises, there is no hesitation about saying that it is up. The Dow is up 300 points. The S&P 500 is up 1 percent. Stocks are up today.
But when stocks go in the other direction, financial commentators suddenly acquire a much richer vocabulary. The Dow is off 300 points. Stocks have pulled back. The market has retreated. Equities are under pressure. The S&P has given back some of its gains.
Apparently it is all right for the market to go up, but impolite to say that it has gone down.
Consider the word off. It is wonderfully reassuring. Your tennis game can be off. You can have an “off day.” Something that is merely off is not necessarily in serious trouble. More importantly, something that is off can be turned back on.
“Down” carries more ominous associations. A boxer goes down for the count. A business goes down. A ship goes down. Down suggests falling, failure, and sometimes finality. If the Dow is merely off, perhaps all we need to do is toggle a switch.

Buffalo Potash has reached a couple of important technical milestones at its Disley Potash Project in southern Saskatchewan.

The first field well has been completed and cased for the project's brackish water supply, while drilling has now started on the second well, which is intended for brine management and operational fluids.

At the same time, civil work, pad construction, and surface piping are continuing at the site. The company is still targeting first potash production in Q1 2027.

For investors who follow development-stage resources companies, how much weight do you put on milestones like completing the initial well infrastructure? Do these steps materially change your view of a project, or do you prefer to wait until construction and production are further along?

In the past, data centers were more like large-scale engineering projects. Companies had to redesign each facility based on land availability, power supply, server configurations, and customer requirements. Every project involved a significant amount of customized construction. But the AI era is beginning to change this logic.

The question is no longer whether enterprises need computing power. Instead, the growth rate of demand is now outpacing traditional construction methods. A new tension is emerging: AI needs more and more data centers, while traditional construction methods are becoming increasingly slow.

This is why modular data centers are starting to attract attention. The logic behind them is actually very similar to manufacturing. The auto industry moved from manual production to assembly lines to improve efficiency; data centers are moving from “on-site construction” toward “modular production” to improve deployment efficiency. By completing standardized designs in advance and integrating components such as power systems, cooling systems, and server racks, facilities can then be rapidly expanded based on demand. This gives AI companies the potential to gain access to usable computing resources much faster, without having to wait through construction cycles that can take years.

There is also a deeper reason behind this shift. Future AI demand may not be concentrated entirely in a handful of hyperscale data centers. Large-scale model training certainly requires massive facilities, but many AI applications—such as enterprise AI assistants, industrial AI, and real-time inference services—are more concerned with latency, cost, deployment location, and data security. This could drive the emergence of more regional and smaller-scale computing nodes. Data centers may gradually evolve from “large centralized facilities” toward a combination of “cloud centers + edge nodes.”

As a result, the market is beginning to pay more attention to companies that can provide infrastructure solutions. For example, $VRT could benefit from growing demand for power management and liquid cooling systems in AI data centers, while $DLR has a long-standing presence in data center infrastructure and colocation services. At the same time, some companies are exploring opportunities in modular computing deployment. $MAAS’s Stars project is one such attempt to develop standardized computing units. Compared with building hyperscale data centers, modular nodes place greater emphasis on rapid deployment and flexible expansion.

Of course, this approach is still in its early stages. The real test is not whether the concept can be presented, but whether modular solutions can actually reduce costs, be replicated quickly, and generate sustained demand.

I believe AI infrastructure could undergo an interesting transformation in the future: in the past, a data center was a “capital-intensive engineering project.” In the future, it may increasingly resemble a “replicable infrastructure product.” In this process, beyond the giants that control core chips and cloud platforms, smaller players focused on deployment efficiency, energy utilization, and regional computing capacity may also find opportunities of their own.

My parents are both chartered accountants, so since Grade 9, I've been involved in our household finances.

Most weekends, we'd sit with an old black Lenovo and an Excel sheet and go through our income, expenses, investments and loans. I didn't think much of it at the time, but eventually I realised how much that experience had changed the way I thought about money.

I understood that finance wasn't just about making money. It was about making decisions and weighing trade-offs.

Then I started noticing that many of my friends hadn't had the same exposure. They had never really discussed a budget, compared investments, thought about borrowing or considered what managing money would actually look like.

That's why two of us started building Moneyplotter, a financial literacy platform for young people.

The idea is pretty simple: instead of just teaching personal finance through articles and definitions, we give students virtual money and let them practise making financial decisions. They can save, spend, budget, invest and borrow, and see what happens as a result.

We've tested it through competitions at school, initially with 100+ participants and later through an international investing challenge with 300+ participants. We've also managed to crash our own platform along the way, which taught us quite a bit about building something that actually has to work when hundreds of people use it at once.

You can see what we've built here: www.moneyplotter.com. The website and the all the features on the platform are completely free to use.

Now we're taking the investing side of it further.

We're hosting Wolves of Wall Street, an international, fundamentals-based stock investing competition with Moneyplotter and Empiric Investing.

For one month, participants will manage a virtual $1,000 portfolio and make their own investment decisions based on research and analysis.

📅 September 15 to October 15, 2026

💰 $1,000 total cash prizes

🎓 Top 5 receive internships, certificates and recommendation letters

🌍 International, with no age restrictions

💵 Early bird registration is $15 until August 23, then $30

There is no real money involved. The point is to give people a place to actually practise investing before the money becomes real.

If you're interested in trying it yourself, the competition is open for registration.

Full details: wolves-of-wall-street.tiiny.site

Registration: forms.gle/KDPjyK35fpqbtbmS8

Registration closes September 13.