Monthly Income With Dividends In January 2026

Hi readers, 👋

Well, what a ride we’ve seen in the past few weeks.

We are currently navigating the notorious “SaaS Winter,” and the sentiment shift has been dramatic, with SaaS stocks getting crushed everywhere. I’ve shared my take on AI a few times, but since this topic is evolving at such a breakneck pace, I have the urge to share my perspective with regard to the SaaS winter as well.

As a lawyer, I am deeply integrated with AI in my professional life. I’m genuinely impressed by its ability to draft documents, challenge my arguments, and sprint through massive data audits in seconds.

But… the more I use AI, the more I call bullshit.

The “obsolete” myth

There is a persistent narrative that the first professions to be replaced by AI will be coders and lawyers (ouch).

But, if you ask the coders, they’ll tell you lawyers are the ones who are obsolete. If you ask the non-coding lawyers, they’ll tell you not to worry as it’s only the “coders” who are at risk.

Then we hit a wall called reality.

I could tell many stories but you have to buy the short version: my humble experience shows that AI only truly works for me when I am the master of the machine. The moment I step into legal territory where I lack deep expertise, the AI regularly leads me astray or produces straight-up BS.

LLMs are only as good as the data structures they sit on and the quality of the guidance they receive. The more chaotic the data, the more precise the “human-in-the-loop” needs to be. Without the expert at the helm, it’s just a very fast, very confident output generator without any real reliability.

Investing in the “data moats”

From an investment standpoint, I believe this gap between the “AI hype” and the “AI reality” provides us with excellent buying opportunities. I am looking for companies that are already sitting on proprietary data goldmines and have the technical infrastructure to build and roll-out real AI capabilities on top of them.

Yes, I was admittedly too early with my entries into Intuit and Salesforce, but in the long run, that isn’t the deciding factor. I am gradually adding to both positions, and I’m looking to open new holdings in companies like Workday or Cloudflare (not even a real SaaS company in the traditional meaning), while adding to my existing SAP position.

But there’s no rush. In this market, patience is a weapon, and it might take quarters (and IPOs of Anthropic and OpenAI) until the dust settles a bit.

While I believe in the long-term “moat” of these companies, I am not blind to the risks. Given the potential disruptions AI can bring, we are well-advised to stay humble. I will be closely watching the upcoming quarterly figures for any “canary in the coal mine” signs of AI disruption.

Specifically, I am looking for:

• Net Revenue Retention (NRR): Are customers renewing at the same rate, or are they trimming “seats” because AI agents are doing the work of three people?
• Pricing model shifts: Is management talking more about “outcome-based” or “consumption-based” pricing? A sudden move away from the traditional per-seat model could signal that the old SaaS economics are under fire.

I also have one final consideration for very nervous investor:

• In the 2010s, Microsoft underwent a radical transformation that many feared would kill their margins. They moved from perpetual licenses (where you bought a physical box of Office and owned it forever) to the subscription model (Office 365).
• At the time, skeptics argued that customers wouldn’t want to “rent” software and that revenue would crater. Instead, it created the most predictable, high-margin cash machine in history.

Now, we may be on the verge of another shift. As AI agents begin to do the work of humans, the “per-seat” subscription model, which relies on a growing headcount, price increases or upsells, is under pressure. Why pay for 100 seats if AI can help 50 people do the same work? Because of this, I believe we will see a swift transition toward Outcome-Based Pricing or Agentic Infrastructure Pricing:

• Instead of charging you for the user who clicks the button, companies will charge for the outcome the AI achieves (e.g., “per resolved legal audit” or “per automated customer interaction”).
• Just as the move to subscriptions saved SaaS a decade ago, this shift to value-based pricing could actually expand the total addressable market. We aren’t just selling tools to humans anymore; we are selling the labor itself. If a company like Salesforce or SAP can successfully charge for the result rather than the seat, the upside is significantly higher than most people realize.

So long story short: I don’t fall for the doom and gloom. There are plenty ways to make money and great CEOs will figure a way out to do exactly that.

Resilience and risk

As I write this (February 11), my personal drawdown during the past weeks was never more than 2%.

That isn’t even a correction.

It also shows that my portfolio has built up some serious resilience, which opens up the room for a more risk-based approach. It feels like this AI-driven volatility is giving me exactly what I need, right when I need it.

Therefore, I will continue to invest heavily in “beaten-down” SaaS stocks. Alongside those, I’ll keep playing with some “play money” for high-risk, high-reward bets. Kraken Robotics was quite a hit recently, proving that a little calculated risk can go a long way. In January, I purchased another high-risk stock which I will monitor closely. If I see good news, I will add more; if bad news arrives, I will sell immediately.

My monthly income with dividends in January:

My investment approach is simple and consists of three pillars:

• Active income.
• Passive income.
• Conversion.

Dividends fall into the last two categories. They are passive because they provide a cash flow without the need to go to work. Additionally, they are an essential pillar for conversion since they can be reinvested to generate even more income in the future. That is the theory. Now, let’s get down to practice.

This month, my cash-flow approach generated the following income through dividends:

So overall:

• the total monthly income with dividends in January (after taxes) was: € 378.76 / appr. $ 446
• compared to last year, the dividend growth was only ok (+ 1.3 % YoY).
• ⌀ monthly dividend income (ttm): € 710.07 / appr. $ 837
• ⌀ monthly dividend income (ttm) compared to the previous month: + 0.06 %.

Here is the big picture:

The following part is for paid subscribers only. It contains an overview of the stocks I purchased in January and some more portfolio details.

Since this report contains valuable/personal insights, I want to restrict access to paying subscribers only. I invest a lot of time and effort into writing these pieces/researching companies etc..

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Best,