The Resilient Entrepreneur, Edition #114
Hi there
I hope you had a great week!
Here are the topics in today's edition:
- Cut Costs, Boost Sales: The Entrepreneur’s Tightrope
- The AI Tightrope: Chasing Wonders or Following Pragmatism?
Please reach out with comments, questions, or suggestions for articles!
Talk soon,
Tom
TACTICS FOR RESILIENT ENTREPRENEURS
Cut Costs, Boost Sales: The Entrepreneur’s Tightrope
In good times, business is easy: Demand and investor appetite are soaring. But what about bad times? Entrepreneurs need to walk a tightrope.
In good economic times, decisions to increase costs are made without giving it much thought. The economy is booming, interest rates are low, and, as a consequence, investors are eager to deploy their LPs’ excess capital.
In dire times, however, investor capital evaporates even faster than your sales pipeline collapses. Your only option to stay afloat in such times is to manage your costs.
Gloomy, huh? Yes. People always think that entrepreneurship is only about growth, success, and glamour. From my own expertise as a founder, I can assure you it’s not. There are at least as many moments of doubt and hardship in an entrepreneur’s life as there are successes.
In this article, let’s look at a core dilemma that might sound familiar to many fellow entrepreneurs: Dire times require you to cut costs, and at the same time, you need to step up your sales activities.
Reducing Your Costs: Doing More With Less
Unfortunately, reducing costs almost always means reducing headcount. That is never pleasant, but it’s required sometimes. At the same time, think of all the organizations you work with, no matter how small or large they are. How many times have you come across people who don’t do anything but keep their chairs warm? I think it’s fair to say that most organizations could cut their headcount by 20% without consequences on output. Don’t get me wrong, it is still unpleasant to reduce costs.
Reducing your costs means doing more with less. That doesn’t mean you will have to work double shifts. It means you will have to focus on what matters most and streamline your processes. That’s not a threat, that’s a chance.
Increasing Your Sales Activities
At the same time as you cut your workforce, you need to step up sales activities in dire times. Even if the economy is not doing well, you need to do everything you can to grow your business. And even if you don’t sell more while the economy is in shatters, at least you will have a full pipeline once the economy recovers.
Sales activities require lots of effort and time. Yes, you need to make this effort with fewer resources than you started with before the cost-cutting.
There goes your dilemma. Because it’s an illusion to say you can do more sales with automation. Marketing works very well with automation, but following up with qualified leads, giving product demos, and answering prospects’ questions still involves people who understand your product and also prospects’ needs.
At the same time, who said you need those people helping you in sales permanently on your payroll? Maybe you can hire a contractor with great connections in a new vertical you’re trying to attack. If your product doesn’t solve a problem in that vertical, you can end the contractor’s mandate without having spent tons of money. If the new vertical helps grow your business, you can always hire that contractor full-time.
Conclusion
Entrepreneurs walk on a tightrope all the time. If you’re not cautious enough in dire times, you’ll fall off the rope. But if you’re cautious all the time, you will not be able to grow your business sustainably.
There is no right or wrong way to manage this dilemma. The important thing is that you are aware of this dilemma, and that you do whatever you can to grow your business instead of complaining about hard times.
STRATEGIES FOR RESILIENT ENTREPRENEURS
The AI Tightrope: Chasing Wonders or Following Pragmatism?
Believe it or not, space exploration is a good analogy for AI developments. And like for space exploration, data separates hype from results.
What kind of emotions does AI evoke in you? A sense of wonder or scepticism?
This isn’t a trick question. I am not trying to pull you into one or the other direction. As always, I’m after that tightrope walk all entrepreneurs have to walk.
Recently, we held a session on leveraging AI tools in Yonder, the B2B SaaS company I co-founded. Before the session, one of our developers shared the keynote from The Pragmatic Summit given by Laura Tacho, titled “Data vs. Hype: How Organizations Actually Win with AI”.
In my humble opinion, this keynote nails the AI tightrope walk. Let’s look into this in detail.
Analogy: Space Exploration and AI
The keynote uses space exploration and AI as an analogy. Both technologies invoked a sense of wonder, but also scepticism.
Landing a man on the moon was about redefining what was possible. At the same time, people were asking why spend all this money to go to the moon when we had lots of problems to solve here on Earth?
As with space exploration, there is a lot of awe around AI: A promise of huge productivity increases. The prospect of all our software code being written by AI. And that, finally, the first single-person unicorn will emerge thanks to powerful AI tools. Similarly, there is a lot of scepticism towards AI in the corporate world: AI tools are costly, they consume a vast amount of energy, and nobody has yet figured out how they can add value to the bottom line.
What Should Organisations Do?
Organizations need to learn to balance the sense of wonder with pragmatism.
And what’s the best tool available to move from hype to pragmatism? Data.
Organizations that are winning with AI are defining clear AI goals and measuring against them. And that’s a clearly distinct approach from the “spray and pray” approach we see in most organizations — give AI licenses to all your employees, and tell them to “adopt AI” in all departments and processes. This will not work.
Let’s look at a specific example: Developer experience, or DevEx. That’s the tools and processes software engineers use to produce and deploy production code — documentation, debugging tools, CI/CD pipelines, etc. Ironically, human software engineers were begging for those tools literally for decades, and management always said no. Now, suggesting to spend money on such tools for robot engineers, everybody screams “yes! yes! yes!”.
Let’s not fuss over this irony; let’s use it to make the organization more productive. Good DevEx tools and processes avoid urgent issues and outages, thereby not distracting developers all the time. They also help to ship products faster and with higher quality.
You see the pattern? In this example, we’re not using AI to fuel the hype; we use AI to fix a system-level problem. And if you fix system-level problems with AI, you’re set to achieve higher revenues, better profitability, and faster time-to-market. But only if you think of AI as an organizational problem rather than a fancy new technology.
What Does It Mean for Your Product?
So far, we’ve been talking about using AI to fix system-level problems in your organization. But what about your product?
Just like space exploration, AI is great, but it costs too much money to use it for everything and everyone. If you can use AI to solve a real problem for your customers, go for it. If you just want to introduce AI into your product because everybody else does, be careful: AI features carry significant token costs whenever they are used.
As a SaaS entrepreneur, I follow the rule that all features that can be solved algorithmically should be solved algorithmically instead of with AI. This helps maintain testability and predictability — remember that AI works statistically, and that results given by AI can slightly vary between executions. In our business serving regulated customers, that’s not what our customers want. Furthermore, running an algorithmic feature on a backend server is much cheaper than paying for AI tokens each time a feature is used.
So what features should you use AI for? I would argue for two cases:
- AI is much better than humans at identifying and visualizing patterns in large data sets. Whenever context between large data sets is relevant for your product, AI can be a real game-changer. Humans will not be able to connect those dots, and even if some bright minds do, they will do so too late.
- Looking back, we had many very specific feature requests along the lines of “can you include some more data columns in this report?”. Whenever a feature needs to be customized for individual needs, AI is way more effective than an algorithmic feature. And if your customers can chat with your product like they know it from Claude and ChatGPT, you will have way fewer customer support tickets.
See that tightrope again? Resist the sense of wonder and follow the pragmatism in product management, too.
Conclusion
Always see AI as a business tool to achieve business outcomes, not just a technology. The core question should always be: Who will pay for an AI feature?
The entrepreneur’s role is to find out which AI features customers are willing to pay for. And if you build AI features that no customer wants to pay for, you end up paying for them yourself.
About Me
I’m a tech entrepreneur, active reserve officer, and father of three — writing about entrepreneurship, leadership, and crisis management from hard-won experience. No AI, no fluff, no promos. Just plain-text insights for people building and leading under pressure.
When I’m not solving problems, I find clarity in the mountains around Zermatt.
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