The Smarter Web Company has sold a portion of its Bitcoin treasury to repay an $11.7 million convertible debt facility held by TOBAM, a move the company frames as a choice for balance-sheet flexibility over equity dilution.
The company sold 177.8909127 BTC at an average price of $65,762 to retire the instrument, known as the “Smarter Convert,” ahead of schedule. The transaction totaled $11,698,540 and was settled roughly two weeks early. After the sale, Smarter Web still holds 2,700 BTC in treasury.
Smarter Web’s financing decisions
On its face, a Bitcoin treasury company selling part of its holdings can read as a signal of weakening conviction. But the transaction is a debt-management decision.
Smarter Web was not exiting its Bitcoin position. It used BTC to extinguish a debt obligation and avoid issuing 7,718,551 ordinary shares, an outcome that would have diluted existing shareholders had the convertible converted into equity instead.
Bitcoin treasury companies typically generate headlines in one direction: a purchase, a rise in total holdings, a deeper commitment to Bitcoin as a balance-sheet asset. Investors respond according to their view of corporate crypto exposure, but the pattern is usually additive.
Smarter Web sold Bitcoin to settle a specific financing instrument, the company said. That is different from a sale driven by lost confidence in the asset, and different again from a forced sale tied to a liquidity shortfall.
The company faced a capital-structure choice. It could leave the convertible in place and risk dilution from a future conversion into shares, or it could draw down part of its Bitcoin position to repay the debt directly. Management chose the second path, prioritizing a cleaner balance sheet over preserving the full Bitcoin position.
For shareholders, the logic may be more legible than the alternative. A new issuance of millions of ordinary shares carries a direct and immediate dilutive effect on per-share value.
A reduction in Bitcoin holdings, by contrast, leaves the company’s per-share equity structure untouched while removing a fixed liability from the balance sheet.
Smarter Web’s remaining 2,700 BTC treasury indicates the company has not abandoned its Bitcoin strategy. The sale addressed one financing obligation, not the broader thesis behind the holdings.
There’s something to be said about the reality of how helpful AI can be within running a business, and as someone who has been on the hunt to discover this for themselves, I speak from experience when I say that the path to AI-run success is not exactly what the internet makes it out to be.
A few months ago, as a business owner myself, I became consumed with the idea of building something truly special with AI assistance a real, legitimate business with actual revenue generation but I couldn’t find any real information on what the actual process of doing this looked like
Most articles written on the subject were either promotional pieces for SaaS tools or sensationalist opinion pieces focused on how the technology could replace humans in the workplace; no one actually seemed to want to discuss the day-to-day reality of building an AI-driven company and what it actually meant to run such an entity. Thus, I set out to answer these questions for myself, and in this piece, I’ll do my best to relay what I learned without pushing any particular tool or method as being somehow superior to the rest.
Image generated by ChatGPT
What Does it Mean to Build a Company with AI?
When I set out on this journey, I didn’t have a business plan. I had an idea, a hope, really that perhaps a single individual with the right tools could be able to achieve the same results as a small, mid-level team.
I had seen too many companies waste money and resources on tasks that a competent individual could complete and struggled to find much in the way of viable options for streamlining my own processes at the time, and so that’s what drove me to seek out information on how to build a company with AI assistance in the first place.
The truth is, I didn’t have a particularly strong grasp on what exactly it meant to build a company in this way at first — a majority of people don’t. What I failed to realise at the time was that to build a truly digitalised, AI-driven company meant to adopt a fully digitalised approach to every aspect of my own operations as well.
In practice, this looked like research and validation became a continuous, daily process rather than an event that only happened occasionally — content writing became exponentially faster and far more experimental, as I could churn out ten different headlines for the same article in the same day rather than spending a week agonising over a single one, customer communications became far more immediate and efficient, and administrative tasks that previously bled into my entire day were consolidated into far more manageable chunks that took up, altogether, less than an hour.
It’s important to note, however, that none of this eliminated the need for judgement or critical thinking within my own operations — I simply replaced my own repetitive, time-wasting tasks with those that could be automated, which ultimately gets to the root of what I feel is the most important lesson within the entire experience in general.
The Lesson that Not Everyone Talks About
When it comes to actually learning how to build a company with AI assistance, I think the most important lesson to be learned is that AI doesn’t do the work for you it only removes the roadblocks that previously kept you from doing the work you needed to do at an acceptable pace.
My early experiments with AI were riddled with failure emails that I sent to prospective clients had been generated by AI and were immediately off-putting due to their robotic nature; market research conducted by my chatbots turned out to be wildly inaccurate when cross-referenced with actual data from other sources, etc. In the end, none of this was actually AI’s fault it simply reflected that people who are using these tools tend to make the same mistakes over and over again, and those mistakes are usually process-related. If you rush through the process of generating content, you’ll end up with content that sounds rushed. If you fail to fact-check your research, you’ll end up with research that’s full of easily avoidable errors.
So, Can You Actually Build a Company with AI Assistance?
Yes, but not in the way that most people seem to think
You can’t magically outsource your own judgement or decision-making to some magical algorithm, but what you can do is automate the drudgery of actually executing on an idea to let your brain focus on the more important tasks that require thought. The companies that have successfully utilised this method in practice have done so by building proper feedback loops into their processes and never putting out any work without first double-checking the AI’s work to ensure it meets their standards.
In essence, these companies know that the best way to use AI assistance is to treat any work that comes out of it as a first draft of something that will eventually need to be reviewed by a human being — this way, they’re able to maintain quality control throughout their operations while still enjoying the benefits of increased productivity and decreased overhead. It’s a delicate balance, but with the right approach, it’s entirely possible.
What Would You Say to Someone Considering This Approach?
If you’re reading this article, odds are you’re considering learning how to build a company with AI assistance one day, and so I urge you to think carefully about exactly what it is you hope to accomplish before investing too much time into learning the ins and outs of these tools.
Above all, I think it’s important that you realise that the end goal should always be a company that only requires your own brainpower to make decisions. Ideally, most of your daily tasks should be automated so that you only have to spend minimal amounts of your own time on them throughout the day.
Start small: take one repetitive task from your own operations and plug it into an AI-powered program before you try to scale up and automate your entire business at once and be prepared to spend some time troubleshooting before you begin seeing results. After all, the companies that will end up succeeding in this space aren’t the ones that claim to be “100% AI-run,” but rather the ones that use the technology as a tool to move faster than everyone else while keeping a close eye on what needs to be improved in their own operations.
This is the reality of learning how to build a company with AI assistance, and I hope that this piece serves not as some magical end-all-be-all guide, but rather an informative look at the actual process that people rarely ever seem to talk about, as well as an actionable starting point for anyone who wants to begin exploring the benefits for themselves.
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