Important Business Tips For AI Startups Devising AI-First Products Amid Latest AI Grant Jumpstart Investment Funds Now Available

Diamond in the rough.

Separating the wheat from the chaff.

Finding the next unicorn.

Those popular catchphrases are all notable sayings that echo endlessly in the minds of keen investors trying earnestly to discover the next breakthrough AI startup.

Prior to my current role as a Stanford Fellow, I readily admit that I was kept awake many a night while serving as a top executive at a major Venture Capital firm by the continual rattling and prattling in my noggin that if we could just look a little further or a bit harder, we would triumphantly uncover the proverbial AI startup keystone needle in an overwhelmingly voluminous and daunting AI products galore haystack.

You have to keep your nose to the grind to spy the winner-winner chicken dinner.

I continue relentlessly to keep on top of the latest in new AI product ideas and AI-based MVPs (minimally viable products). One such trend-spotting approach entails my participating as a pitch judge at numerous AI startup pitch competitions. All manner of both sensible and at times wildly zany pitches arise (for my insights on how to best prepare for and undertake your startup pitch, see the link here).

Zany can be almost okay if the AI product being pitched has a bona fide basis and proffers tangible promise. Meanwhile, some of the AI product proposals are so outstretched and untethered to reality that it makes me and my fellow pitch judges roll our eyes and inwardly cringe.

Shooting for the moon on an AI product idea is fine, though you can’t be betting on the sudden emergence of AI sentience to bring your madcap idea into being. Sorry, but throwing the dice and putting money down on AI sentience is just not in the cards for now. Mindful investors don’t plunk money on the table in hopes that The Singularity shall suddenly and miraculously happen (for my explanation and analysis of the theorized The Singularity, see the link here).

Anyway, for those of you that do have a reasoned and plausible AI startup product idea and perhaps even a demo or proof-of-concept (POC), please know that my heart is with you and I urge you to keep on trucking. You are undoubtedly going to be making quite a herculean number of pitches. It is a daunting affair.

My usual words of encouragement are that each time you get a resounding and resolute “No!” to your pitch, you are eating away at the lengthy list of no’s and gradually persistently inching toward the “Yes!” that will aid your startup in getting further off-the-ground. For my own startups, I eventually lost count at the number of dismally depressing turndowns, possibly a hundred or more, before finally having finetuned my startup and perchance met investors that saw the same impassioned dream that I did.

Newly Announced AI Grant Initiative Underway

I’d like to bring your attention to a recently announced call for AI startups that might be worth giving a look-see. I will explain what the matter seems to consist of. You’ll need to decide for yourself whether this is something applicable to your interests and direction.

Keeping your eyes and ears open is a pretty good trait for aspiring AI entrepreneurs.

You never know what new opportunity is out there and within your reach.

The recently announced effort is somewhat plainly referred to as the AI Grant initiative, see the link here, and actually is an expansion and transformation of an earlier undertaken approach that began in 2017. The forerunner tended to fund AI startups or innovations that were academic or scholarly oriented, spurring new AI research and garnering various research papers and theory-progressing studies.

Now, the latest incarnation seeks to go straight ahead into the making and platforming of innovative AI products. The rubber is decidedly going to meet the road.

Here is the stated mission:

• “Our goal is to find and support the great entrepreneurs who are exploring this new frontier. We want to raise the status of building AI-first products. Research is important, but creating a product that people love on a new platform requires unusual levels of creativity and ingenuity – arguably more so than raising money and spending it to scale up a training cluster. And the rewards to the entrepreneurs who create these products will be enormous” (quoted as per their website).

You might have astutely noted that the desire is for AI-first products.

I’m guessing you might be unsure of what that portends.

Unpacking The AI-First Motto

AI-first is an increasingly voiced motto or slogan that tries to clarify a distinction between the prevalent generic or fundamental AI all-in-one capabilities versus devising AI that consists of a clearly usable and identifiable product. This is especially the case with the advent of Large Language Models (LLMs), which I’ve covered at the link here. By and large, much of the LLM efforts are of a generic or fundamental focus. You would be hard-pressed to illustrate readily how an overarching LLM is itself a viable product or service per se.

Clever entrepreneurs are taking the LLMs and leveraging the AI into products or services that people want or need. In that sense, you could contend that the LLMs are an enabler for devising AI-based products or services. A crude analogy might be that if I showed you how to make fire, the fact that you could produce fire at will is mildly notable. If you then figured out that by controlling the fire you could cook meals, well, you are now harnessing the fire for an entirely utilitarian purpose. You are able to cook and make hot meals for people.

Of course, fire can be harnessed for other uses too. You can use fire to warm up people. You can use fire to ward off bears and wolves. And so on.

As a type of core AI technology, LLMs are malleable and usable for a slew of yet articulated useful and profit-making purposes. Just like the fire analogy, there are loads of ways that LLMs can be leveraged. Realize that many of the LLM insiders are heads-down trying to advance the LLM techniques and technologies. They are preoccupied with the high-tech. There’s nothing wrong with that, and we can applaud them for their devoted energies toward breaking new ground in AI fundamentals.

On the heels of this, the second wave of visionaries is turning LLMs into viable products or businesses that are worthy of investing in.

A pivotal question that I often get at the AI pitch competitions is a classic chicken or the egg conundrum.

The question is expressed usually in this manner:

• Should the LLM be “perfected” first, before you try to use it for a particular use case (i.e., does the use case come thusly after the LLM is already assured)?
• Or should you be thinking about the use case while the LLM is still under development and being progressed, such that they both co-join and integrally emerge?

My answer is that strictly speaking either path can be fruitful, though the generally preferred or “better” path would consist of being in the weeds or inner sanctum of the evolving LLM so that to some degree you can shape the LLM toward the product or service that you have in mind. The issue is that if the LLM is already a circular peg and you want to shovel it thru a square hole, this might not be especially productive. Some entrepreneurs try to turn LLMs upside down to make them fit the desired application or use case. Might work, but usually, this is a bridge too far and savvy investors will realize that something radical is going to have to give.

I should though emphasize that there are more ways than one to fry an egg.

The AI Grant initiative states things in this manner:

• “Some people think that the model is the product. It is not. It is an enabling technology that allows new products to be built. The breakthrough products will be AI-first, built on these models from day one, by entrepreneurs who understand both what the models can do, and what people actually want to use” (quoted as per their website).

Do you have an LLM-based use case that is percolating in your mind?

Perhaps you’ve already been toying with LLMs to ferret out how to implement your envisioned use case. The more that you’ve explored the possibility, the better. I say this because you are likely to have identified what is feasible and what is a bottleneck or roadblock. An idea for an AI product that hasn’t been put through some kind of ringer or gauntlet is bound to be rife for acrid criticism and attacked as either infeasible or impractical.

Try to put your ducks in a row, as much as possible.

Let’s next take a gander at what the AI Grant initiative consists of.

Digging Into The AI Grant Aspects

First, just as an urgent and helpful heads-up, applicants are to submit their application as soon as possible and no later than by October 1, 2022. Time is ticking. Get your posterior in gear and look into this, if the opportunity applies to you.

Second, here’s what you can potentially attain if your application gets chosen as a winner (I am going to excerpt quotes of what the website indicates):

• A $250,000 investment via a no cap, no discount MFN SAFE.
• Spend a week with peers and industry experts at the AI Grant summit in San Francisco in early November.
• $250,000 in cloud credits from Azure, along with other startup benefits, membership to the Microsoft for Startups Founders Hub, and go-to-market support.
• $50,000 in credits from AssemblyAI
• $10,000 in human-labeling credits from Scale.ai

A quick and important point to note is that though this initiative is being called an AI Grant, please note that it in fact is an investment-oriented initiative. I believe that the word “Grant” is a bit of a carryover from the prior effort that tended to entail academic and scholarly research efforts, wherein those ordinarily are covered via grants and not particularly construed as a business investment, as it were.

This latest manifestation is an investment. You will be receiving an overt investment and have investors (if chosen to proceed). Also, for those of you unfamiliar with some of the startup industry lingo, the investment will be structured as a Simple Agreement for Future Equity (SAFE) style, which is relatively common overall, and will purportedly have a clause stipulating a Most Favored Nation (MFN) indication.

Generally, the favored nations stipulation might sound like you are going to be enmeshed into a nation-building exercise, but, no, it just means that the investors at the early stage will ostensibly be anointed the same benefits and rights as those of later investors (else, you see, the early investors might be worried that later investors will get better terms than they did as early birds at the get-go).

As with any occasion where you have a chance to obtain investment and have investors, you’d be wise to have a good startup-experienced attorney and a tax expert in the wings. For this particular initiative, you would only need that advisory capacity if you get selected.

I am though saying that you should be always prepared for these kinds of aspects at any time. Here’s the reason why. Sometimes an investor that you’ve just met is hot to trot, so you don’t want to be struggling to find your own legal or tax advisors to aid you in making sure the contractual matters are in order. A lengthy delay can dampen interest and the investor will drift to another potential investment that seems ready to go. I might also add, that trying to do your own legal work on startup affairs is prone to difficulties (some entrepreneurs think they are a do-it-all including bottle washing and legal work).

You know the old saying, a person that is their own lawyer has a fool for a client.

But, let’s not jump ahead of ourselves. We ought to continue examining this AI Grant initiative and what else you should be contemplating.

How Startup Investors Think

Let me tell you about the rider and the horse.

Having been a VC and now as an angel investor, plus a pitch judge, I find myself repeatedly sharing the insightful line that startups are both a horse and a rider. I realize this might seem a bit of a puzzling metaphorical concoction. Nevertheless, it is abundantly on-target and demonstrably valuable to know about.

Allow me to briefly explain.

The product or service of the startup is the horse.

The entrepreneur or founder is the rider.

A startup consists of a rider and a horse that is trying to compete in a horse race. At some point, the startup comes out of the gate. It needs to get underway. It needs to survive. It needs to thrive. This formidable horse race is going to be a tough one. Muddy and rutty track. Lots of other riders and horses compete to outgun you or push you to the side. Envision a grueling gauntlet ahead of you.

Investors generally want to find what they consider to be the best possible pairing of the right rider and the right horse.

Most people assume that the horse is the only aspect that investors care about (i.e., the product idea). Presumably, you either have a whizbang product or service in mind, or you don’t. The product or service has to be one of those knock-it-out-of-the-ballpark ideas. One in a million. Something so amazing that it knocks the socks off the panel of pitch judges or investors that are anxiously on the edge of their seats to know what the idea is.

Please know that I am not one of those pundits that proclaim ideas are dime a dozen. I don’t go for that. I do though openly agree that ideas are a long way from being something of the reality that works and can make money. Also, the effort to turn an idea into a productive product or service is an arduous and bumpy road. No doubt about it.

Okay, the gist is that the rider of the horse is the presumed spirited force that is going to turn that idea into gold. The entrepreneur has to have gumption. They have to be persistent in the face of long odds. They have to be committed to dealing with all the bruising shenanigans that happen to a startup.

Ideally, in a make-believe world, the rider and the horse are perfect. Each on its own accord is perfect. Combined together they are perfect. Unfortunately, the chances of that kind of double-barreled perfection are extremely low. Investors know this. They know that the probability is that either the rider will be really good and the horse maybe turns out to be so-so, or the horse will be really good while the rider turns out to be so-so.

Assume that in the real world you might need to make your choice on one factor of the two factors, more so than the other. You would naturally and sensibly prefer to make it equally on both. That isn’t usually fully realizable.

Which would a seasoned investor rather do, put their bet on the rider or the horse?

Well, if the horse comes up lame, for whatever reason, the odds are that a great rider can switch over to another horse (such that if the envisioned product or service doesn’t pan out, a shrewd entrepreneur can switch or pivot to something else instead).

In essence, finding a solidly outstanding entrepreneur is a lot harder than you think. Finding good ideas is usually easier. Also, realize that most startups are going to have to pivot throughout their journey. The horse that was envisioned at the start is not necessarily going to be the same horse when the startup adjusts and advances along. Meanwhile, if an entrepreneur is worth their salt, they pivot as needed.

The short answer then is that the rider, the entrepreneur or founders, becomes the focal point for deciding whether to invest or not. The horse, or the outlined product or service, can be somewhat secondary, though I am not suggesting it is not also a huge consideration. All in all, all else being equal, the rider is especially crucial.

This usually comes as a shock to budding entrepreneurs. They look around at pitch competitions and see dozens of other entrepreneurs. As far as their naked eye can see, entrepreneurs are a dime a dozen. The thing is, there are tons upon tons of entrepreneurs that want to be entrepreneurs. There are many fewer that have the right stuff.

Now then, when I tell the foregoing tale of the rider and the horse, I nearly always get someone that raises their hand and says that apparently then the horse, aka the product or service, seems to be unimportant and trivial.

Yikes!

Not what I said.

Just to repeat, the horse and the rider are both vital.

A horse with an insufficient rider is probably going to inspire an investor to find a better rider. The investor will find some other more suitable entrepreneur that has a similar horse and likely go with that combo.

A rider with a lousy horse is probably going to get passed over. This is for twofold reasons. First, the product or service is perceived as being unworkable or ultimately not business-wise profitable. Second, the fact that the entrepreneur thinks that the product or service is viable can be somewhat worrisome. Either they are genius that can see a future that the investor just can’t see, or they are a poor choice at being able to pick ideas that are going to be successful.

That being said, if an entrepreneur shows a spark and appears to be someone that can adequately pivot, an investor will sometimes take them under their wing. The thinking is that perhaps with the right kind of mentorship, the entrepreneur can be eventually paired with a proper fitting horse.

Given all of this talk about riders and horses, we should consider what the AI Grant initiative indicates it is looking for.

Here’s the horse or AI product-oriented element of things (contains a mixture about the rider too):

• “Anything that leverages AI models in a useful or engaging way. In particular, we're looking for technical and pragmatic founders who want to build great products. If you get a thrill from making something that other people love to use, and you understand that building a new product is 1% idea and 99% iteration, we want to support you” (as quoted from the website).

Here’s the rider or founder side of things (along with a bit of the product mixed in too):

• “We're looking for smart and energetic people with actionable ideas that are clearly useful. Demos are a big plus; not just because they're fun to look at, but because they hint at the type of person that cares about the end-user experience, which is ultimately all that matters” (as quoted from the website).

They also provide a handy list of AI-first product characteristics for you to consider when either coming up with your AI idea or putting together a prototype of it (I’ve paraphrased the tidbits):

• Co-pilot model (LLMs that assist humans in performing tasks)
• Utilities atop LLMs (add-ons that for example keep AI from “hallucinating” see my coverage of AI hallucinations at the link here)
• Scaling up LLMs (there are efforts afoot to do 8-bit LLM versions and otherwise reduce latencies)
• AI-first social networks (LLMs that generate content for human consumption via social networks)
• Generative entertainment (LLMs that generate personalized stories, and can produce gaming content)
• Creative workflows (LLMs that can render dozens or hundreds of variants of poses or scripts)
• User Interface for text generation (LLMs with innovative UI capabilities)
• Mobile-oriented (LLMs that work well on mobile devices and enable mobility options)
• Chatbots (we’ve all seen or dealt with bad chatbots, as I’ve discussed at the link here, so find new ways to make chatbots better)
• AI-first knowledge retrieval (using LLMs to find and then customize content for you)
• Other

For those of you that have been possibly scratching your heads about what kind of AI apps can be fostered from the emergence of LLMs, the foregoing list should be instructive to you.

Take a close look and mull over which if any might be your bailiwick.

Furthermore, I find it especially informative when investment opportunities lay out the ground rules of what they are generally looking for. This is useful so that you can right away decide whether your ideas are going to be at least within the ballpark of what is being sought. I also like it when the ground rules are somewhat loose and open, rather than pinning down to the nth degree the particulars of what will be given consideration.

There is always a chance that some really innovative and impressive ideas will come to the surface by allowing sufficient latitude. Not that everything under the sun should then be pitched, but just that the overall latitude and longitude are roughly prescribed.

Getting Your Act Together

Do not just randomly and skimpily pick an AI topic or app idea and decide to run with it.

I’ve seen many AI startup pitches that were entirely off-the-cuff and had no particular rhyme or reason to them. Indeed, the idea for the AI product or service changed five times throughout the course of a five-minute pitch.

Not a good look.

The entrepreneurs that do this are also shooting their own foot, sadly and detrimentally (as if shooting your foot could be done beneficially, seemingly unlikely). I’ve witnessed investors that get quietly perturbed at the total lack of preparation by such entrepreneurs. In a sense, this is disrespectful to the investors and the pitch judges. The message conveyed is that entrepreneur doesn’t think the valuable time of the investors and judges is worth having done proper homework beforehand.

In the case of this AI Grant initiative, take a look at the application form before you start to actively churn away at filling it in if you are thinking of proffering a submission.

You will notice for example that they ask for a short description of your envisioned AI-first product and they ask for a longer version too. They also indicate that if you have a pitch deck, go ahead and include it.

I would strongly urge that you have a pitch deck, ready in hand, even if you aren’t going to be applying to this particular AI Grant initiative. A good pitch deck is a sign that an entrepreneur has thought carefully about their product or service. By putting into adroitly chosen words and accompanied by eye-catching visuals, you are forced into taking an otherwise hazy product idea and making it into something serious and specific.

Merely vocalizing about a product or service and hand waving is not usually of much merit.

In terms of a pitch deck, you should consider adjusting your pitch deck depending on the circumstances at hand. I mention this because some entrepreneurs make one pitch deck and use it until the end of time, unchanged and unaltered no matter what. This usually isn’t very smart. For example, if you have investors that are mainly finance-oriented and not into the AI particulars, you are probably going to want to especially emphasize the financial aspects and underplay the AI aspects. If you have AI-oriented investors and they aren’t much into financials, you had better make sure that your AI aspects get the limelight and you can likely underplay the financials or place them into an appendix.

The right kind of pitch deck for the right audience at the right time.

Let’s get back to the AI Grant initiative and the application.

The application indicates that you should provide a URL to a 1-minute YouTube video introducing yourself and any of your associated founders. This is relatively standard fare these days. It used to be that you would introduce yourself in person at investor events or meetings, but nowadays the odds are that you’ll be asked to provide beforehand a short video of the mainstay entrepreneurs involved.

There are differing opinions about what the introductory video should portray. In the AI field and high-tech overall, usually, the down-to-earth version is the most suitable portrayal. If you were pitching in a marketing or sales realm, you probably would go over the top. In the tech arena, the salt of the earth is generally more apt.

Here’s what the application form says to do in this instance:

• “Please enter the URL of a 1-minute YouTube video introducing yourself (and any other founders). Explain what you're making and why. Do not submit a promotional video; just talk to the camera as if it were another person” (as per quoted from the website).

My having suggested that you should be down to earth is reflected in their phrasing too.

Of course, do not go overboard on being earthy. I’ve had some entrepreneurs that provided videos that were so poorly lighted that their face was not at all visible. It was some shadowy figure speaking into a microphone. Not very enlightening. There have also been instances wherein the audio of the video was a mess, including all kinds of background noises and other distractions, as though the person was recording their video at a playground or in the midst of a circus fanfare and had not thought at all about being heard and seen adequately.

Make your introductory video as sensibly as you can, including sufficient lighting, appropriate setting, sound quality, and visual quality so that you are able to be readily seen and heard.

I sometimes wonder if the entrepreneur watched their video to double-check that it was well-done. Here’s a bit of a kicker. I asked one such entrepreneur about their wreck of a video, and the person told me that they cannot stand watching themselves on video, thus they decided not to watch what they taped. I urged them to get over that hesitation and watch the video, plus ask some friends or colleagues to watch it and provide feedback too.

Enough said on that.

The application also suggests that you should consider submitting a URL of a demo or a video of a demo if you have such content.

Obviously, if you have not yet produced a prototype or something akin to it, this can be problematic. The instructions mention that you don’t have to have this (it is considered optional), but they also say that applicants will be prioritized for submitting such aspects.

Often, someone will set up a restricted website to portray their AI product in some barebones or demo-using way. It is a simplified version that allows gingerly trying out a few key features. This should be carefully prepared since you don’t want the on-the-fence investor going there to end up in a frozen screen situation or some other maladies arise. Though investors and pitch judges might overlook such guffaws and realize that it is only meant as a show-and-tell, regrettably others might not be so considerate.

Creating a video of your demo is likely to be less nerve-wracking than enabling a live-demo experience by an investor or pitch judge. Here’s why. You can take your time to produce the video. You can edit the video. The video encapsulates what you want the investors and judges to be paying attention to. In contrast, access to an open-ended demo system or prototype could allow the investors or judges to inadvertently wander afield or get bogged down in figuring out what to do.

I realize that an entrepreneur with limited time and limited resources might decry the aspect of having to both create a demo and then film a demo. Yes, that is a lot of potential work.

Also, in the AI field, the chances are that the entrepreneur is more adept at AI development, therefore the demo coding and building are more in their wheelhouse. Making a video of the demo is often less so in their skillset. One popular and generally acceptable approach to making the demo video would be to do a Zoom-like walk-thru and record the walk-thru as you do so. This is pretty low-end and simple to do. I suggest that you practice this several times before making one end-to-end demo video (or, use video editing to splice the demo tape together).

Follow The Money

Money makes the world go round.

Money also has strings attached.

Not all money is the same.

For those of you that have a nascent startup, and upon having wandered along the dusty road of seeking various investors, you are likely to gradually realize that not all investors are the same. Some investors you’ll click with and gleefully share a genuine sense of chemistry such that their funding and your talents all are in harmony as a joyous startup kumbaya (which, hopefully, will carry you and them through the harsh times that the journey will inevitably entail).

Other investors might seem a kilter of your style and aims. Hard decisions sometimes need to be made regarding the source of investment dollars.

My point is that make sure to consider where any investments that you seek are coming from.

In this instance of the AI Grant initiative, the funding is being provided by Nat Friedman, former CEO of GitHub, and Daniel Gross, having run Machine Learning projects at Apple and has other notable accomplishments as well. The two investors indicate that they are investing $10 million into the AI Grant initiative, doing so by establishing a business entity known as AI Grant LLC that carries out the investment efforts for them. The organizing team consists of Evan Conrad (Everyprompt) and Alex Gajewski (Metaphor).

As an enticement for those of you that are already further along on your startup and believe that $250,000 is something you’ve already surpassed as a seed or already accomplished funding round, they indicate this on the website: “If you are raising more than this, come talk to us directly! We're interested in great companies raising between $2M and $200M.”

I’d like to also mention some other useful benefits beyond the monetary investments alone. Consider other potential perks that are sometimes tossed into the treasured pot.

For example, when getting involved with a startup accelerator or incubator, which I’ve served many times as a mentor for coaching founders, you are also going to be rubbing elbows with fellow entrepreneurs. This can be extremely valuable.

You can glean a lot of important tips from your entrepreneurial peers. They also are likely to be willing to give you direct advice based on their own trials and tribulations. They can be inspirational, keeping your spirits high as you deal with startup headaches by the barrel full. If your startup is faltering, these trusted peers can sometimes find creative solutions to keep things going.

In that sense, the AI Grant initiative is somewhat akin to that kind of added value or augmented experience since you will be part of a cohort that is selected to proceed. There is also an anticipated get-together. The chances are quite keen that you’ll make a lot of significant contacts.

There is yet another facet that I often mention to AI founders.

Whenever you manage to win a pitch competition or get an award or receive a grant or investment, all of these are not solely a means of merely keeping your startup underway. They also are highly visible indications that your startup is seemingly worthy and can be a huge sign of confidence for anyone else contemplating investing or supporting your endeavors.

Recall the sage wisdom that proclaims “success breeds success”.

The more that you are able to get successes under your belt, the better off your startup is likely to be. Completely unknown startups are seen as a risky bet. Startups that have gotten some stamps of approval are typically considered more worthy of taking a chance.

Make sure that whatever accomplishments you and your startup do garner, log those accomplishments, and tout them when appropriate to do so. I’ve had pitches made that I asked the entrepreneur whether they have ever made the pitch before, and they surprisingly said that they had done so and won various notable prizes and investor mentoring. That’s the kind of cheerful and supportive news that ought to have been proudly declared upfront.

Sometimes those diehard AI developers are shy and reserved when it comes to the public eye, not willing to toot their horns. In that case, I tell them they can toot the horn of the startup if that makes them feel less uncomfortable about being boastful. The startup can take the credit.

Perceptive investors will know that the entrepreneur is the one that truly earns the praise.

Conclusion

A few concluding remarks.

I’ve tried to share with you a number of entrepreneurial insights about how to get your AI startup underway. I earnestly hope that my remarks about what mistakes are often made will give you some lessons learned so you won’t necessarily need to experience them brutally firsthand.

I profoundly wish you all the best on your founder quest.

Lastly, for now, the famous comedian Milton Berle made this telling comment: "If opportunity doesn't knock, build a door."

For those of you that are into AI, I’m sure that you have had contemplative moments about forging some exciting and groundbreaking innovative AI product or service. This is undoubtedly gnawing away at you. Maybe you need a bit of a favorable word or encouragement to turn your innermost thoughts into something real.

Alright, here you go.

Are you ready?

Get your AI thinking cap on. Come up with an AI-first product idea. Write it down. Mull it over. Refine it. Craft a proof-of-concept or demo. Make a video of it. Make a video about you and any of your fellow founders. Put together a suitable pitch deck. Share this with friends and colleagues that can provide constructive feedback. Adjust. Now bring this to the attention of the world by aiming to get investors interested. There are plenty of avenues for doing so.

So, with those lively words of encouragement, please finish reading this heady discussion and get yourself in gear.

One thing I know for sure, I know you can get it done.