The TL;DR (“too long, didn’t read”) version: Corporations and LLCs are the best choice for almost all new businesses, and Startomatic can get yours formed with no guesswork and no headaches.

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Photo by Vladislav Babienko on Unsplash

Most founders have some idea of the variety of legal forms that they have to choose from when creating their new company. Who hasn’t heard of a corporation or a limited liability company (LLC)?

Only slightly less recognizable are entities like general partnerships (GPs), limited partnerships (LP’s) , sole proprietorships, and non-profit corporations.

And what about those more “exotic” choices — professional corporations (PCs), professional limited liability companies (PLLCs), and even limited liability limited partnerships (LLLPs) (holy cow)?? …

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Photo by Danielle MacInnes on Unsplash

Entrepreneurship, while always a cornerstone of the U.S. economy, is emerging as the dominant force for growth amid global economic and technological trends which are changing the very nature of work.

This manifesto describes some of the empirical observations and resulting ideas, developed by Robbie and Andrew over years of watching, advising, and building many companies. These tenents guide how Startomatic is built.

Entrepreneurship is not a risky leap of faith, but a viable career path

Entrepreneurship suffers from a number of widely held misconceptions, chief among them that it is an extremely risky pursuit, suitable only for either those with nothing to lose or those with the means to survive a complete failure. …

Startomatic, a software-as-a-service company, launched in what might euphemistically be called an “eventful” time — the first week of June, 2020.

It would be understandable if you were to ask, why? Why launch a software business in the middle of a global pandemic and the largest social unrest the U.S. has seen in fifty years?

Do we think Startomatic can right all of the wrongs of the world?

Do we think Startomatic can spark a real change in the lives of people challenged — or devastated — by systemic racism and the COVID-19 pandemic?

Here’s how we get there:

1. Entrepreneurship is not a level playing field, and never has been. African Americans and other racial minorities in the U.S. have long been at a disadvantage when it comes to starting a business. Though minorities make up 32 percent of our population, minority business ownership represents only 18 percent of the population. There is a significant disparity when it comes to access to capital, contracting opportunities and other entrepreneurial development opportunities for minority-owned firms. …

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Way back in the mid-nineties, when the aw-shucks drawl of a charismatic Arkansan named William Jefferson Clinton was the reliable soundtrack of the nightly network news (which people actually used to watch!), one little known entrepreneur was casting about for a name for his new online retail business.

He first landed on “Cadabra”, presumably an uninspired play on the magical mainstay abracadabra, and went so far as to incorporate his new company with that name.

But when someone misheard “Cadabra” as “cadaver”, he renamed the venture “Relentless” and bought, prepared to forge ahead under the new brand. …

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Startomatic Inc. takes all of the tasks required to launch a business — from choosing a name and logo, drafting and filing legal documents, securing a domain name, creating a website, and setting up company email and social media accounts, just to name a few — and rolls them into Startomatic LAUNCH — a single, user-friendly platform with an overlay of easy-to-understand guidance.

Startomatic OPERATE then provides affordable, ongoing business support in a monthly subscription service with a customizable library of common legal documents, advanced website builder, SEO and DNS tools, trademark search, custom logo generation, and more.

Startomatic is offering LAUNCH to the first 500 companies at the discounted flat fee of $299 (normally $499) plus state filing fees, which range from $150-$300 in most states. That means entrepreneurs can get a new business formed and online in 48 hours for much less than most attorneys would charge for a couple of hours of work, to say nothing of the individual costs of things like logo design, domain registration, and website design, all of which are included in Startomatic’s flat fee. …

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Photo by Naresh Nayak on Unsplash

Deep learning has been the sexiest term in machine learning. For business leaders accustomed to taking a “deep dive” on an issue, or imagining a marine explorer surveying the ocean’s depths, the term deep learning implies that it is the best, most advanced technique available.

Moreover, deep learning involves the creation of “neural networks.” Separate from its actual meaning, the term is a marketer’s dream, since it semantically associates the technology with the power and mystery of the human brain.

In reality, deep learning and neural networks are poor substitutes for the fullness of the human brain, and they need not be so mysterious. While variations of deep learning are the most advanced techniques for tackling several types of problems, deep learning has some limitations, and it’s not the best technical solution in every case (including for the aforementioned client). In this article, we’re pulling back the curtain. Once you grasp a few key deep learning concepts, you still may choose to embrace the term for marketing purposes. But at least you’ll have a clearer understanding of what it’s all about. …

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Photo by Susan Holt Simpson on Unsplash

Given the attention machine learning has received and the sophisticated problems it is solving, it may seem like magic. But it is not. It’s built on a foundation of mathematics and statistics, developed over many decades.

One very practical way to think of machine learning is as a unique way of programming computers. Most programming that is not machine learning (and the practical programs that humans have dealt with the most over the last 50 years) is procedural — it’s essentially a set of rules defined by a human. This ruleset is called an algorithm.

In machine learning, the underlying algorithm is selected or designed by a human. However, the algorithms learn from data, rather than direct human intervention, about the parameters that will shape a mathematical model for making predictions. Humans don’t know or set those parameters — the machine does. Put another way, a data set is used to train a mathematical model so that when it sees similar data in the future, it knows what to do with it. Models typically take data as an input and then output a prediction of something of interest. …

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Entrepreneurs are optimistic by nature. They have to be to survive the ups and downs that come along with starting and running a company. This optimism often leads to a rosier view of the future than what plays out.

Entrepreneurs also have to manage employees. If most employees knew about the reality of your cash position, or the real reason an employee resigned, or all the negative feedback you’ve heard from potential investors, they may not stick around. This leads to sugar-coated untruths that help paint a slightly better picture for the company’s situation.

Below is a selection of these little white lies I’ve heard repeatedly from entrepreneurs over the years. Heck, I’ll admit I’m guilty of saying some of these myself. …

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I started programming in the mid-90s when I was a senior in high school. Since then I’ve gone stretches in my career where I’d actively code followed by several years where I didn’t write a single line of code as my duties as a CEO took priority.

A few months ago I decided to dust off the terminal because I thought programming could be the creative outlet that I was missing. But could I just jump back into writing code? It had been since 2011 that I wrote any substantial code. Eight years is a long time in the technology world. …

Machine learning projects ultimately come down to delivering and implementing computer code. It’s no surprise, then, that the management of these projects is similar to traditional software development. Software project management is a well understood, well-documented field. If you’re going to do a machine learning project, it’s logical that you’d start with a software development mindset.

In fact, machine learning and traditional software projects are similar in many ways. But the differences are significant enough to completely derail ML projects that hold tightly to a traditional software mentality. …


Robbie Allen

Now: Co-Founder Previously: Co-Founder, Founder

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