Business

What does it really mean to be an Entrepreneur?

Published

3 years ago

May 18, 2022

We see that word a lot, especially in the business world. Entrepreneurship is an idea that is often tied to the concept of the American dream. An individual chooses to put their head down and work hard to open a business and are now reaping the benefits of investing their time, money, and energy.

For those of us who have a job in the traditional sense working for a company that we do not own, the idea of becoming an entrepreneur can be both exciting and intimidating. Not everyone is built to start a business and pour their soul into helping it grow and become their main source of income. So what does it really look like to be an entrepreneur in 2022?

Betting on yourself

Anyone who has started a business themselves will tell you that the key to success is believing in yourself, as cliche as that may sound. With all of the responsibility of the business falling on your shoulders, there is a lot of weight that you have to carry. Figuring out the product or service itself, marketing the brand online or through your network, and handling the logistics of owning a business are just some of the tasks that will fall on you. Depending on what industry you are in, you may need to take the time to be certified, especially for some trades where a license is required. Getting through “impostor syndrome,” or the belief that you do not have what it takes to achieve your goals, will be key to creating long-term success, but this is only possible if you truly believe in your abilities and your business.

Assuming all of the risk

The scariest part of being an entrepreneur is the inherent uncertainty. Will your business be successful? How long before you start to turn a profit? Will this business be able to support your livelihood both in the short term and in the long? These are questions that you will undoubtedly face as a business owner, especially early on. All of the risk associated with owning a business is yours. The best way to manage this risk is to seek assistance in the areas that you feel uncomfortable in. Don’t understand how to keep track of clients and invoices? Research the best software to help you. Having trouble with taxes? Hire a tax professional to work through the details with you. There will likely be aspects of owning a business that you will not even know exist, so be sure to do your research.

When starting out as an entrepreneur, embracing a mindset of continuous learning and adaptability is crucial. Stay curious and be open to new ideas and perspectives. Surround yourself with a supportive network of fellow entrepreneurs and mentors who can provide guidance and share their experiences. Additionally, seek opportunities to enhance your entrepreneurial skills through workshops, courses, and networking events. Explore more helpful tips and discover the ways to be an entrepreneur that can set you on the path to success.

Reaping all of the benefits

While there is significant risk associated with entrepreneurship, there is also the possibility of success. In the event of success with your business, you will reap all of the benefits of your growth. Whether that means achieving financial independence, or simply living out a purpose and feeling fulfilled, you receive the full reward as the owner of that business. This is what most entrepreneurs keep their focus on and what gets them through the long hours and extreme investment of their assets. They look forward to the day when they reach their financial or personal goals, which makes the whole journey worth it.

The freedom of choice

This factor is especially evident with the wave of new businesses that have started since the beginning of the global pandemic. A huge number of workers have filed applications for new businesses in the last few years, with over 551,000 applications in July of 2020, a huge jump from similar time periods in years past. That trend has continued into 2022, with many workers leaving their regular jobs in order to pursue entrepreneurship. One of the main draws is the freedom of choice. You can choose what type of business to run, what product or service you will sell, what your company culture will be, where to allocate resources, and even what hours to work. People may have left previous positions for any number of reasons such as low pay, feeling undervalued, poor management, long hours, or simply burnout. By starting a new business, an entrepreneur has the freedom to customize the role to suit themselves. Even if there are long hours, the feeling of self-determined fulfillment can override the difficulty of running the business.

Entrepreneurship should not be taken lightly

As stated before, becoming an entrepreneur is not for everyone. Even if you come up with a great idea for a product or service, you may not have the capacity or the drive to turn it into a thriving business. It is important to spend time in reflection and doing research before taking the leap to make sure that you understand what you are getting into and what it will take to be successful. Lay out your goals, come up with a plan, seek outside advice from people who know you and professionals in the field you are interested in, and then make a decision. If you choose to go for it, then be ready to defeat that impostor syndrome.

Business

MetaWorx: Building Full-Stack AI Teams, Not Just Automation

Published

6 days ago

June 6, 2025

Matthew Wiles

Automation still dominates most headlines, yet the returns often fail to meet expectations. A sprawling chatbot rollout might shave a few support tickets, but it rarely shifts the profit-and-loss statement in a lasting way.

McKinsey’s 2025 workplace survey pegs AI’s long-term productivity upside at $4.4 trillion, but only one percent of enterprises say they’ve reached true “AI maturity.” MetaWorx, a Dallas, Texas-based AI employee agency founded by Rachel Kite, argues that the shortfall has nothing to do with models and everything to do with people.

“Treat AI like a point solution and you’ll get point-solution results,” shares Kite. “You need a roster that can carry the ball from raw data to governance, or the whole thing stalls at the proof-of-concept phase.”

The pod blueprint

When a plug-and-play automation script collapsed under real-world data drift, costing Kite a lucrative contract, she sketched the six-person “pod” that now anchors every MetaWorx engagement:

An infrastructure architect to tame compute costs.
A data engineer to secure and shape pipelines.
An applied scientist to prototype models against live feedback loops.
An MLOps engineer to automate rollback and retraining.
A domain product lead translates forecasts into features users actually notice.
Ethics and compliance analysts to stress test outputs for bias and keep the audit.

The team’s first sprint still delivers a quick-win bot — “small enough to calm the CFO,” jokes Kite — but the roadmap quickly pivots to reliability, explainability, and eventually optimization. By tying every algorithmic decision to a quantifiable business metric, the pods turn AI from a science project into a growth lever.

Recruiting for curiosity, not credentials

With Bain & Company predicting a global AI-skills crunch through 2027, MetaWorx has stopped chasing unicorn résumés. Instead, it hires “adjacent athletes”: a computer-vision PhD who hops from medical imaging to warehouse surveillance, or a former journalist who recasts her nose for story into prompt-engineering finesse.

“Domain expertise expires fast,” Kite says. “What doesn’t expire is the instinct to ask better questions.” The result is a lattice of overlapping skills that stays flexible when models wander into the long tail of edge-case data.

A culture of rapid experiments

Inside MetaWorx, every idea faces the same litmus test: ship something — anything — into a user’s hands within 21 days. The “three-week rule” forces prototypes into the wild early, where failure is cheap and feedback is swift. Post-mortems, including cost overruns, are circulated company-wide, erasing any stigma associated with missteps.

That laboratory mindset powers velocity. “Our first model is almost always wrong,” Kite admits, “but version 1.0 is the tuition we pay for version 2.0.” The philosophy echoes her TEDx talk on resilience: progress is iterative, not heroic.

How leaders can steal the playbook

Executives itching to replicate MetaWorx’s results don’t need a blank check. Kite offers a five-step sequence:

Inventory pain points, not tools: Walk the P&L line by line and tag the friction you can measure.

Map the stack to the problem: A recommendation engine, for instance, requires behavior data, retraining triggers, and feedback capture — automation alone won’t suffice.

Stand up a pod: Reassign existing talent into a cross-functional tiger team before hiring externally; the chemistry test is free.

Measure the story, not just the statistic: Pair model accuracy with human-scale metrics like ticket backlog or employee churn.

Budget for the boring: Reserve at least 30 percent of spend for MLOps and governance; Stanford’s HAI review links most AI failures to neglected upkeep.

Taken together, those steps shift AI from a pilot novelty to an operational habit that compounds value rather than topping out after an initial PR splash.

Character still scales faster than code

MetaWorx plans to double its headcount this year, yet Kite insists the secret isn’t a proprietary framework or a monster war chest. It’s credibility. Clients see a founder who has wrestled with the same outages and surprise bills they face. That authenticity converts skeptics faster than any algorithmic novelty.

“Tools level out,” Kite says. “Culture compounds.”

The insight lands in a marketplace still dazzled by generative fireworks. Yes, MetaWorx ships models and dashboards, but its true product is a mindset: resilience over rigidity, questions over credentials, experiments over edicts. In Kite’s world, automation is merely the appetizer. The main course is a full-stack team that knows why the model matters to the business and who owns its success after launch day.

And that, Kite argues, is how AI finally graduates from cost-cutter to growth engine, one curious pod at a time.