Business
5 Helpful Tips for Getting Started in Real Estate

Not everyone is cut out for a career in real estate. However, for those who want flexibility, freedom, high income earning potential, and the ability to perform meaningful work on a daily basis, real estate is the perfect landing spot. Here are a few helpful tips you can use to get started:
- Attend Online Real Estate School
Before you start your career as a real estate agent in Dayton Ohio, you have to get licensed. And in order to obtain your license, you have to follow the steps outlined by your state’s real estate commission.
All states have nuances, but the general requirements are the same across the board. You’ll need to take a real estate license course to prepare yourself for the required exams. Thankfully, you can take your 75-hour course online. (Some states require lengthier courses, so do your research to find out what you need to do in order to sit for the exams.)
- Pass Both Exams
The next step is to pass your exams. This includes both the state and national exam.
The state portion of the test will evaluate your knowledge on specific regulations and laws in your state. Most state exams require you to answer 30 out of 40 questions correctly to pass.
The national exam is standardized. It covers a variety of topics, including fundamentals of real estate law, real estate contracts, agency law, appraisals, mortgages and finance, taxation, real estate mathematics, federal laws affecting real estate, etc. There are typically around 80 to 100 questions on this portion of the exam.
- Find the Ideal Broker
Once you pass the exam and you have your license, you need to choose a broker. And this is where many new agents get tripped up.
“Too many new real estate agents think a real estate broker choice is primarily based on commission splits,” real estate professional James Kimmons writes. “It’s not all about the split, as the final in-your-pocket income has to do with many variable services provided by brokers.”
In addition to commission splits, you need to think about how you’ll obtain leads, what marketing and advertising expenses are covered, what the office costs are, mentoring and training, and your level of comfort with the broker (and other agents).
While a broker isn’t technically your boss, he or she can make or break your success early on in your real estate career. Take your time and choose wisely!
- Build Your Network
Success in real estate is all about networking. While you might get lucky and find a broker who occasionally tosses you a lead or two, you’ll typically be responsible for bringing in all of your own clients. And the bigger your network the better.
Use every opportunity in your work and personal life as a networking opportunity. Whether it’s neighbors, friends, family, past work colleagues, or the parents of your child’s friends – the wider you cast your net, the more potential there is for success.
- Wow Your Clients
Once you earn a client’s business, you need to do everything within your power to multiply it. And the way you do this is by wowing them to where they can’t help but refer you to their network of friends and family. But be strategic in how you do this.
“All too often, real estate agents try to impress their clients by using fancy terms or information which can end up making their clients feel uncomfortable,” Mashvisor mentions. “While it’s important to show that you’re knowledgeable and an expert in the real estate market, this alone is not enough. There are tons of other agents out there, so why should they pick you?”
At the end of the day, it’s all about building trust and coming across as authentic. People want to do business with people who they perceive as both knowledgeable and caring. There are plenty of knowledgeable agents, so set yourself apart by adding a human touch.
Build Your Real Estate Business
When you break it down into five simple steps, it makes the process of building a career in real estate sound easy. And while it’s definitely not easy, you don’t have to make it more complicated than it is. By following the path that others have already discovered, you can set yourself up to be successful for many years to come.
Business
MetaWorx: Building Full-Stack AI Teams, Not Just Automation

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.
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