Business
Prophecy Onasis: Taking the industry of advertising & marketing technology to much greater heights

This famous tech mogul has been consistently innovating in the industry of programmatic advertising and he aims to sustain & expand his position as a global leader.
Prophecy grew up a bright kid found himself highly attracted by creative inclinations right from the start. Later he developed a particular liking for media, mainly in the tech and marketing industry. He says, “I have always been driven to be innovative as a child. Whether I was drawing, building anything I always would try to find the crease to do things differently or make things better. I have always had a very inventive mindset.”
Prophecy is a technical entrepreneur working for Vuuzle Media Company as a CTO. He builds online entertainment business models such as native apps and content delivery networks. He has extensive knowledge of programmatic advertising in the monetization of short and long form videos. He is currently working actively with Verizon and its accredited production team for OTT and is also the lead orchestrator of a 3-dimensional content distribution framework for the Vuuzle TV CDN platform, VUMU Music platform, and Clout9.
When it comes to success in the tech world, he thinks staying ahead of the game is important and prides himself on spotting trends before others. He claims that the platforms we use on a daily basis have a profound effect on human psychology that many do not realize. He aims to create new and innovative products that do as little harm possible and that many can utilize for interpersonal experiences every day.
Prophecy is a family man and isn’t shy about expressing how much his children encourage him. He is particularly pleased to share the impact his wife has made on his career and says that she keeps him focused in order for him to continue to perform at the highest level. In an interview he said, “My wife is my best motivator. She truly understands the championship mindset. She does not allow me to hit a low and is my best friend. She is not a woman of opinionated destruction, she understands how to pivot and this is really helpful. What makes our relationship more interesting is my wife was a vet tech working with animals and she pivoted to ad tech about 8 years ago and now she is highly respected as a practitioner in the programmatic advertising space. So we are on the same playing field working now and we enjoy it.”
His exemplary network is reflected in his close partnership with Verizon Media and their accredited OTT production team. He was recently awarded the Brand Blazer award for becoming a pioneer in streaming technology solutions. Although his influence in the sector is notable, he remains modest. His goal is to create valuable tech solutions for society even more through entertainment by building structures that increase communication and self-mastery.
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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