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Square will Provide CBD Payment Program to the US Vendors

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Payment program maker, Square has announced that it is going to launch a CBD early access program. This program will be specially based on CBD sales and will allow vendors in the United States to sell CBD products using Square. The company will also provide businesses with a combined ecosystem for everything vendors need to sell the products. CBD business runners can easily manage their business including payment to hardware, payroll, inventory management and more. Square will also provide complete views of the business with the CBD program.

CBD stands for cannabidiol which is a chemical compound from the cannabis plant. CBD products are available in the market in many forms without THS. People are experiencing a lot of benefits after using these products. CBD vendors are experiencing large customer visits due to the products’ effective results on anxiety, pain and other illnesses. It was legalized in 2018 and Square now wants to make payment tools in the CBD space. This tool will be helpful to start, run and grow the CBD business.

eCommerce companies are receiving payment of CBD products by checks. With Square they could get better rates. Instead of waiting for checks on the mail, the vendors can get paid on the next business day itself. According to Forbes, CBD market is going to become the next billion-dollar industry and will grow by 700% in the next few years. The cannabis industry is projected to reach $50 billion by 2026. It is all due to the CBD products’ effect on the humans to get cured and enhanced.

The idea of Bigtime Daily landed this engineer cum journalist from a multi-national company to the digital avenue. Matthew brought life to this idea and rendered all that was necessary to create an interactive and attractive platform for the readers. Apart from managing the platform, he also contributes his expertise in business niche.

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Business

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

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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:

  1. An infrastructure architect to tame compute costs.
  2. A data engineer to secure and shape pipelines. 
  3. An applied scientist to prototype models against live feedback loops. 
  4. An MLOps engineer to automate rollback and retraining. 
  5. A domain product lead translates forecasts into features users actually notice. 
  6. 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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