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Hiring During a Pandemic

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How is it possible for you to recruit and then hire a few new employees when your business shifted to completely remote work during the pandemic? Here’s a quick look at a few ways to successfully transition your strategy for employee recruitment and hiring.

The Basics

You can’t forget the basics – writing a job description, recruiting, interviewing, and even criminal background checks before hiring someone. We’ll dive a bit deeper into a couple of these, along with how they might change. Others, such as the background checks, should stay the same.

Get the Word Out

It doesn’t matter whether you’ll be looking for an executive assistant or a data entry specialist; if people don’t know you’re hiring, you won’t be hiring anyone. The thing is many people who might’ve been looking for a job before the pandemic hit might simply assume that nobody is hiring, so you need to let them know that you are. Be sure that any open position is listed on your website, but don’t forget to call attention to them on social media and other online venues.

It’s All in the Details

If you do happen to be hiring during a pandemic, you’ll definitely need a well-thought-out and detailed plan of attack for recruiting before you dig in. Remote hiring is an incredibly different experience from hiring face to face, and you have a responsibility to potential employees and to your business to ensure that you’ve got a process that will work. To that end, be sure that you have tested your tech before beginning to hire and ask the people you’re interviewing to check their tech as well. Remember that anything you can do before the interview to ensure that all goes well is a great way to start.

When you send an invitation to interview, be sure you list how the process works and what to expect. Be sure to include all of the vital information, like date, time, and who will initiate the video chat. Provide prospective employees with a link to the actual video meeting, and let them know whether the position will be temporarily or permanently remote.

Keep It Real

Once you’ve written and posted the job description and have enticed people to interview, you need to keep in mind that times are quite uncertain for both employees and businesses. When you hire someone, you need to ensure that your business will support onboarding employees with no modifications or reservations. Be completely conscious of what you’re offering. Ensure the position will be at least long-term if not completely permanent and comes complete with benefits and competitive pay. If you have an inkling that once the pandemic has passed, there might be a shift to working on-site, let them know that up front. Always keep things real, and be on the same page with the people you’re interviewing and hiring.

If your business is hiring, just keep in mind that due to the pandemic and all of the changes everyone has had to make, things might be a bit different from what we’re used to – for both your business and the people out there looking for employment. With things like face-to-face interviews and preceding and subsequent conversations needing to occur via video chat, it may seem even less personal than normal. Just make sure that you adapt any and all necessary recruiting practices to ensure that you keep the employee candidate pipeline as full as possible, and things will continue to go smoothly. 

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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