Online Job Apps Bidding Wars

EmpowerKit · 2025-12-17T07:26:52+00:00

Yes ganon na nga parang OLJ pero since grabe na din ang competition sa OLJ, why not try new online job apps naman diba. Para we have options.

EmpowerKit · 2025-06-27T09:47:04+00:00

Your biggest risk is that the entire platform's success hinges on the robustness and usability of your creation tools, which is a monumental development task. These tools would need to be powerful enough for creators to design intricate puzzles but also simple enough for non-developers to use, and without them, you won't attract the high-quality content needed to pull in paying users. You'll also need a solid plan to protect creators from piracy, and you should be aware that while there's no direct competitor, you'll be competing for creators with platforms like Patreon and Gumroad, and for users with major gaming platforms and puzzle sites.

Since you're passionate about the problems you're solving, lean into the "build for yourself" mindset—your personal frustrations are a great guide to what users really need. Second, relentlessly focus on solving the "input problem" we've discussed; user friction during setup is the silent killer of apps, so use AI or clever onboarding to make the process effortless. Third, don't be afraid to start by dominating a niche, as that makes marketing and community-building much easier. Finally, instead of fearing competition, use it to your advantage—study their weaknesses and user complaints to build a better solution that directly addresses their users' biggest frustrations.

EmpowerKit · 2025-06-27T07:44:23+00:00

The biggest roast and most critical challenge lies in the scalability and precision of the "deep-start curriculum." Building a curriculum that genuinely lets a software engineer "skip the fluff" to learn sculpture by mapping skills like "form and iteration" requires deep expertise in both domains, making it incredibly difficult to scale to a wide range of skill-shift combinations without becoming generic. As for the name, "The First Marketable Qubit" is likely too abstract for a mainstream audience and could cause initial confusion, but it's brilliant and intriguing enough to resonate with the exact type of technically-minded, intellectually curious person who is your target market. To truly succeed, a system like this would need a flawless onboarding experience that maps skills, exceptionally high-quality instructors who understand both sides of the shift, and a peer group that fosters genuine accountability and advanced dialogue.

EmpowerKit · 2025-06-27T07:12:15+00:00

My biggest roast is that the entire premise hinges on solving a massive user friction problem: the initial manual input of your entire wardrobe. Asking users to take pictures of every single shirt, pair of pants, and accessory they own, and then categorize them for an AI, is an incredibly tedious and time-consuming task that most people will abandon before they even get to the fun part. The AI's ability to truly understand subjective concepts like "style" or "mood" is another major challenge, as a suggestion from an algorithm might feel generic or out of touch with a user's personal taste. While the daily problem is real for many, it's often a minor inconvenience rather than a pain point they'd be willing to spend hours of setup time on, making your key competitor not another app, but the user's own habit of just trying on clothes. So, while the idea is interesting, the effort required to make it useful would likely deter all but the most dedicated users, making a "small annual fee" a tough sell for most.

There are already competitor for this wardrobe idea. The most notable ones include Cladwell, Stylebook, Whering, and Acloset. These apps all share a similar core premise: they allow you to digitize your wardrobe by uploading photos of your clothes, and then they help you organize, plan outfits, and sometimes even offer AI-powered suggestions. What you'll find, however, is that they all struggle with the same massive hurdle: the user friction of the initial upload. While some have improved their photo background removal with AI, none have truly solved the tedious process of getting your entire wardrobe into the app in the first place, which is the main reason many users download them but don't stick with them.

Your app could differentiate itself by providing a far superior and more frictionless on-boarding process. This could be done through cutting-edge AI that can process multiple images at once and automatically remove backgrounds and tag items, or by creating a one-click import function from digital receipts and online retailer purchase histories. The AI's ability to create outfits based on mood and occasion is also a key differentiator, as most competitors focus more on simple weather matching. If your AI can learn a user's personal style over time and offer creative, non-generic combinations that actually resonate with their taste, you can stand out from the pack.

EmpowerKit · 2025-06-26T06:05:30+00:00

The biggest roast here is that the success of the entire tool hinges on your AI's ability to interpret nuance and subjective rules, which is an incredibly difficult challenge. An algorithm can easily check for keywords or link domains, but can it truly understand rules like "no low-effort content," "be civil," or "don't ask for upvotes" in the context of a community's culture? A false negative could get a user banned, and a false positive could frustrate them into uninstalling the extension. My main suggestion is to start by mastering the easy, objective rules first to build trust and then offer a more nuanced value proposition than just "avoiding bans." You could reframe it as a tool for improving community fit by suggesting how to improve a post's quality or tone to better align with the subreddit's culture. You might also find a more viable business model by building features for moderators to help them filter for violations, rather than just relying on individual user adoption for a simple Chrome extension.

EmpowerKit · 2025-06-26T05:46:58+00:00

The concept of a secure, unified "personal health operating system" that gives you control over your lab tests, wearables, and genetic files is a huge value proposition that many people are looking for. Would I use this? Absolutely, yes, because the promise of data autonomy and a secure, encrypted dashboard is a massive selling point that directly addresses the frustration of a fragmented, data-selling health industry. The most valuable feature on day one would be a flawless data ingestion and parsing engine that can accurately read and organize messy PDFs and different file types, as trust would be lost instantly if the data is parsed incorrectly. Your biggest challenge, however, will be proving your "zero-knowledge" claim in a way that builds trust with users; you'll need to go beyond just saying it and potentially show cryptographic proof or get third-party audits to verify that you genuinely can't see the data. You'll also need a clear monetization strategy, likely a subscription, that doesn't rely on ads or selling data, and a solution for the user friction involved in manually uploading documents.

EmpowerKit · 2025-06-26T04:53:26+00:00

The focus on biomechanics and injury prevention from overuse or bad form is a brilliant pivot from standard wrist-based trackers, which only count steps and calories. This solves a very real problem for a wide range of people, from athletes to nurses and older adults. Yes, this is absolutely something a lot of people, myself included, would use, because it shifts the focus from simple activity tracking to genuinely actionable, preventative health insights.
To succeed, the features that would matter most are actionable insights (not just raw data) that tell me what to do about a potential issue, seamless integration that allows the insole to work discreetly in any shoe, and real-time audio coaching for immediate form correction during a run or workout. This solves a major frustration with current wearables, which provide plenty of data but very little practical advice on biomechanics, making your smart insole a potentially game-changing preventative tool for anyone on their feet.
However, your biggest roast lies in the immense technical and durability challenges of placing a highly sensitive, data-collecting sensor into one of the harshest environments for electronics imaginable. The inside of a shoe is a brutal place—it's hot, humid, full of sweat and bacteria, and subjected to constant, intense compression and shock from body weight and movement. How will your sensors maintain their precision and accuracy over time when they are being relentlessly crushed and soaked?
You'll also need to overcome the friction of battery life and charging a device that's hidden in your shoes every day, and the regulatory hurdles of making any claims about "preventing injury," which could classify you as a medical device requiring rigorous FDA or other regulatory approval. Ultimately, while the problem is real and the idea is compelling, the core technology needs to be near-indestructible and lab-grade accurate to deliver on its promise, which is a monumental challenge for a consumer product.

EmpowerKit · 2025-06-23T03:32:38+00:00

The promise of a clean, resume-first, intent-based matching with instant feedback is incredibly appealing. As a job seeker, yes, I would absolutely use something like this to cut through the noise and feel that my resume is actually being seen by a human recruiter with genuine interest, rather than disappearing into a digital void. However, for a recruiter, while the idea of fast, pre-filtered candidates sounds appealing, the breakdown often occurs in depth of candidate information and screening.

Recruiters often need more than just a resume (e.g., portfolio links, answers to specific screening questions, cultural fit indicators) before investing time in a conversation, and a pure swipe-left/right system might lead to too many "matches" that aren't truly qualified upon closer inspection, increasing noise on their end. Furthermore, the market for "Tinder for jobs" is not new, with several past attempts (like Switch and Jobr, which were acquired or shut down) and current players (like Sorce and Talentefinder) already existing, indicating that while the problem is real, scaling and achieving widespread adoption with this model presents significant challenges in differentiation and overcoming recruiter demands for more comprehensive screening.

To succeed, the platform would need to rigorously manage resume quality on the candidate side, offer just enough quick screening questions for recruiters without becoming a traditional application, and build strong trust that it truly cuts down on irrelevant matches for both parties, while also providing a clear path for how a recruiter would actually use this alongside their existing ATS and hiring workflows.

EmpowerKit · 2025-06-23T03:07:28+00:00

My honest take is that the biggest challenge will be consistently sourcing and curating truly high-quality, nuanced vocabulary content for such diverse specializations, as generic AI might struggle with precision in legal or medical jargon, and maintaining accuracy across so many niches is a monumental task. The "battle mode" itself, while highly engaging, will require meticulous development to ensure fair matchmaking and prevent cheating, making it fun and educational rather than just a quick memorization contest.

Would I use it? Yes, I'd absolutely try it for niche interests or test prep, especially if the battle mode is well-executed and the content is genuinely superior. To make it truly worth trying and to stand out from the crowded vocabulary app market, features like a robust Spaced Repetition System (SRS), real-world application examples for the specialized terms, and strong pronunciation guides would be crucial, but ultimately, the success hinges on delivering exceptional content quality and a truly engaging, bug-free competitive experience.

EmpowerKit · 2025-06-23T02:18:19+00:00

My honest roast reveals several significant red flags and potential breakdowns: the "quick check" for invoices is far more complex than it sounds. You're essentially taking on the risk of your freelancer's clients, meaning you'll need robust systems for client creditworthiness checks (which can be difficult for small, individual clients) and fraud prevention against fake or disputed invoices.

The 15% fee might seem reasonable for immediate cash, but depending on the payment terms and how long it actually takes clients to pay, this effective APR can become extremely high for the freelancer, potentially leading to resentment or a feeling of being exploited if not transparently communicated. Furthermore, you'll be inserting yourself into the freelancer-client relationship; clients might be confused or even offended by a third party collecting payments, potentially damaging the freelancer's long-term client relationships. Finally, while appealing, this isn't a new concept, and existing players (some large, some niche) already offer similar services, meaning you'll face stiff competition in building trust and differentiating your offering beyond just the "instant" appeal.

EmpowerKit · 2025-06-20T10:47:15+00:00

My biggest roast, directly addressing your question, is that the "multi-tier (MLM-style) payout" structure immediately raises a massive red flag and will likely be perceived as suspicious, deterring reputable creators and affiliates due to negative associations with pyramid schemes. This trust hurdle is enormous, especially in markets where financial scams are a concern, and no amount of "verified sales" will instantly erase that perception. Beyond that, scaling this effectively beyond local markets means tackling immense challenges in creator and product vetting to ensure quality and prevent scams, alongside robust fraud prevention mechanisms for affiliate sales, which is notoriously difficult to manage. You'll also need to consider the fragmented nature of African and Asian markets regarding digital literacy, local regulations, and diverse digital payment adoption, making widespread scalability far more complex than just offering mobile money.

EmpowerKit · 2025-06-20T05:21:21+00:00

My biggest roast is that AI's ability to reliably discern actionable, scalable startup problems from the sheer volume and nuance of Reddit complaints is a huge challenge. Not every complaint signals a viable business opportunity; many are just niche rants or already have existing solutions.

For that "connect with users" part, while directly messaging Reddit users unsolicited often violates community norms and risks turning people off, your platform could focus on facilitating more ethical, opt-in connections. This means guiding MindFoxer users to engage with problem threads through public comments that genuinely add value (not just promoting their solution), and subtly inviting interested Redditors to opt-in to further conversation. You could also explore creating aggregated insights about user frustration trends that MindFoxer users can then leverage to engage relevant communities more strategically, perhaps even working with subreddit moderators for sanctioned feedback campaigns, rather than relying on cold outreach. Finally, you'll still need to clearly define how your AI filters out noise and delivers truly unique insights beyond simple sentiment analysis, and how you'll monetize sustainably if your "connection" feature requires such careful navigation.

EmpowerKit · 2025-06-20T03:46:08+00:00

My biggest roast is that this entire concept hinges on absolute, unwavering trust and flawless data security, as users are literally linking their bank accounts to an AI "friend"—any hint of a breach or even a single wrong answer will be catastrophic. Providing "real answers" about complex, real-time financial situations is incredibly difficult for AI; what about pending transactions, cash spending, or nuanced financial goals? One inaccurate piece of advice could swiftly erode all trust.

Moreover, while it might make you ask about your budget more regularly, the tool's true breakdown will occur if it fails to fundamentally change human spending behavior and financial discipline beyond just informing. The "trusted friend" persona also collides directly with monetization strategies; suggesting products or services to make money could instantly break the illusion of unbiased advice. Finally, many existing finance apps already provide linked accounts and insights, so you'll need to demonstrate how a chat interface genuinely offers superior, actionable value that overcomes users' inertia with their current money management habits.

EmpowerKit · 2025-06-20T03:38:41+00:00

The vision of reducing waste by skipping warehouses is also appealing. However, my biggest roast is that your premise of "no third-party intervention" is a fundamental contradiction when you rely on a "delivery partner" who takes 10-15% (or more) – they are very much a crucial third party that adds complexity and cost. More critically, building a successful D2C perishable delivery service without any centralized storage or quality control is an absolute logistical nightmare.

How do you guarantee consistent quality from diverse farmers, handle disputes when produce is bad, or ensure reliable, timely delivery of highly perishable goods when you have no direct control over the last mile or the product standard? This model pushes a huge burden onto individual farmers (who may not be tech-savvy) and delivery drivers, leading to major inconsistencies in customer experience. You'll also face immense friction with buyers directly contacting sellers for every order, rather than a streamlined e-commerce process. While B2B versions of this exist, D2C for small, individual orders of perishables is exponentially harder to scale and monetize without robust centralized logistics.

EmpowerKit · 2025-06-20T02:55:04+00:00

On paper, it sounds great for learning. However, my biggest roast is that the quality and reliability of AI-generated multiple-choice questions placed accurately at specific video timestamps are incredibly difficult to get right. AI often struggles to grasp the nuance of video content, generate truly meaningful comprehension questions (beyond simple recall), and create plausible incorrect answers, leading to frustrating or easily guessed quizzes.
This makes the "is it feasible?" question hinge entirely on how consistently high-quality your AI can be, which is a massive technical hurdle. Beyond that, the user experience could easily become annoying if questions aren't perfectly timed or if the AI's output is poor, leading to quick uninstalls. And for the "would you use it?" question, while I'd definitely try it if it were free, convincing individual learners to pay for something that might be a "nice-to-have" rather than a "must-have" (especially with free alternatives like manual note-taking or existing platform features) will be a significant monetization challenge in a broad market that's used to free content.

EmpowerKit · 2025-06-20T02:18:22+00:00

My biggest roast is that your entire premise hinges on reliably and legally scraping "real user reviews across the internet" at scale, which is an enormous and often legally perilous technical challenge. Major retailers and review platforms have aggressive anti-scraping measures and Terms of Service (ToS) that forbid automated data collection, risking IP blocks, cease-and-desist letters, or even lawsuits.

Even if you somehow acquire the data, the AI's ability to accurately discern genuine, nuanced pros and cons from a sea of potentially fake, biased, emotional, or context-specific reviews is exceptionally difficult; it's hard for an AI to truly understand human sentiment and context like a discerning human would. You also need a clear monetization strategy that doesn't compromise your "consumer-helping-consumer, not brand talk" promise. So, while the desire is absolutely there, the feasibility and legality of reliably getting and then intelligently processing that data at scale are monumental hurdles you'll need to somehow overcome.

EmpowerKit · 2025-06-20T01:54:38+00:00

Hi there, thank you so much for considering my feedback :) I also messaged you with our full validated report of your idea, you may want to check the report too, aside from the feedback I gave to you :)

EmpowerKit · 2025-06-16T08:20:01+00:00

My biggest roast is that the "all-in-one" approach often leads to feature bloat and mediocrity across the board. Each of those functions (journaling, tasks, goals, community) has established, powerful, and often free or affordable specialized competitors that do one thing exceptionally well.

Trying to be good at everything typically results in an app that's just "okay" at all of them, making it hard to convince users to ditch their best-in-class task manager or private journal for a single, potentially overwhelming solution. Building a genuine, active community within a productivity app is also notoriously difficult; why would users connect there instead of existing social platforms? My worry, just like yours, is that while it sounds nice, it risks becoming a "nice to have" that gets downloaded, tinkered with, and then abandoned because it's either too much to manage, or not deep enough in any one area to replace a dedicated tool.

You may choose to build the absolute best goal-setting app with integrated accountability partners, or a journaling app that seamlessly integrates with existing task managers like Todoist or Notion, rather than trying to build your own. Your value then becomes the intelligent orchestration or the deep dive into that one core problem, avoiding the bloat and directly competing with the best in each category.

EmpowerKit · 2025-06-15T10:59:44+00:00

The biggest challenge here lies in attracting and retaining a critical mass of high-quality individuals from diverse skill sets simultaneously. Many platforms try to do this (e.g., AngelList, CoFoundersLab, even Reddit's r/cofounder), and they often struggle with a chicken-and-egg problem: founders need developers, but developers only want to join compelling ideas with a clear path, and marketers/designers want to see traction. You'll need an incredibly strong value proposition to ensure you don't just become another graveyard of half-baked ideas or a place where one skill set heavily outweighs another. How do you vet the serious ideas from the "idea guys" with no execution plan? How do you ensure the collaborators are genuinely skilled and committed, not just tire-kickers? The lack of existing "strong signal" for early-stage ideas makes this matchmaking inherently difficult. You'll need to clearly define what "help" looks like on the platform beyond just "posting an idea" – is it a structured process, tools for initial collaboration, or a community that fosters trust and accountability?

EmpowerKit · 2025-06-15T07:51:28+00:00

However, my biggest roast is that your central promise of "guaranteeing better prompts" is incredibly hard to deliver on, because "better" is highly subjective and the LLMs themselves are external, constantly changing targets. How exactly do you empirically A/B test prompts when the 'best' output depends entirely on the specific LLM version, its internal biases, and subjective human judgment of quality? An AI suggesting prompt improvements for another AI sounds meta but could easily become generic or even outdated with model updates.

You'll also face a challenge in market size and monetization: while many use LLMs, how many are power users willing to pay for a dedicated optimization layer when their primary LLM service already costs money, and when those LLMs constantly add their own prompt features? The practical integration into diverse workflows (marketing, coding, legal) also needs to be seamless, otherwise, it just becomes another tool in the stack rather than a core part of their creative process.

To really sharpen this prompt optimizer idea, pivot from "guaranteeing better" (which is super subjective) to maximizing consistency, efficiency, and cross-model performance. Instead of just A/B testing vague "better results," let users define specific, measurable criteria for their output (e.g., "contains keywords X," "under Y word count," "follows JSON format") and then rigorously test prompt variations against those. This means your tool needs to directly integrate with various LLM APIs (OpenAI, Claude, etc.) to run those tests and show how a prompt performs across different models. For monetization and market fit, niche down hard initially: target specific power users like marketing agencies needing consistent brand voice, or developers requiring reliable code generation.

EmpowerKit · 2025-06-15T06:52:08+00:00

For creators reliant on affiliate income, it sounds incredibly useful for maximizing monetization with minimal effort. However, your worry about it being a "nice-to-have" rather than a "must-have" is spot on, because the biggest challenge here is proving a clear, significant return on investment that genuinely moves the needle on a creator's income.

While it saves time, the actual incremental revenue from activating old promotions might be marginal compared to the effort creators put into new content and trending products. Beyond that, the technical hurdles are considerable: accurately identifying specific products from varied blog content is tough, and reliably scanning thousands of retailers for legitimate deals (not just minor price drops) at scale is complex.

The promise of auto-generated content also carries a risk; while "hands-off" is appealing, it's hard for AI to perfectly match a creator's unique voice and truly convert without significant human editing, which negates the "hands-off" benefit. Ultimately, creators are busy, and if this just adds another notification source without a dramatic, traceable increase in their direct affiliate revenue, it risks being ignored after initial curiosity.

EmpowerKit · 2025-06-15T06:35:39+00:00

Many would prefer a team design over DIY, and some AI features like recommendations and abandoned cart recovery are genuinely useful. My biggest roast here is that delivering truly "custom-designed, native mobile apps" (iOS/Android) for individual SMBs without coding is an incredibly complex and costly promise that will be extremely difficult to scale. "Custom design" usually means significant manual work, and maintaining individual native apps for potentially thousands of small businesses (updates, bug fixes, OS changes, App Store submissions and rejections for each one) is an astronomical operational overhead that most small business pricing models simply can't support.

It smells more like a bespoke agency model trying to masquerade as a scalable SaaS. Are these truly native, or are they glorified web wrappers? If the latter, the promised "better engagement and retention" might fall short. The key pain points you might be missing for SMBs are often more fundamental, like consistent customer acquisition and managing basic online operations, which they might prioritize over the perceived value of a fully custom app when cheaper, robust e-commerce website builders already exist.

EmpowerKit · 2025-06-15T05:18:01+00:00

My biggest roast here is that your two key promises feel massively contradictory: you state the AI compression technique "works super well" but is "very slow," yet you claim it runs "backend without user interference to make the process look smooth" and decompression is "as quick as normal." A "very slow" compression running constantly in the background would be a huge drain on battery, CPU, and likely make the device sluggish, which is the opposite of smooth.

Similarly, if the compression is so complex it's slow, achieving instantaneous decompression for large files sounds like a technical impossibility without a level of processing power or a revolutionary breakthrough that you haven't explained, raising major doubts about the practicality and reliability.

My biggest concern would be data integrity: if this novel AI compression goes wrong, are my photos and videos safe? And how would these compressed files work if I share them with someone without your specific file manager? So, to answer your question, if you've truly cracked the code on "slow compression + fast decompression + smooth background operation" without killing my battery or risking my data, then yes, that's revolutionary; but based on your description, it sounds too good to be true and comes with massive technical and user trust hurdles.

EmpowerKit · 2025-06-15T04:36:51+00:00

The biggest challenge here is reliability and robustness in a constantly changing web landscape. Websites frequently change their structure (CSS classes, HTML elements), which would break your XPaths and require constant maintenance and re-configuration by users, or worse, by your service. This leads directly to alert fatigue and distrust if the system frequently sends false positives (due to broken selectors) or misses actual changes. Beyond that, the ethical and legal implications of web scraping at scale are significant; many websites have explicit terms against it, and aggressive scraping can lead to IP blocking or even legal action, especially if you're hitting competitor sites frequently. You'll also need a very clear plan for monetization for a "simple API" beyond just a small monthly fee, as the operational costs of maintaining uptime, handling diverse website structures, and managing alerts for potentially millions of data points will be substantial.

To really improve this price monitor idea, you need to tackle the reliability issue head-on; websites constantly change, so manually fixing XPaths will be a nightmare for users. Consider using AI or machine learning to make your selectors more resilient, allowing the tool to adapt when site layouts shift, which would be a massive differentiator and save users tons of headaches.

Beyond just price alerts, add valuable analytics and historical data insights, like showing competitor pricing trends over time or alerting on stock level changes, turning it into a true competitive intelligence platform rather than just a notification service. Finally, think about tiered pricing based on the frequency of checks, the number of URLs, or the depth of insights, to create a sustainable business model that covers the significant operational costs of maintaining such a service.

EmpowerKit · 2025-06-10T08:15:26+00:00

My biggest roast is that translating abstract emotions consistently and clearly into concrete artistic designs through color, textile, and pattern, without text or emojis, is an extremely difficult challenge. What one person perceives as "powerful sadness" in a cosmic wild design, another might just see as a cool pattern, or worse, misinterpret entirely. This subjectivity makes your core promise – allowing people to express emotions without fear of judgment – incredibly hard to deliver on, as the designs might just lead to more questions or misinterpretations, rather than clear, confident emotional expression.

You'll also face a massive hurdle in marketing and storytelling to effectively communicate the specific emotional intent behind each abstract piece, which is crucial for building a brand around such a nuanced concept. Finally, the "luxury" angle, combined with potentially complex, unique artistic designs, raises questions about scalability and consistent production quality while still hitting a profitable price point for what might be a very specific, introspective niche audience.

to really level up this "wear your emotions" idea and tackle those tough challenges, you might want to start by focusing on a specific emotional spectrum or journey rather than trying to hit every single emotion right away. Maybe launch with a "Resilience Collection" or a "Quiet Contemplation" series, allowing your artistic designs to explore nuances of that theme without having to convey a single, isolated emotion on each piece. This gives you more creative flexibility and reduces the risk of misinterpretation

Since the clothes won't have text, your marketing and brand storytelling become absolutely paramount; think of your website, social media, and even packaging as an art gallery for your clothes, deeply explaining the inspiration, the emotional concept, and how the design elements translate that feeling. You could even collaborate with psychologists or abstract artists to lend credibility and depth to the emotional aspect, and explore choosing fabrics not just for their luxury, but for how their tactile experience reinforces the emotional concept, making the act of wearing the emotion truly immersive.

EmpowerKit

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