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Guardian OS: Enterprise Security & Workforce Management Platform
Initiated AI-assisted UX/UI designs and also architected & built Guardian OS, an enterprise security operations platform digitizing 5 departments for 500+ security guards across 50+ commercial sites (Emaar Misr, Saint-Gobain). • Stack: Nuxt 3 (PWA), Vue 3 Composition API, Vuetify 3, Firebase Firestore, RTDB & Vercel Serverless. • Features: Automated shift roster rest-violation engine (<8h rest alert), Egyptian Labor Law payroll engine, zero-trust Firestore security rules, real-time FCM notifications, & uniform custody tracking. • AI Engineering: Built with multi-agent dev pipelines (agency-agents-orchestrator) & Vitest.
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AI Commercial & UI Explainer Ad for Bdjobs Live 🎬
Blending AI-generated spokesperson visuals with clean UI screen replacements and commercial motion design. Designed to turn complex web platform features into an engaging, high-trust visual explainer for digital marketing and user acquisition.
• Role: AI Generation, Video Editing, UI Motion Graphics, Compositing
• Tools: Premiere Pro / After Effects / AI Video Tools / CapCup / Google FLow
#aivideoediting
#creativevideoediting
#shortformvideoediting
#paidadvertising
#videoediting
𝐉𝐨𝐛 𝐡𝐮𝐧𝐭𝐢𝐧𝐠 𝐨𝐧 𝐡𝐚𝐫𝐝 𝐦𝐨𝐝𝐞
B2 English, based in Argentina. Payment preferably in USDT. Remote only. Quite a combination, right?
I built an AI-assisted job-search system around Freehire and Hirify. Both platforms offer official API/CLI access for automation, which makes them much easier to connect to an agent workflow. Simple Python scripts collect job listings and run the first pass of filtering against strict rules.
Then agents double-check the requirements, match them against my experience, and tailor my CV to each role. They highlight relevant projects and technologies I've actually worked with. Final review and approval stay with me.
𝐀𝐬 𝐨𝐟 𝐒𝐞𝐩𝐭𝐞𝐦𝐛𝐞𝐫 𝟐𝟔:
✅ 20 applications sent;
✅ 8 HR screenings passed;
✅ 1 video screening completed and submitted.
🚀 Technical interviews are still ahead.
I'm not ready to write off the market. Even with my constraints, things are moving.
A job search deserves 𝐚𝐧 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 𝐭𝐨𝐨: clear rules, automation, and checks on the results.
Rope Street Tattoo, Brașov (fictional)
Problem solved: a solo tattoo artist loses tourist leads to midnight DM replies and a day's pay to every no-show. Now any message becomes a priced, deposit-paid booking in under a minute, and confirmations, reschedules and waitlist refills run on their own.
The client: Mara, one chair, around the corner from Strada Sforii. Gloves on 7 hours a day, so DMs wait until midnight. Every quote needs size, placement and colour: about 7 messages per booking. Tourists leave before she replies, and 1 client in 7 doesn't show up.
What I built in Lovable:
→ Front door: describe the idea in English, German or Romanian. AI reads it, but Mara's own rules set duration, price and deposit. Only times that fit the job and the customer's days in town. Stripe deposit, booked. Cover-ups and hands go to Mara instead.
→ Autopilot: confirm or move at 72 h, a second nudge at 48 h, unconfirmed slots released 24 h ahead and offered to the waitlist, prep reminders, online consent forms, aftercare and touch-ups.
→ Owner area: Today, Week, Needs you with drafted replies, paste-a-DM replies, and the numbers: in four weeks of demo data, 304 messages not written and 38 h 53 min saved.
→ A demo clock to fast-forward and watch it work.
Try it: https://rope-street-tattoo.lovable.app
Owner view: footer → Studio → Try the owner view → Demo clock
Case study: https://rope-street-tattoo.lovable.app/story
A tourist who books two days ahead lands inside the 72-hour confirmation step. Does that booking skip the confirm-or-move message, or does it get the 48-hour nudge straight away?