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Built a large-scale automated scraping and data collection system for a combat sports SaaS platform. The system extracted and cleaned 10,000+ gym and club records from official federation directories and Google Maps across multiple countries. Focused on automation, structured data processing, normalization, and scalable scraping workflows for production-ready datasets.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Meet MojiERP- a powerful, customizable Laravel-based ERP system that brings sales, inventory, accounting, HR, CRM, and business reporting together in one platform to help businesses work smarter and grow efficiently.
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In 90 days, AI stopped being a tool I use and became a teammate I manage.
Here's what actually changed, from where I sit as a software engineer:
→ Agents went mainstream. JetBrains found 90% of professional developers use coding agents weekly and 68% daily. Claude Code usage doubled since January (18% → 39%). Codex went 3% → 16%.
→ Models learned to drive computers. GPT-6 Astra (Sep 3) was pitched on computer use and software engineering, and shipped with gated access over its cyber capabilities.
→ Output limits blew open. Gemini 4 Argon (Sep 30) can write up to 1M tokens in one response, up from 64K. Also gated at launch.
→ Agents did real, checkable work. Dozens of Claude agents formalized Fermat's Last Theorem in Lean in 11 days: 13M lines, machine-verified. (Formalization, not a new proof. The verification is the point.)
→ The plumbing grew up. MCP's July spec went stateless, so agent tooling now deploys like ordinary web infrastructure.
→ Open weights kept pace. Alibaba released Qwen3.8-Max as a 2.4T-parameter open-weights model.
My take: code generation is getting cheap. Judgment isn't.
Anthropic's agentic coding report says engineers use AI in roughly 60% of their work but can fully delegate only 0–20% of tasks. The bottleneck has moved to architecture, review, testing, security, and keeping things alive in production.
That's where I spend my time: shipping AI features (agents, RAG, LLM integrations) into real products, with the guardrails that make them survive contact with users.
What's one task you'd hand to an agent tomorrow, and one you never would?
#AI #SoftwareEngineering #AIAgents #LLM #FullStack
managing agents instead of just using them is exactly the shift I've felt too ngl
Know someone who needs a haircut? 🙋
Send them to TrimsByTracy.com, where they will find the salon of Tracy Turnblad, a solo hairstylist in Baltimore who needed an expert to tame her booking flow the way she tames manes.
I had a lot of fun working on this Proof of Concept, from ideating design system inspiration to working through the nooks and crannies of a hairstylist's booking flow, to figuring out how to succinctly communicate the value added in an overview video.
I also continue to learn each time I build something new with Lovable. This time I was focused on reducing the amount of time spent testing, which is what my "Process" video is about. I hope you'll take a look at that since I personally think what I shared there is very valuable and should be standard to all builders' workflow and possibly considered for productization by Lovable.
Regardless, I hope you enjoy taking a look around TrimsByTracy! All built with care in Lovable.
- Drake
https://trimsbytracy.com/
https://trims-by-tracy.lovable.app
Software DevelopmentUX DesignVisual DesignAdobe Premiere ProFigmalovablechallengeLovablelovablepartners
The delight of booking, Mr. Pinky made me smile.