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Automated API Data Pipeline to Google Sheets
A fully automated data-sync workflow that pulls information from external APIs, processes it, and updated a Google Sheet on a scheduled basis. This system eliminates manual data entry ensures real-time accuracy, and provides teams with a single source of truth for reporting, analytics, and operational decision-making. The workflow includes authentication, data extraction, transformation, validation, and structured output, all running automatically in the background.
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Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
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KILLBEROS
Risk-First (Educational · Fully simulated)
Measure the danger before the gain.
Most small investors don't lose for lack of ideas they lose for lack of risk discipline: they over-trade, double a losing position, and over-size out of fear or greed. KILLBEROS gives anyone the risk discipline of an investment fund, on a modest $1,000 budget ($500 in play, €500 kept untouchable). 100% educational, fully simulated no real money, no broker, no orders ever placed.
• Risk Planner — real position sizing on any instrument: size, risk, reward-to-risk, computed live.
• The 7 Gates — every trade must pass 7 risk checks; break one (e.g. a reward:risk below 2:1) and it's BLOCKED. The danger is measured first.
• Market Regime — live market "weather" (real Fear & Greed + real crypto prices) decides which strategies are even allowed to play.
• AI Advisor + a mistake "pokédex" — so the same error never repeats.
• Journal — log real trades, see your true edge: win rate, expectancy, drawdown (real backend, not a mockup).
Innovative Workflow)
KILLBEROS was designed and built in Figma Make, then reviewed live and iterated, version after version (V2 -> V43), by an AI agent "Cowork Brain" working through Figma's MCP.
But the real innovation is HOWdecisions were made: every significant choice (doctrine, a risk gate, a strategy, the UI) was debated by a standing panel of 11 AI "voices" that the agent embodies in one head — 5 trader profiles (macro, chartist, a risk/Aladdin voice with veto power, a short-term "gambler", and a long-term allocator) + 5 engineer profiles (backend, UX, API, security, data).
Risk speaks first, the angles are confronted, a decision is made, and the dissenting view is written down. (Junior) signs off on anything irreversible. It's a small AI team with a real method not a single prompt. Build-in-public: every version and decision is journaled.
And After :
KILLBEROS is the educational tip of the iceberg. Behind it, a far more powerful engine the full GambleRisk is in the works: the same risk-first doctrine, but it paper-trades itself for weeks to PROVE its edge, market regime by market regime, before anything else. Still risk-first, still discipline-before-gain. This is just the beginning.
Team : Junior Odika (+ Cowork Brain, AI collaborator).
URL :
Hey Junior, don't forget to share your project on Instagram, X, or LinkedIn with #ConfigMakeathon and @figma to complete your submission! 😊
Check the guidelines and get that in before the deadline!
Built a Customer Behavior Dashboard analyzing 3.9K customers, tracking average purchase amount, review ratings, revenue by category, and sales by age group. Created using Power BI with interactive filters for gender, category, and shipping type. This project demonstrates end-to-end data analytics from raw data to business insights.
Hello guys, here is how i save time for my client with AI automation using n8n, my client applying new employee to their small business.
the automation start from applicants putting down their information through "tally form" and "n8n" automatically grab the Informations from tally including their CV, Specialities, Years of experience, Main Skills, Previous experience.
And AI analyze the their responses and score them from 1-10 based on their CV, Communication skills, Experience. 1-5 is failed 6-7 is average and 8-10 is passed.
Store their CV/Resume in the "google drive" as a pdf format for the business to also confirm.
I added the applicant info to the "googlesheet" where all record of applicant are been stored
And send a message to the hiring department on "slack" with the applicant info if the Pass, Average, or Fail. and also drop the googlesheet link in the message for hiring department to check the information and make amendment if necessary.
"Email" will be sent to the applicant automatically giving them feedback on what they had just apply for, And using "HTML" to format the message so it can make sense and have a better coloring and well structured.
Tools and Software i use:
_n8n
_google drive
_chatgpt
_google sheet
_slack
gmail From manual data capturing, sending email, adding info to database, and sending email message to every applicant to a time saver leveraging on automation to perform the task. If this will be helpful let's talk better and map out automation tailored to your business or tasks Peace✌
wooo it looks so nice
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