CTO at Guestlist Ticket · Bali, UTC+8Web, iOS, Android, back office and six AI agents in daily use. Live in Bali, opening Las Vegas next, on one platform built to add cities.
Six chapters on a timer. Tap right to skip, left to go back, press and hold to pause.
CTO · Bali · UTC+8
09:14 [agent-board] 18 fields proposed
09:14 [review] a person approves
09:15 [event-import] 42 events staged
09:17 [error-alert] help code H-4F2A sent
09:20 [ops-briefing] daily brief posted
09:21 [social] weekly summary written
Consumer web and app, the partner app at the door, a link hub, the landing page and the back office that keeps it running. I build and ship all of it.
Six surfaces, one gateway, six Go services, one self-hosted database. Light travels the wires. Agent output goes back to a person before anything customer-facing changes.
Real local time, real counts, and the tools behind them. Hover a tile for the light. The agent feed is a sample.
Problem, approach, result. Scroll and the files stack. Each one has a full write-up.
Opening a market used to mean weeks of manual venue research. Now it is an import pipeline, a person approving, and a price list in the local currency.
Region filters in the back office, multi-currency checkout and SEO groundwork for a new market are in place.
An agent pulls venues and events from partner pages and keeps the source for every field.
Duplicates, hours and formats are checked against the source.
Nothing goes live until someone says yes to each field.
USD pricing and multi-currency checkout, with the city picker.
Las Vegas, October 2026. The same release adds the next city.
The feed is a sample. Real runs are logged the same way, with a help code and an owner. Status is shown as it is: live, in build, or still a plan.
09:14:00 [error-alert] POST /bookings returned 500, alert sent, help code H-4F2A
09:14:03 [agent-board] 18 fields proposed, waiting for a person
09:14:06 [agent-board] venue hours differ from the source, needs a person
09:14:09 [ops-briefing] daily briefing posted, 11 commits grouped into 4 tickets
09:14:12 [it-automation] opened a pull request for the sitemap redirect fix
09:14:15 [social-analytics] weekly Instagram, Facebook and TikTok summary written
09:14:18 [error-alert] payment webhook timeout, retried, resolved in 2 minutes
09:14:21 [agent-board] approved by a person, 18 fields went live
09:14:24 [agent-board] duplicate event detected, skipped
09:14:27 [error-alert] POST /bookings returned 500, alert sent, help code H-4F2A
09:14:30 [agent-board] 18 fields proposed, waiting for a person
09:14:33 [agent-board] venue hours differ from the source, needs a person
09:14:36 [ops-briefing] daily briefing posted, 11 commits grouped into 4 tickets
Telegram and WhatsApp bot grounded in the issue tracker and 11 repositories. Answers questions, sets reminders and opens pull requests.
Daily briefing, commits grouped into tickets, and the weekly tech report written automatically.
Every failed request becomes a plain-language alert with a help code and a paste-ready AI prompt.
AI reads venue pages and proposes each field with its source, and a person approves before anything goes live. Also pulls events from partner sites and a ticketing catalog into staging.
A headless Claude Code job reads Instagram, Facebook and TikTok metrics through MCP and summarises them.
Persistent remote coding sessions, cost-aware model routing and a shared status dashboard.
End-to-end tests, hourly smoke checks and an alert when the database stops matching the code. Being rebuilt for staging.
Explains why bookings stay unpaid and suggests fixes, with a weekly summary for the founder.
A multi-model assistant: ask once, several AI models answer, and a judge merges them into one reply. Includes a podcast companion with voice.
Answers guest questions on WhatsApp from trained replies, with an AI fallback. Staff always win: it steps in only when nobody replies in time, and refunds and complaints go to a person.
Next on the roadmap, each with a named owner and a cost case.
Outreach agent plus demand forecasting and trend scanners for Bali tourism.
Marketplace platforms, mobile apps, back offices, AI agents and 44 Web3 launch pages. Built and led end to end, from the first screen to the server that keeps it up.
87 builds, each with a real capture or a plain tile. Let the rows run, or search them.
Entertainment-first marketplace for nightlife, events and experiences, rebuilt and rebranded.
Consumer app with a dark redesign, new Home and Discover, and per-guest QR tickets.
Offline-first QR check-in and a booking list for venues and promoters.
Link-in-bio hub in English and Indonesian with dynamic campaign tags.
“Your night out, sorted.” with floating phones, a Tonight in Bali rail and store badges.
About 65 admin screens for bookings, partners, affiliates, imports, analytics and error history.
Social-first job search with skill-based matching.
Employer app to post jobs and manage applicants.
Learning and career-prep platform on iOS, Android, web and desktop. Led the mobile team.
Job-prep simulator with realistic tryouts and performance analytics.
School attendance, leave and digital payroll app.
Customer app for the regional water utility.
The terminal answers to help, whoami, agents, stack and cat cases/search. The diffs show what each job changed.
I am the CTO of Guestlist, a nightlife and experiences marketplace built for many countries: live in Bali, launching in Las Vegas in October 2026, with more countries on the roadmap. I lead the engineering across the apps, the web platform and the back office, and I stay close to the code. Before that I led mobile teams at BTW Edutech and Jobseeker, and I build client platforms and Web3 sites as a freelancer.
Clear specs, small releases, honest status ("live" versus "in build"), and documentation that survives team changes.
Based in Bali, UTC+8.
Own technology for Guestlist Ticket: web, mobile, partner app, back office and AI agents on a Go microservices backend. Leading the Las Vegas launch.
Matching platforms for job seekers and employers.
iOS, Android, web and desktop. Led and mentored the team.
Led 114 members and more than 40 programs.
Client work across the whole stack, and the start of the Web3 launch sites.
I highly recommend Axel as a Flutter Engineer. I worked with him at Jobseeker Company and was consistently impressed by his skills. He builds great, user-friendly apps, writes clean code, and is a fantastic problem-solver. Axel's also a great team player and always eager to learn. He'd be a valuable asset to any team.
During my time working with Axel. when I find a bug or problem on the server related to him. Axel will quickly fix it, according to the order of tasks and priorities which are prioritized. Axel sometimes provides input on new technologies in flutter which will later be reviewed by the company whether it is worth it or not. I recommend him because he is experienced as a flutter engineer.
Quoted word for word from recommendations on LinkedIn.
Only tools used in real repositories, production systems or past roles. A mark appears where the tool has one.
Full-stack, engineering leadership, AI agents or Web3: send a message and I will get back to you.