I run a support team — and build the software it runs on.
Two years at Bolt Food, three roles, one pattern: find the structural gap, build the tool, ship it to production. My team's scheduler, KPI dashboard, QA pipeline, and the automations that feed them aren't side projects — they're in daily use, built with no formal engineering support.
Internal tools
Built at Bolt Food for the support org and running in production today — not prototypes. The repos below are sanitized copies: employee names replaced, demo data seeded, credentials stripped.
CS Performance DashboardLIVE DEMO
AI-powered KPI and review platform used by 30 managers across 180 agents. Per-agent trends, team rankings, weighted bonus calculator, AI-generated review drafts with editable prompts, Slack delivery, PDF export. Cut weekly review prep from a full shift to under 2 hours.
CS Shift SchedulerLIVE DEMO
24/7 roster generator built on a constraint solver (Google OR-Tools CP-SAT) — rest rules, coverage minimums, leave imports, shift-swap approvals, overtime tracking, Slack + Google Calendar integrations. Replaced a ~$1,000/yr paid service; ~25 daily users. Backed by a 9-module pytest suite.
QA Review Cockpit
One-button QA automation: an always-on engine drives a dedicated browser, reads support cases, scores them against the company scorecard and policy knowledge base with Claude, and fills the review queue. Turned hours of manual ticket QA into a supervised pipeline.
Beehive Plus
Chrome extension that augments the internal case-management tool with admin-panel context the support team otherwise had to look up by hand — order details, provider info, and history injected straight into the case page.
Slack Automation Layer
Two bots that push work to people instead of waiting for them to log in. The dashboard bot DMs every agent their own Block Kit scorecard — each metric against its goal, the team average, and their rank — weekly and monthly, with send history and a manual re-send. The scheduler bot DMs admins a 9:00 AM daily roster: shifts by block, who's on leave and for how long, plus 1:1 catch-up suggestions computed from shift overlap. Swap requests notify approvers the moment they're filed.
Scheduled AI AnalystsRUNS DAILY
Four scheduled Claude agents that finish the recurring analysis before I start work. Two review our AI support chatbot: 40+ BI dashboard CSVs per run, aggregated in pandas, ranked by automation opportunity, separating “never picks the case up” from “picks it up and fails”. Each run ships a markdown review, a Slack canvas, and the example cases behind every finding. A third drafts each agent's monthly review from live KPIs, then spawns a subagent to re-verify every number before I read it. The fourth rebuilds my morning checklist. Shared rule: a stale feed means alert and stop, never an estimated number.
About
I started at Bolt Food as a junior operations specialist and became a support manager in under two years. At every step I built software to remove the manual work around me — an invoice generator handling 1,300+ providers, a diagnostic dashboard for delivery delays, then the full toolkit my CS team uses today.
I'm not a traditional engineer. I'm an operator who codes: I live inside the workflows I automate, so the tools fit — and they're in daily use across the support org, from my own 20-agent team to 30 managers on the dashboard. Built with React, Angular, Python, and heavy, deliberate use of AI-assisted development.