Repositories
108
67 private repos are included in this deploy snapshot.
Resources
The working kit behind my backend, cloud, AI tooling, and writing practice: grouped by how I actually use it.
Tool belt
Coding signal
A public snapshot of how I build: the numbers and contribution graph refresh from GitHub during each deploy, including private work when the build token can read it.
Open GitHub profileRepositories
108
67 private repos are included in this deploy snapshot.
Commits
333
Authored commits across the GitHub work I can count here.
Code footprint
79 MB
Approximate source footprint from repository language stats.
Project archive
17+
Experiments, utilities, infrastructure notes, and product-shaped builds.
Contribution graph
AI co-pilots
Anthropic
1000M lifetime · 300M last 30d
OpenAI
900M lifetime · 276M last 30d
DeepSeek / Alibaba
10M lifetime · 10M last 30d
Numbers updated by hand each cycle. Anthropic ships an admin-key billing endpoint, OpenAI doesn't expose Codex usage publicly, so this stays a manual pull rather than a live read.
Desk console
Not a shopping list, more like a map of the work surface: one machine for heavy builds, one lab machine for experiments, quiet audio for concentration, fast input gear, and phones for mobile checks.
Main workstation
compile bay01 Audio
focus channel02 Desk controls
input rail03 Phones
mobile dock04 Serverless compute for APIs, scheduled jobs, and event-driven backend pieces.
Packaging and deploying Lambda, API Gateway, IAM, and queues as repeatable stacks.
Managed HTTP edges for serverless APIs and integration experiments.
Queue-first reliability for background work and async payment-adjacent flows.
Fast key-value and document storage for serverless workloads.
Object storage for documents, artifacts, static assets, and durable handoffs.
Logs, metrics, alarms, and operational visibility for production systems.
Cloud platform experience across managed services, APIs, and experimentation.
Fast static hosting and simple deploy previews for this site.
Infrastructure as code for environments that should be recreated, not remembered.
My preferred language for APIs, CLIs, workers, and boringly fast backend tools.
Automation, data scripts, small AI workflows, and glue code.
Enterprise-friendly API structure, services, resources, queues, and backend delivery.
Message-driven systems, retries, routing, and operational queue patterns.
Cache, pub/sub, rate limits, short-lived state, and worker coordination.
Relational storage for systems that need constraints, reporting, and trust.
Postgres-backed product infrastructure for auth, storage, realtime, and quick prototypes.
Serverless Postgres for branching databases, experiments, and scale-to-zero workflows.
Payment-message thinking: fields, reversals, response codes, and careful protocol design.
Authentication, sessions, user management, and product login flows without rebuilding the basics.
Transactional email for product notifications, onboarding flows, and clean developer ergonomics.
A fast product backend layer when a project needs data, auth, storage, and APIs quickly.
Database branching and serverless Postgres for side projects and production-shaped experiments.
A safer JavaScript baseline for product UIs and API-facing code.
React applications, server components, dashboards, and product-shaped builds.
Clean reactive interfaces when the job calls for a lighter frontend feel.
Content-first sites like this one: fast, simple, and easy to keep tidy.
Utility styling when I want design consistency without a giant component system.
Layouts, flows, visual exploration, and design-system thinking.
Reproducible local environments, model runners, deployment packaging, and demos.
Source control, public projects, issues, automation, and contribution history.
CI/CD pipelines, repository workflows, and team delivery patterns.
Fast issue tracking and product planning.
Docs, lightweight databases, planning, and personal knowledge capture.
Meeting notes and synthesis without adding noise to calls.