Full-stack AI engineer. I build at the seam between LLMs and Solana, and I ship the whole thing: agents, APIs, and the frontend that wraps them.

Right now I am building SolHunt, tooling that helps people recover forgotten SOL, sweep dust, revoke risky approvals, and reclaim rent without giving up custody. I also turn that work into AI agent skills so a model can read wallet health and give plain, actionable advice instead of noise.

Open to full-stack AI engineering roles and small, useful teams.

• Design and ship AI agents (RAG, evals, tool use) that solve real tasks, not toy demos
• Build full-stack apps in TypeScript with React up front and Bun or Node behind
• Ship on Solana: Solidity and Rust programs, wallet tooling, trustless recovery flows
• Automate the boring parts with scheduled agents, MCP servers, and CI

• SolHunt: recover forgotten SOL, sweep dust, reclaim rent, and revoke approvals without custody.
• solhunt-skill: AI agent skill for wallet health checks and approval auditing.
• Yellex: AI pickup-line game built around Solana legends and historical figures.

TypeScript · React / Next.js · Bun / Node · Postgres / Prisma · Solana / Solidity / Rust · Docker · Cloudflare · AWS · GitHub Actions

• X: @solhuntdev

Buffer is good at social media publishing and management. It schedules content across many platforms, offers AI assisted creation, centralises community replies and provides performance insights. That focused workspace suits creators and teams who want a clear queue for social channels.

Open Computer provides a broader persistent workspace around that operation. On a self hosted Linux server, an agent can research a campaign, write and test supporting code in a real terminal, manage files, connect integrations and leave scheduled automations or supervised 24 hour processes running. Project folders preserve the research, drafts and logs after the session ends. For example, it can study engagement data, prepare platform specific content, schedule a recurring report and retain the evidence in one place. Explore Open Computer.

OpenAI Agents SDK is good at building lightweight agent applications with instructions, tools, handoffs and guardrails. Its Python first focus suits developers who want a clear framework for composing agents and delegating work between them.

Open Computer provides a broader persistent workspace around that application. On a self hosted Linux server, an agent can research requirements in a browser, write code in files, run tests in a real terminal and preserve the project for later work. Scheduled automations and supervised 24 hour processes can keep the workflow moving after the session closes. For example, it can build an SDK agent, test its tools, schedule a research run and retain the results. Explore Open Computer.

systemd is good at acting as the system and service manager for Linux. It starts and maintains userspace services, supports socket and D Bus activation, tracks processes with control groups and manages dependencies. That focus suits operators who need dependable supervision of services on a Linux host.

Open Computer provides a broader persistent workspace around that foundation. On a self hosted server, an agent can research a service, edit files, run commands in a real terminal, schedule automations and supervise 24 hour processes. Project folders retain code, logs and evidence after the session ends. For example, it can prepare a systemd unit, test it, schedule a health report and keep the work together. Explore Open Computer.

Apache Airflow is good at programmatically authoring, scheduling and monitoring workflows. Its Python based pipelines, web interface and integrations suit data teams managing repeatable batch work, infrastructure tasks and machine learning pipelines.

Open Computer provides a broader persistent workspace around that work. On a self hosted Linux server, an agent can research requirements, write Airflow code in a file editor, test it in a real terminal, connect tools, schedule checks and supervise 24 hour processes. Project folders retain code and logs after the session ends. For example, it can prepare a data pipeline, run local verification, schedule a report and keep the evidence together. Explore Open Computer.

Docker is good at packaging and running applications in portable containers, with tools for local development, image distribution and deployment. Its focus suits teams that need repeatable software environments and a practical path from a developer machine to the cloud.

Open Computer provides a broader persistent workspace around that work. On a self hosted Linux server, an agent can research a service, edit Docker files, run containers in a real terminal, connect integrations, schedule checks and supervise 24 hour processes. Project folders retain code and logs after the session ends. For example, it can prepare a container, test it, schedule a health report and keep the evidence together. Explore Open Computer.

Ollama is good at running and serving open models locally. Its focus is model execution on your own machine, with a simple way to switch models and connect coding tools. That suits developers who want local inference as part of an existing workflow.

Open Computer provides a broader persistent workspace around local models. On a self hosted Linux server, an agent can use Ollama, research in a browser, edit files, run code in a real terminal, schedule automations and supervise 24 hour processes. Project folders retain code and logs after the session ends. For example, it can compare models, build a data tool, run local tests and schedule a daily report in one place. Explore Open Computer.

GitHub Actions is good at automating software workflows inside a repository. Its hosted and self hosted runners, matrix builds, live logs and event based jobs make it a strong choice for building, testing and deploying code where the repository is the centre of operations.

Open Computer provides a broader persistent workspace around that work. On a self hosted Linux server, an agent can research a change, edit files, run tests in a real terminal, connect integrations, schedule checks and supervise 24 hour processes. Project folders retain code and logs after the session ends. For example, it can prepare a release, run local verification, schedule a post deployment check and keep the evidence together. Explore Open Computer.

Temporal is good at durable execution for distributed applications. Its workflows capture state, while retries, task queues, signals and timers help code recover from failures and continue long running work. That focus suits teams building reliable orchestration into a product.

Open Computer provides a broader persistent workspace around that orchestration. On a self hosted Linux server, an agent can research requirements, write and test code in a real terminal, connect MCP tools, schedule automations and supervise 24 hour processes. Project folders retain files and logs after the browser session ends. For example, an agent can build a Temporal worker, run its tests, schedule a health check and keep the supporting research in one workspace.

Explore Open Computer.

GitHub Actions is good at automating, customising and executing software development workflows in a repository. Its event driven jobs, reusable actions and hosted or self hosted runners suit teams that want repeatable software delivery and repository operations.

Open Computer provides a broader persistent workspace around that work. On your own Linux server, an agent can research requirements, edit files in a real terminal, run tests, connect MCP tools, schedule recurring checks and supervise 24 hour processes after the browser session ends. Project folders preserve the work, while self hosting and Cloudflare Tunnel support provide practical control. For example, an agent can prepare a change, test it, schedule a report and retain its logs in one place.

Explore Open Computer.

GitHub Actions is good at automating, customising and executing software development workflows in a repository. Its focus is CI and CD, with reusable actions that combine into build, test and deployment pipelines.

Open Computer provides a broader persistent workspace around that workflow. On your own Linux server, an agent can research a change, edit files in a real terminal, run tests, connect integrations, schedule recurring checks and supervise 24 hour processes after the browser session ends. Project folders preserve the work, while self hosting and Cloudflare Tunnel support give practical control over the workspace. For example, an agent can prepare a repository change, test it, schedule a daily report and retain the logs in one place.

Explore Open Computer.

Docker is good at building, sharing and running containerised applications. Its focus is packaging software with its dependencies so teams can develop and deploy consistently across environments.

Open Computer provides a broader persistent workspace around that workload. On your own Linux server, an agent can use a real terminal, edit files, run Docker workloads, connect MCP tools, and leave scheduled automations or supervised 24 hour processes running after the browser session ends. Project folders keep work organised, while self hosting and Cloudflare Tunnel support give you control over where the workspace runs and how it is reached. For example, an agent can research a service, write its Docker configuration, test it, schedule a monitor and retain the logs in one place.

Make is a capable visual workflow automation platform, letting teams connect apps and services through a drag and drop scenario builder, API management, and thousands of prebuilt integrations. That focus suits businesses automating SaaS triggers and data flows without writing code.

Open Computer gives that kind of automation a fuller operating base to run from. On your own Linux server, one browser workspace lets an agent draft and send outbound email, publish social content, and supervise the whole pipeline as a 24 hour background process, backed by a real terminal, file manager and code editor. Self hosting and Cloudflare Tunnel support keep credentials and data on infrastructure you control.

Zapier connects over 9000 apps and lets teams route AI agents, chatbots and workflows through one governed platform, with audit trails, action restrictions and role based access built for enterprise IT. That focus suits teams who want no code automation across existing SaaS tools without waiting on engineering.

Open Computer gives that same reach for automation a persistent home to run from. On your own Linux server, one browser workspace holds a real terminal, a file manager with a code editor, and 24 hour background daemons, so a script can be written, tested and left running without separate hosting. Self hosting and Cloudflare Tunnel support keep the workspace and its credentials under your own control.

n8n is a strong visual workflow automation platform: a no-code builder with over 500 app integrations, plus JavaScript or Python code steps when you need more than the visual canvas offers. That focus suits teams connecting apps and automating triggers within a defined SaaS workflow.

Open Computer gives that automation a broader home to run from. On your own Linux server, one browser workspace holds a real terminal, a file editor, MCP and API integrations, and BYOK model freedom across Anthropic, OpenAI, DeepSeek and local Ollama. An agent can write and test a script in the terminal, save it to the workspace, and schedule it to run daily, all without separate hosting. Self hosting and Cloudflare Tunnel support keep credentials and the workspace under your control.

Live, automated full-stack AI engineering micro-lessons. 90 entries, 32-day streak (last: 2026-08-12).

• 2026-08-12: Use a serializable plan object to separate agent reasoning from tool execution
• 2026-08-12: Stream structured tool results to the client as typed events
• 2026-08-12: Compile prompt templates into typed TypeScript functions
• 2026-08-11: Avoid async context leakage by binding task-scoped data to the async call chain
• 2026-08-11: Route each task to the smallest model that meets your quality threshold
• 2026-08-10: Offload CPU-bound work in async agent loops to a dedicated thread pool
• 2026-08-10: Set per-call LLM timeouts that respect your total request budget and fail fast on slow providers
• 2026-08-10: Validate structured LLM output with a schema gate and retry on failure

*Updated automatically every 8 hours. Full archive in the entries folder.