AI-Driven Full-Stack Automation Build
Budget: $2 – $8 USD
I’m revamping a web product that relies on intelligent, self-orchestrating workflows. The stack must be built end-to-end—interface, APIs, and infrastructure—while weaving in three core AI enablers: Claude code, GPT Codex, and a deeply Agentic development approach.
The heart of the assignment is process automation: think hands-free data ingestion, decision logic that evolves with new prompts, and autonomous agents that hand off tasks to one another without human nudging. I already have the big-picture user stories and a loose wireframe; what’s missing is a robust full-stack implementation that transforms those ideas into a production-ready, scalable platform.
Key deliverables
• Architecture proposal detailing how each agent will call Claude code and GPT Codex, plus fallback strategies
• Modular frontend (React or similar) tied to a secure, low-latency backend—language and framework are flexible as long as they support rapid iteration and clear test coverage
• End-to-end automation pipeline that demonstrates at least one complex business process running autonomously
• Deployment scripts and concise technical documentation so future contributors can extend the agents without guesswork
Acceptance criteria include clean, commented code, repeatable tests, and a short demo video showing the autonomous workflow in action.
When replying, link to at least one live or recorded project where you combined large-language-model calls with automation logic. A brief note on your approach to Agentic patterns—especially error recovery and task decomposition—will help me shortlist quickly.
The heart of the assignment is process automation: think hands-free data ingestion, decision logic that evolves with new prompts, and autonomous agents that hand off tasks to one another without human nudging. I already have the big-picture user stories and a loose wireframe; what’s missing is a robust full-stack implementation that transforms those ideas into a production-ready, scalable platform.
Key deliverables
• Architecture proposal detailing how each agent will call Claude code and GPT Codex, plus fallback strategies
• Modular frontend (React or similar) tied to a secure, low-latency backend—language and framework are flexible as long as they support rapid iteration and clear test coverage
• End-to-end automation pipeline that demonstrates at least one complex business process running autonomously
• Deployment scripts and concise technical documentation so future contributors can extend the agents without guesswork
Acceptance criteria include clean, commented code, repeatable tests, and a short demo video showing the autonomous workflow in action.
When replying, link to at least one live or recorded project where you combined large-language-model calls with automation logic. A brief note on your approach to Agentic patterns—especially error recovery and task decomposition—will help me shortlist quickly.