You will get your AI agent or LLM app debugged and hardened for production
Project details
Is your AI agent, chatbot, or LLM feature failing in real usage? I debug unstable AI apps and harden them for production: tool-call failures, OpenAI/API errors, timeouts, async jobs, broken state, retry loops, poor logging, and fragile prompts.
You get more than a quick patch. I start with failure triage, identify the root cause, apply focused fixes, and deliver test evidence plus clear handoff notes. My own evidence includes HaltTrace, an open-source agent debugging tool with 27/27 tests passing, and LinguaCall, where I removed 5-15s GPT report timeouts by moving report generation into an async pending_report worker.
Best fit: existing AI agents, LLM apps, MCP tools, OpenAI integrations, LangChain-style workflows, or backend AI features that need to stop failing silently.
You get more than a quick patch. I start with failure triage, identify the root cause, apply focused fixes, and deliver test evidence plus clear handoff notes. My own evidence includes HaltTrace, an open-source agent debugging tool with 27/27 tests passing, and LinguaCall, where I removed 5-15s GPT report timeouts by moving report generation into an async pending_report worker.
Best fit: existing AI agents, LLM apps, MCP tools, OpenAI integrations, LangChain-style workflows, or backend AI features that need to stop failing silently.
AI Development Type
Deep Learning, Model Tuning, Software MaintenanceAI Tools
PyTorchAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$120
|
Standard
$480
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | ||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | - |
Model Documentation | |||
Ontology | - | - | - |
Source Code | - | ||
Taxonomy | - | - | - |
Frequently asked questions
About Lee
Production AI Engineer : LLM Agents, MCP Servers & Realtime Voice AI |
Busan, South Korea - 7:06 pm local time
* Knows Python, FastAPI, TypeScript, Node.js, and C++ — plus LLM agents, RAG, MCP servers, and realtime voice AI (OpenAI Realtime)
* I direct AI to build fast, then verify everything with tests and benchmarks before it ships — no untested "vibe-coded" code
* Full project management from start to finish, with runnable proof you can check yourself
* Regular communication is important to me, so let's keep in touch.
Steps for completing your project
After purchasing the project, send requirements so Lee can start the project.
Delivery time starts when Lee receives requirements from you.
Lee works on your project following the steps below.
Revisions may occur after the delivery date.
Failure triage & scope
I reproduce or inspect the issue, review logs/code, and confirm the smallest safe fix or hardening plan before changing production-critical behavior.
Root-cause analysis
I trace where the AI flow fails: prompts, tool calls, async jobs, API errors, retries, timeouts, state handling, or integration boundaries.