You will get Claude Code and AI coding agents set up on your repository
Project details
Uptime monitoring lies. I learned that in a 30-hour outage where every availability check stayed green the whole time and the answers coming out were wrong the whole way through.
That is the thing I build into coding agents, and it is what most setups are missing. An agent that reports success because a command exited zero is not telling you anything. Mine check whether the output is actually right.
What you get is Claude Code configured for your repository specifically: a CLAUDE.md that encodes how your code really works rather than generic advice, the commands and settings your stack needs, and agents scoped to jobs they can finish.
I run this loop on my own work every day: plan, build, deploy, smoke test, review, read the logs. I have a triage agent with repo and queue access that reproduces a reported bug, fixes it, and replies to the person who filed it, mostly closing them end to end.
Eighteen years of being the person paged at 3am is why I set them up to verify rather than to report.
That is the thing I build into coding agents, and it is what most setups are missing. An agent that reports success because a command exited zero is not telling you anything. Mine check whether the output is actually right.
What you get is Claude Code configured for your repository specifically: a CLAUDE.md that encodes how your code really works rather than generic advice, the commands and settings your stack needs, and agents scoped to jobs they can finish.
I run this loop on my own work every day: plan, build, deploy, smoke test, review, read the logs. I have a triage agent with repo and queue access that reproduces a reported bug, fixes it, and replies to the person who filed it, mostly closing them end to end.
Eighteen years of being the person paged at 3am is why I set them up to verify rather than to report.
AI Algorithms
Large Language ModelAI Applications
AI-Generated Code, AIOpsAI Models
AlphaCode, OpenAI CodexWhat's included
| Service Tiers |
Starter
$250
|
Standard
$600
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | |||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
Frequently asked questions
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AS
Asif S.
Aug 11, 2026
Upwork Talent Accelerator: AI Chatbot Developer
Really impressed with the final results and the attention to detail throughout the project.
About Christian
AI Agent & Automation Engineer | Python, LLM Integration | 18 Yrs IT
Pittston, United States - 10:07 pm local time
Most AI projects stall in the same place. The demo works, then someone asks what happens when it gets something wrong, and nobody has an answer. I build the answer in from the start: identity verification before any privileged action, policy gates that decide what runs automatically and what stops for a human, and an audit log for everything.
What I do:
- AI agents and workflow automation. Multi-agent systems that resolve helpdesk tickets end to end across Microsoft 365 tenants: password resets with identity verification, distribution list and Teams group management, approval routing. Built in Python against the Microsoft Graph API.
- Microsoft 365 and Azure automation. Graph API integrations for provisioning, reporting, and the admin work that should not be manual. PowerShell where PowerShell fits.
- Custom tools and integrations. FastAPI services, API integrations, and scripts that connect systems never meant to talk to each other. I have shipped a live SaaS product and published a Python package to PyPI.
- Retrieval and data extraction. RAG on pgvector with recency decay layered onto similarity, so relevance does not quietly mean stale. Playwright scrapers and extraction pipelines that clean, score and rank what they pull, with tests over the scoring logic.
Background: 18 years in IT, help desk through Director of Information Technology. Twelve of those inside a HIPAA-regulated healthcare provider, three of them owning the budget and the vendor decisions. Four years at an MSP running Microsoft 365 and Azure across many client tenants. I know what production means because I ran it before I built for it.
I have been building with LLMs since ChatGPT launched, which is about as long as anyone has.
How I work: I tell you what I think will actually work, including when the answer is do not build this. I write documentation. I hand things off so you are not dependent on me.
Tell me what is eating your team's time and I will tell you whether AI is the right fix.
Steps for completing your project
After purchasing the project, send requirements so Christian can start the project.
Delivery time starts when Christian receives requirements from you.
Christian works on your project following the steps below.
Revisions may occur after the delivery date.
Read your repo first
Before writing any config I read the code, the tests and the build, because a generic CLAUDE.md is worth nothing.
Write the context file
How your code actually works: conventions, the parts that bite, what never to touch, how to run things.