Who builds it
Run by the engineer. Not an account manager.
AgenticMode AI is the studio arm of Jahanzaib Ahmed, an AI systems engineer with 126 production systems shipped across healthcare, legal, real estate, and ecommerce. Small by choice: a handful of projects at a time, each one built by the person who scoped it.
Before the AI work, there was an ecommerce agency: four years of running a business, paying for the tools, and needing them to work on a Tuesday afternoon when three things had already gone wrong. That is a different education from writing software for someone else's company.
It is also why AgenticMode is built the way it is. The failure we see most is not technical. It is a system that demos beautifully and then nobody uses, because it was designed around what the technology can do rather than around how the work actually happens.
So the first thing we do on any project is find out how the work actually happens. The building part is the easy half.
How we work
Four things we do not compromise on.
The person who scopes it builds it
No account manager translating your problem into a brief for someone who has never spoken to you. You talk to the engineer, and that engineer writes the code.
Small scope, shipped, then grow
One workflow, one KPI, live in 14 days. Big-bang AI projects fail for the same reason big-bang software projects always did: nobody finds out what is wrong until it is expensive.
You own everything
Code, prompts, accounts, data. If we stopped working together tomorrow, everything keeps running and any developer can pick it up. Nothing here is rented back to you.
Sometimes the answer is no AI
A scheduled query and a well built form beats a language model for plenty of problems. We will tell you when that is the case, which is the whole reason to trust us when we say the opposite.
The toolkit
What we build on.
We pick tools per project, not per fashion. This is what most builds end up using.
- AI voice: Vapi, Retell, ElevenLabs, Twilio
- Models: Claude, GPT, Gemini, on AWS Bedrock
- Automation: n8n, Make, custom services
- Retrieval: vector search over your own documents
- Infrastructure: AWS Lambda, S3, DynamoDB, CloudFront
- Monitoring: cost, latency, and error tracking from day one
Jahanzaib writes about building AI systems in production, and runs free tools for sizing the work before you commit to it.
jahanzaib.aiTell us what you want built.
We read every submission and reply only if it is a fit. No sales calls.
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