ITNeuroNet
AI-Assisted Product Development

Build Your AI-Assisted MVP

I help you plan the system, document the work, and build it with AI support while I review the architecture and key technical decisions.

Discuss AI-Assisted Development Book a Discovery Call
Who this is for

For founders and teams who need to move quickly, but do not want a black-box build, brittle generated code, weak architecture, or a product that only one person can understand and maintain.

The problem

AI can speed up development, but it can also produce a lot of code before the basics are clear. If requirements, architecture, tests, and review are missing, the result may look fast at first and then become hard to trust, extend, or hand over.

What ITNeuroNet does

I help you plan the system, document the work, and build it with AI support while I review the architecture and key technical decisions.

We build with AI support, but we do not let AI run the project on its own. First we write down the requirements and design the system. Then we plan the tasks. Only then do we implement. AI agents help with coding, analysis, test scaffolding, refactoring, and documentation. Evgeniy Medvedev reviews the architecture, product fit, security-sensitive decisions, and overall quality.

What you get
  • 01Working product increments tied to documented scope
  • 02Implementation tasks mapped to the requirements and architecture notes
  • 03Test-aware delivery with reviewable acceptance criteria
  • 04Code review, architecture review, and decision notes
  • 05Demo-ready milestones that non-technical stakeholders can evaluate
  • 06Technical notes, handoff materials, and maintenance context
How it works
  1. 1

    Start with documentation: requirements, architecture, task descriptions, and acceptance criteria.

  2. 2

    Controlled AI-assisted implementation with tests built into the process.

  3. 3

    Evgeniy Medvedev reviews the architecture, the code, security-sensitive decisions, and whether the implementation still matches the product goals.

  4. 4

    Demo-ready milestones, iteration notes, and handoff materials.

Fit check

Is this the right engagement for you right now?

Good fit

You want speed, but you also need the system to stay understandable, reviewable, and aligned with the product goal.

Not a fit

This is not a fit if you expect AI to make the product decisions, design the architecture, take care of testing, and own delivery without experienced human oversight.

Related proof

Where this kind of work has shipped

Case study

TodaiHealth

AI-assisted delivery under senior architecture.

View case studies
Case study

AIspeaky

Voice product built with provider abstraction and review.

View case studies
Technical foundations

More detailed notes on architecture, data, quality, and safety for this service

Related services

Other engagements that often connect

Next step

Ready to move forward AI-Assisted Product Development?

Start with a short assessment. I will look at your situation and suggest the most practical next step: an assessment, a discovery call, or a more specific engagement.

Discuss your projectBook a Discovery Call