I’m a project manager who thinks like a product person

I work hands-on with tools like Codex, Claude Code, and n8n in my day-to-day workflow.

I lead delivery from discovery to release and stay close to the product decisions behind the work.

  • 6 years in digital and IT
  • 28 projects delivered
  • 14 clients
Kristina Chernodub portrait

I like to bring structure, clarity, and work that makes sense

Over the past 6 years, I've worked across digital projects, campaigns, and web products. Most recently I managed full project cycles for international clients, from discovery and technical documentation to release coordination and post-launch support.

How I work

  • Start with the real problem

    I prefer to define the bottleneck early instead of pushing a team into motion without a clear reason.

  • Write things down early

    Requirements, scenarios, and technical context save time later and help everyone make better decisions.

  • Keep people aligned

    A good project is usually a coordination problem before it becomes an execution problem.

  • Stay close to the outcome

    I care about delivery, but I also care about whether the work actually solves something.

A few proof points.

28 projects, 14 clients

Over the last 2 years I delivered 27 client projects and 1 internal product, with repeat work from 8 clients.

Cross-functional by default

I worked across design, frontend, backend, 3D, QA, DevOps, and analytics rather than handing projects off between silos.

Documentation is part of the job

I wrote requirements, user scenarios, technical specs, and integration plans instead of treating documentation as an afterthought.

Complexity, but under control

I often managed 3-5 projects in parallel for clients across the US, UK, EU, and UAE.

How I use AI in practice

I use AI tools where they reduce repetitive work, help me structure context faster, or make early testing easier. The important part is still human: define the problem well, set boundaries, and review the output before it affects real work.

  1. Spot the bottleneck

    Start with the task that keeps stealing time or attention.

  2. Structure the context

    Give the tool the right documents, constraints, and expected output format.

  3. Test the loop

    Run small iterations until the workflow is reliable enough to be useful.

  4. Keep human review

    Anything important still needs judgment, editing, and final ownership.

Selected work

Meeting follow-up automation pilot

Post-meeting processing dropped from 60+ minutes to about 30 minutes.

Context
Manual meeting follow-up was taking more than an hour after each call.
Problem
Important context and next steps were too slow to consolidate.
Action
I scoped the automation scenarios, structured the test context, and led iterative prototype testing.
Tools
n8n, Fireflies, Productive, OpenAI, Telegram, Outline.

Full-cycle delivery across client work

Delivered 28 projects for 14 clients, with repeat work from 8 of them.

Context
Client work spanned discovery, integrations, release planning, and post-launch support across several disciplines.
Problem
Projects could drift without strong documentation and release alignment.
Action
I ran discovery, wrote specs, aligned teams, coordinated dependencies, and kept 3-5 projects moving in parallel.
Tools
Technical specs, user scenarios, Shopify, WordPress, GA4, GTM, Looker.

PROSTO NOTION

Reached 500+ monthly SEO visitors and 1.75% conversion, then shut it down cleanly when the economics stopped working.

Context
A niche Notion template business had to prove demand and stay economically sensible.
Problem
The product and delivery flow needed to work without manual overhead.
Action
I researched the market, prepared the products, automated delivery, and tracked the economics closely.
Tools
Tilda, Make.com, Google Sheets, Notion API, email automation, Telegram bot.

If this feels relevant, reach out

I'm currently open to remote Project Manager roles and product-adjacent conversations with thoughtful teams. If you're hiring, building, or want to compare notes on practical AI workflows, I'd be glad to talk.