I start with the product problem: who has it, how often it appears, how people solve it today, and whether the alternative is valuable enough to build.
Depending on the context, this may include customer interviews, support conversations, competitor research, behavioral analytics, market research, SEO data, or direct observation of workflows. My goal is to understand both the user problem and the business constraints before moving into solution mode.
I turn product ideas into clear scope: user flows, requirements, edge cases, acceptance criteria, and implementation-ready tasks.
I prefer lightweight documentation that helps development move faster without creating unnecessary process. The key questions are: what problem are we solving, what is the smallest useful version, what trade-offs are acceptable, and what should be measured after release?
In practice, product work is often less linear than the ideal process diagram. Especially in B2B SaaS, many improvements start from a customer request, internal workflow issue, technical constraint, or product usage signal.
In those cases, I quickly clarify the problem, define the expected outcome, align with the developer, and move from scope to implementation without overcomplicating the process.
I apply Lean principles whenever possible: test quickly, validate the solution, and iterate.
Not every problem needs a large feature or a heavy research phase. Sometimes the best product decision is a simpler workflow, a clearer setting, a smaller MVP, or removing complexity before it becomes part of the product.
I still use Figma for key frames and early visual thinking, but I increasingly create working prototypes and interface changes with Codex.
For complex changes, I often first discuss the product logic, edge cases, and UX trade-offs in ChatGPT, where the context is easier to keep and refine. Then I turn that into a clear Codex prompt for implementation. This helps me test product logic, simplify workflows, and reduce the gap between product thinking and working software.
Product work: discovery, market research, MVP scoping, requirements, acceptance criteria, prioritization, analytics, and delivery support.
Design and prototyping: Figma, Axure, sketches, HTML/Tailwind prototypes, Codex-assisted UI implementation.
Analytics and research: session recordings, product analytics, user interviews, competitor research, SEO data, support feedback, and behavioral signals.
Collaboration: Notion, Coda, Jira, YouTrack, Asana, Trello, Miro, Whimsical, ChatGPT, and Codex.
I like products where the main challenge is not visual polish, but understanding the workflow, reducing complexity, and helping users make better decisions.
This is why I am especially interested in B2B SaaS, analytics, logistics, operations, marketing technology, and other products where product value depends on clear logic and thoughtful execution.
I like turning messy product usage data into something teams can understand and act on. This includes dashboards, charts, session recordings, usage patterns, adoption signals, and drop-off analysis.
Good analytics should not only show numbers. It should help a team notice problems, compare behavior, and decide what to improve next.
I use AI as a practical product and implementation partner. It helps me explore product logic, compare alternatives, write clearer requirements, generate implementation prompts, and move faster from idea to working prototype.
The most useful part is not just speed. It is the ability to keep context, challenge assumptions, and turn vague product questions into concrete next steps.
I am not a programmer, but I care about implementation details because they shape product decisions.
Understanding enough about frontend structure, data models, permissions, integrations, analytics, and technical trade-offs helps me write better tasks, reduce ambiguity, and work more effectively with developers.
I've been building side projects since 2006. They helped me learn product work from the inside: choosing a problem, shaping the offer, defining functionality, working with developers, promoting the product, and dealing with real users.
This experience is important because it goes beyond design tasks. It taught me how product decisions, implementation constraints, SEO, advertising, operations, and customer understanding affect whether a product can actually work.
Hymetry is a B2B SaaS behavior analytics product that started from session recording, but evolved into a broader product analytics platform for understanding how companies and users interact with a product.
I shaped the product concept, positioning, MVP scope, analytics model, UX, public website, and early go-to-market direction. The product now goes beyond playback: it includes companies, users, pages, product areas, sessions, visits, engagement metrics, usage distribution, peer comparisons, adoption signals, and privacy-aware behavioral data.
The biggest product challenge was turning raw behavioral events into useful insights for SaaS teams. This required decisions around data structure, segmentation, privacy masking, multi-tab behavior, tenant/project separation, performance, and how analytics should help teams notice problems and prioritize improvements.
Holst was an ecommerce project for classic art canvas prints. The core product feature was a configurator that allowed customers to choose frame types, set custom sizes, and immediately see the final size and price.
I worked across product definition, requirements, content, SEO, advertising, and developer instructions. At the time, this was a relatively advanced configuration experience for this type of ecommerce product.
The project helped me understand how product, marketing, and operations connect in ecommerce: a good interface is not enough if the offer, pricing, acquisition, and production process do not work together.
Miracle Canvas was an ecommerce project for multi-panel canvas prints. The main feature was a powerful 2D configurator where customers could create panel blocks, change their size, rotate the final print in 3D, and preview it in an interior.
I created detailed requirements and developer instructions, worked on SEO and advertising, and launched clones for the US market. The configurator was one of the strongest parts of the product because it helped customers understand a complex customizable product before ordering.
This project taught me how important product clarity is when the customer is buying something custom. The interface had to explain the product, reduce uncertainty, calculate the result, and make the final order feel predictable.
Modern Art was an early ecommerce project focused on modern acrylic paintings from Germany.
It gave me practical experience with product positioning, catalog structure, content, operations, customer acquisition, and the realities of running an online business.
This project was important because it moved my work beyond interface design into product ownership: choosing what to sell, how to present it, how to reach customers, and how to connect product, marketing, and operations.
Treenga was my attempt to rethink task management. Rigid hierarchies and endless boards felt heavy, so I wanted something lighter - where priorities and context were clear without clutter.
It taught me that simplicity is hard. Many "must-have" features became distractions in daily use. Stripping down was tougher than adding more, but far more effective.
The deeper lesson was about product mechanics: how people structure work, what "priority" means in practice, and why clarity often beats flexibility.
This project started from a small annoyance: constantly switching to the calendar to check what's next. The idea was to show upcoming events directly in the Dock icon - reducing friction and keeping focus.
It was not just UI polish. I had to handle system integrations, real-time updates, calendar edge cases, and performance so it stayed lightweight and unobtrusive.
The lesson was that meaningful value can come from solving small, recurring pain points. Subtle, well-placed cues can make a big difference - especially when they respect platform conventions and blend in naturally.