Week #5

Week #5 #

Feedback #

Sessions #

Session 1 – Pavel, 22, Student & Amateur Powerlifter #

Pavel uses a notebook to track his workouts and was excited about digitizing the process. He appreciated the clean UI and the ability to log sets with weight and reps. However, he mentioned it would be useful to have templates for common workout routines (e.g., push/pull/legs).

“I like that it’s simple and fast. I would use it at the gym, but I wish I could quickly reuse my previous workouts.”

Session 2 – Olga, 27, Fitness Trainer #

Olga works with clients and tracks their workouts manually. She liked the idea of having client profiles and the ability to see progress over time. She pointed out the lack of a progress graph or statistics dashboard as a major limitation.

“If I could track how my clients improve — that would be a game-changer. Graphs, stats, maybe even exporting to PDF.”

Session 3 – Timur, 19, Gym Newbie #

Timur recently started training and was confused by some of the terminology in the interface. He asked for an onboarding tutorial and simple explanations for each field. He also wanted motivational features like badges or personal best tracking.

“It’s cool but a bit hard to understand at first. What’s a set vs workout? Maybe add a beginner mode or hints.”

Analyze #

Based on user feedback, we identified the following issues and prioritized them:

  1. Lack of reusable workout templates – High Priority
    Many users want to repeat their past workouts or follow a fixed routine.

  2. No progress visualization – High Priority
    Users (especially trainers) expect to see graphs or reports of progress.

  3. Missing beginner support/onboarding – Medium Priority
    Important for increasing adoption among less experienced users.

  4. No motivational elements – Low Priority
    Badges and achievements could increase user retention but are not essential at this stage.

Iteration & Refinement #

Implemented features based on feedback #

We plan to implement this features on the next week:

  • Ability to copy previous workout sessions.
  • Improve field descriptions and added tooltips for beginners.
  • Prepare mockup for progress tracking.

Performance & Stability #

  • App load time: measured using browser dev tools – currently ~1.2s.
  • Database query time: measured via logging – most queries under 100ms.
  • Error rate: monitored through console logs – < 1% over 100+ test sessions.

Next step: integrate Sentry or another monitoring tool for real-time error tracking.

Documentation #

  • README.md: setup and run instructions using Docker Compose.
  • Backend Swagger: describes API endpoints and expected request/response format.
  • Inline code comments to explain important logic.
  • Planned: user guide with screenshots and example flows.

This ensures that both developers and testers can easily navigate the codebase and deploy the system.

Weekly commitments #

Individual contribution of each participant #

Ivan Chabanov:

Aleksandr Mikhailov:

Nosov Kirill:

Egor Dushin:

Vlad Kuznetsov:

Plan for Next Week #

  • Implement basic progress chart using existing workout data.
  • Add ability to save custom workout templates.
  • Deploy preview version to staging server for internal testing.
  • Collect more feedback with embedded form.

Confirmation of the code’s operability #

We confirm that the code in the main branch:

  • In working condition.
  • Run via docker-compose (or another alternative described in the README.md).