Why us (and why now)

Why this problem is worth tackling

The interview synthesis shows consistent, high-intensity pains around:

  • Retention + motivation (learners churn; tutors lose income stability)
  • Progress visibility (especially at intermediate/advanced levels)
  • Cross-lesson memory/context (tutors build manual systems; learners experience disjoint practice)
  • Low-friction practice (learners resist “homework” but want real-world competence)

The opportunity is to use AI to enhance human-to-human learning (not replace tutors) by making practice more personalized, coherent, and habit-friendly.

Why I’m a good fit (Robert)

  • I have experience in startups as an engineer building research adjacent products.
  • I have unique experience in building enterprise and consumer AI products at Microsoft
  • I’ve already built a working prototype and refined the workflows over ~2 years of dogfooding.
  • I can ship product quickly and iterate on the AI generation pipeline as we learn.
  • I’m passionate about language learning (and education in general)– I never lack time or motivation for projects in this area.

Why you’re a good fit (Aleksandra)

The type of team that I’ve seen succeed in these types of ventures is the big tech engineer + big tech product manager (PM) duo. In big tech, the core job of the PM is maintain a product roadmap and continuously translate that roadmap into priorities in a sprint cycle. I believe (though I may be mistaken) that you don’t have experience that is specifically PM. However, what tends to happen is that the PM-side of the duo must expand from the highly structured PM role into the more dynamic and multidisciplinary role of leading product vision. In my experience with startups, before product-market fit is found, someone in this role needs to:

  • lead a rigorous discovery (i.e., doing lots of interviews) and synthesis process (e.g., segmentation, competitive landscape, BPMs, GTM strategy)
  • support rapid prototyping in order to test hypotheses and determine whether to double-down or pivot

I believe your technical background and experience in doing needs-gathering with B2B clients make you well-suited for these tasks.

Moreover, after product-market fit is found, this someone needs to:

  • Design and manage a roadmap, and make sure development cycles stay aligned with the roadmap
  • Design and track key SaaS metrics (churn, CLV, CAC, etc.)
  • Optimize onboarding and minimize churn (run usability studies, run digital experiments, interview power users, etc.)
  • Manage marketing (run campaigns, develop, manage, and optimize marketing channels)
  • Developing strategic partnerships and fund-raising (if needed)

I think the combination of your technical skillset and management experience cover much of the PM’s role and the rest you can get from readings (eg. this, this, and this are great examples). this role and the rest you can learn on your feet. I think your experience in quantative marketing will support digital experimentation, SaaS metric tracking, minimizing churn, and managing digital campaigns. Finally, I think your experience working through full sales cycles with B2B clients makes you ideal developing partners and fund-raising.

Why this collaboration could work

The division of labor is clean:

  • Me: engineering + AI workflows + rapid iteration
  • You: customer discovery + PM + analytics/metrics + GTM

The 2-week collaboration proposal

All that said, the near-term goal is to commit to the idea or pivot to another quickly. If this idea doesn’t work for you we can explore others. I propose an initial 2-week collaboration

  • You run ~10 interviews (mostly learners; a few tutors), using the prototype as an artifact.
  • Deliverable on day 14:
    • Updated BMC
    • Recommendation memo: double down / pivot / explore other ideas together
  • I update the site to be more aligned with the current set of hypotheses
  • I create a tutor user type and enable the tutor to have students
  • I implement the credit system

We can discuss these further.