Priyanka Gosai

AI is everywhere right now - from copilots and chat assistants to analytics, research, and planning tools. But beyond the hype, I m curious about what s truly useful in day-to-day product work.

From a PM or founder perspective:

• Where has AI genuinely saved you time?

• What tasks do you trust AI with - and what do you never delegate?

• Has AI changed how you write specs, manage roadmaps, or talk to users?

• What AI use cases sounded great in theory but failed in practice?

Personally, I see a lot of potential, but also a lot of noise. I believe that in the future, AI should help us much more. Create good roadmaps, convert product specs into concrete tasks, prioritise them, assign people, push for realisation, and much more.

We ve worked in two other eco-systems (India & France), and each has clear strengths and trade-offs in terms of talent density, cost of building, access to capital, speed of decision-making, and openness to risk all vary a lot.

Curious to hear from founders and operators who ve built outside the US:

• Which ecosystem punches the most above its weight today?

• Where do you see the best balance between talent, capital, and customer access?

• Are there cities/countries that are especially strong for specific stages (0 1 vs scaling) or specific verticals (AI, fintech, climate, SaaS, deep tech)?

Hey everyone,

I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.
That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.

In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.

For those of you building AI or compute-intensive tools: