Product Hunt is best known for its homepage, a daily leaderboard of the most creative and innovative products on the internet. Makers go all out to win launch day, because that visibility matters. Product Hunt also plays a significant role in how products appear in Google search results.
What surprised us was that AI assistants like ChatGPT were rarely citing Product Hunt in product recommendations.
Last year we hired a design agency to build our marketing site for @Basedash. They did an incredible job. The headline makes it sound like I'm dunking on them, but I'm not. The site was genuinely great. They built it in Framer so we could manage content ourselves, which was a completely reasonable bet at the time (and something we explicitly asked for).
I ve been working as a developer for a while now, and one thing I kept seeing was how messy telecalling and lead management get once you scale past a few dozen calls a day. Spreadsheets break, follow-ups get forgotten, and tracking campaign performance becomes a manual nightmare.
To solve this for my own projects, I built Effort Bloom.
It s a telecalling-focused CRM designed specifically to:
Mnexium memories are great for capturing facts, preferences, and context from conversations. But many AI applications also need to manage structured business data events on a calendar, deals in a pipeline, contacts in a CRM, tasks on a board, inventory items, support tickets.
Until now, you had two choices: build a separate database and API layer for your structured data, or try to shoehorn everything into unstructured memories. Neither is ideal.
Today, I came across an article on TechCrunch: The great computer science exodus (and where students are going instead).
It shows that UC campuses saw a drop in computer science enrollment for the first time since the dot-com crash (6% in 2025, 3% in 2024), but students are shifting to AI-focused programs.
Effort Bloom is a powerful Telecalling CRM and Lead Management platform. Track calls, manage campaigns, analyze team performance, and boost sales productivity.
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built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.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:
