... seeing AI transform industries, but are we looking deep enough? I've been thinking about applying first-principle thinking to identify areas truly ripe for AI disruption going beyond automating existing tasks to fundamentally reimagining solutions. Instead of asking 'How can AI make X better?', what if we ask: What is the core human need X is trying to solve? What are the fundamental limitations of current solutions, pre-AI? If we were to solve this need from scratch today ... ... instead of asking what the outcome really requires . Comment from Parth Ahir(@parth_ahir): Love this first-principles thinking. That 24/7 expert access example really stands out so many moments happen outside normal hours. For me, personalized learning feels ripe

... adoption among legal professionals surged from just 19% in 2023 to 79% in 2024. The legal sector, notoriously manual and inefficient, is one of the ripest industries for AI disruption. However, it's also one of the hardest. "AI has to meet a higher bar to be commercially viable in legal," says Ethan. "That's why tools have taken longer to hit the market." How We Help If you're building AI-powered contract analysis, document review, or legal research ...

... time suck with so much room for error. Over the past five years, several factors remote work, global hiring, and a growing demand for skilled talent esp in the tech sector have finally brought the HR/People tech stack, ripe for innovation, to the forefront.  Payroll and compliance are no longer the only focus; modern solutions now at a minimum, automatically include org charts, HR data management, tax reporting, and compliance, along with extras like device management, workflow automation ... ... Deel to @Wise which makes it realllly easy to be a working nomad. I agree with you on @Lattice - it's pretty powerful but I do think it could help managers and leadership by being a bit more proactive vs

... help us with our own problems: to sell stuff. At the core of what we're building is the everyday consumer like you. Everyone said consumer was dead, but I knew in my heart that consumer was ripe. I believed back then and even more firmly now that the real value in AI is at the application layer. Maybe, just maybe, we could build an AI-first, mobile-first application that people would use (...and they are). Since then ... ... that these interfaces suck to work with -- the listing process is broken. We have a combination of models that help us identify items and their condition. For eg, some things like electronics are easier to "recognize" with brand, etc, vs

... about the unique challenges and pain points you're encountering in your respective fields. Whether it's in tech, healthcare, finance, education, or any other industry, what are some of the persistent or emerging problems that you believe are ripe for innovation? Let's discuss the issues that are currently lacking solutions and share our thoughts on how they might be addressed in the future ...