A very simple reason agents fail is the lack of context- however, the onus shouldn't be on the user. When building an agent, an easy fix to the lack of context problem is to build a context loop. A context loop is simply a conversational method for agents to solicit more context from the user.
It is unbelievable how context loops aren't more mainstream. I see no reason why Claude Code or Cursor can't ask the user what they mean if the user doesn't provide enough information. The addition of context loops gets us much closer to working with AI agents vs telling AI agents to do some work.
I recently built an autonomous agent for Matchy. Like all other popular agentic interfaces today, our interface is chat based & conversational. Something that I've been exploring and questioning is what does a better interface look like? I don't believe chat/voice based interfaces are necessarily the best. While chat allows for data input that is significantly more flexible and perhaps better than traditional UI- it is also a little more work. I don't have an answer today but hopefully I will, soon.
My issue with search engines is we use them for just about everything. From shopping to medical advice- we start with a search engine. Issue is the search engine isn't built for all these things. You often have to navigate to various webpages and manually get what you want. Yes, you can do them through the search engine, but it's simply not efficient. It's like using a hammer to screw a screw.
Niche search engines can offer interfaces and data models that are built for specific use cases.
The "do what you love" career advice is deeply flawed. It assumes everyone has something they love that's marketable and ignores economic realities for most people. Meanwhile, advice-givers face zero consequences when your passion-fueled career tanks.
Just do things. Build stuff. Go outside. Live your life. This isn't guaranteed to reveal some magical calling, but at minimum, you'll collect experiences worth having. And that beats chasing some idealized career that might not exist.
Returns are both a symptom and a problem. They signal that shoppers don't have enough information—about sizing, materials, or what they're really getting, and the environmental cost of all these returns is huge, only getting worse as online shopping grows.
With AI and better access to data, making informed purchases is finally an easier problem to solve. What we need are tools built for shoppers, not just sellers—tools that help people compare options, understand what they're buying, and choose what matters to them.
I've always been fascinated by how we steal nature's best ideas. Velcro from plants, neural networks from brains—nature figured it out first. Recently stumbled across asknature.org and it brought me back to watching ants as a kid, wondering how they coordinate so perfectly without anyone in charge. That same pattern shows up everywhere—fish schools, bird flocks. I think AI teams could work this way too—simple agents following basic rules but collectively solving complex problems. Not that centralized systems are bad—they have their place. But when problems get messy and unpredictable, these swarm approaches might be our best bet.
Lately, it feels like every platform is racing to add image generation features—often without a clear reason why. Most of the time, these tools seem like solutions looking for problems, pushed onto users who never asked for them. I rarely find a real use case for image-gen in the contexts where it's being promoted; more often than not, I just accidentally click on them and move on.
There's a real need for a better approach to using generative AI in consumer applications. Instead of chasing trends, maybe we should start by asking what people actually need.
Games have always been about more than just gameplay for me—they're about the people I play with. Lately, though, I've been thinking about the potential of AI companions in games: entities you can actually talk to, build relationships with, and who feel real-ish, even if they aren't. A recent conversation with a state-of-the-art TTS model (By Sesame AI) made me realize how close we are to this future.
Of course, there are risks—social isolation, blurred lines between real and virtual relationships—but there's also something hopeful about the idea. Maybe AI companions could make games more accessible, or offer new kinds of friendships for people who need them. It's a future I'm both curious and optimistic about.
While in India, I noticed how many people are locked out of new technologies—not because of a lack of interest or ability, but because of logistics like payment methods. Most platforms don't offer country-specific options, so a huge number of people simply can't get access. It's a quiet kind of gatekeeping that limits who gets to build, use, and innovate. If you're in a position to change this, it's worth thinking about how to make technology truly accessible.