I see this as a big unbundling, since your agent has your ear now, not Google, not social networks, they lose their entry point status and don't control by ranking, filtering and UI what I see or what I can do. They can spread out searches to specialized engines, replace Google for search, walk above all social networks and centralize your activities so you don't have to follow each one individually. A wrapper or cocoon for the user, taking the ad-block and anti-virus role, protecting your privacy and carefully reducing your exposure to information leaks.
All of this only works if you can host your model. But this is where the trend is going, we can already see decent small models, maybe before 2030 we will be running powerful local models on efficient local chips.
Once this is working better, it will allow to extend the abilities of local models without running into the massive issues with context limitations I personally was hitting for self hosted.
A firewall which can set the user on fire.
https://guard.io/labs/scamlexity-we-put-agentic-ai-browsers-...
I recently used Comet to find out of print movies that were never released on DVD/Bluray, then find them on ebay, then find the best value, then provide me with a list to order. It felt like magic watching it work, and saved me many hours of either doing it myself or scripting it.
I did have to repeatedly break it into ever smaller tasks to get everything to fit within the context windows, but still... it might have been janky but it was janky magic.
The point is the multiply how much you can get done, simple searches still require me to be present and to do the work of compiling the list myself, this type of busy work seems much better suited to tools like this that take a sentence or 2 to kick off
I am also finding work is becoming more tiring. As I'm able to delegate all the rote stuff I feel like decision fatigue is hitting harder/faster as all I spend my time doing is making the harder judgement decisions that the LLMs don't do well enough yet.
Particularly tough in generalist roles where you're doing a little bit of a wide range of things. In a week I might need to research AI tools and leadership principles, come up with facilitation exercises, envision sponsorship models, create decks, write copy, build and filter ICP lists, automate outreach, create articles, do taxes, find speakers, select a vendor for incorporation, find a tool for creating and maintaining logos, fonts and design systems and think deeply about how CTOs should engage with AI strategically. I'm usually burned pretty hard by Friday night :(
I consider myself extremely competent at getting niche results. Couldn’t for the life of me find a certain after market part for a home appliance.
I go ask Claude to find it and it comes back with exactly what I need. One of its queries hit a website with a poorly labeled product that it was able to figure out was exactly what I needed. That product was nested so deeply in results that I would have never found it on my own.
That was the goal, yes. In the end I only actually found about 10 I didn't already own, but the AI had to wade through a few hundred to find them.
We will likely have decent standalone voice assistants at some point soon but Alexa and Siri were way too early for that.
That's _still_ the only thing they're good at...
The closest one came to handling controlling music playback well in anyway was Cortana but even Cortana didn’t do the things that I needed to do with my voice while controlling music play.
The biggest Used case for me was always hey Cortana hey Siri add a specific song to now playing and play it next. No matter what on any operating system. The voice assistant delete the entire queue and then probably plays the wrong song. Not only will they play the wrong song, but they will play the entire album from the wrong song if it is available so now I’ve gone from a playlist that I was building and listening to on loop for potentially days to some album that I don’t wanna listen to because it could not just add a song next.