Of course, in the meantime, they brought new features and regressions, but the core technology remained the same, so I have an excellent insight into that product. I would say that the main differentiator is the team behind the product. Ours is better, and your experience as a customer will also be better with us.
Yeh I tend to agree. Real value comes from carefully curating the data and applying smart optimizations, which is something few companies focus on. But I also get the sense that a lot of energy ends up being spent elsewhere - on integration, infrastructure, lots of fragmented OS libraries, etc at the expense of iteration speed and relevance-focused experimentation.
I was frustrated with enterprise search vendors and their customers because they didn't see it my way. Here are some ways of thinking about it.
Most cynically, enterprise software is bought by different people than those who use it. The buyers have a list of items to check and the fastest way to get eliminated is to not have an integration for a data source they have so vendors will put up a comprehensive list of them on their web site. The buyers will never test the relevance of the results against their data, though the users will feel it every day, unless the search engine is so bad that they just don't use it. (Common!)
On the other hand, if the integration doesn't work, you get recall of 0% no matter how smart and well tuned your search engine is.
I think a lot of founders and data scientists believe in a variant of the Pareto principle which comes down to "I want to do the 20% of the work that gets me 80% of the way there". The trouble is that a minimum viable product has to be viable, and you have to get to 100% of that minimum or you are always going to be a bridesmaid and never a bride.
The awful truth about data science, relevance, ML and all that is that data is dirty and takes a huge amount of work to wrangle. If you want "iteration speed and relevance-focused experimentation" you have to make investments in product, people and process to run more cycles in less calendar time. Look up my profile and ping me if you want to hear war stories.
If I understand correctly, the library doesn't index the codebase but just generates a good, formatted representation of the repo. I'm curious to hear what you think about more meaningful way to represent a codebase? There is a lot of tribal knowledge in the repo that can help the LLM.
I'm currently working on Merlinn, an open-source AI agent that helps on-call developers troubleshoot production incidents.
https://github.com/merlinn-co/merlinn
Great game! I actually found myself doing an adventure for 10 minutes and it was fun!
Few notes:
* As someone said, it'd be cool if you could render what I'm saying and add a loading indicator for the LLM. It'd improve the UX a bit.
* As someone mentioned, you can try to generate images to make the story more "real". This could be fun.
* You can also try to generate more realistic and drammatic sounds, and make the DM sound more theatrical. I'm not sure if that's easy but might be a big improvement. Bonus - maybe it'd be fun to choose a famous voice, like morgan freeman or anthony hopkins.
* It'd be cool if that could save my adventure. Right now, it is restarted everytime I leave the page.
Awesome, thanks for trying it out! This is great feedback.
I'd love to connect this up to Flux.1 and have auto-generated hero images at the top! And getting the sound right will be a huge part of it, since it's basically an audio-first experience. I'm wondering if it would work to change voices for the dialogue when you speak to different people in the world...
I've noted that save games are essential! Thanks for playing it through long enough to think about that :) I'm glad you enjoyed it enough to keep going!
