Domain driven design is well aware that is not feasible to have a single schema for everything, they use bounded contexts. Is there something similar for the semantic web?
Looking forward to their durable execution Workflows. Writing Temporal workflows has great DX but their pricing and hosting requirements put it out of reach for many projects.
> - Monorepo with FE, BE and shared types - React + Next.js (frontend) - pnpm - Nest.js (server) - Tailwind - Material UI - Apollo (GraphQL) - Jest (Testing) - Typescript + ESLint + Prettier + Husky - Turbo - TypeORM - Segment - Database migrations - Docker - Logging (Pino.js)
How will non-tech founders develop their product on this stack? That's a stack for developers to build the product.
This is a very hard problem, when you see a fragmented ecosystem its because players in the ecosystem have wide ranging and demanding requirements.
You will have to acquire your target customer when they are ready to setup this stack but before they have done so themselves. This would require very high brand awareness. Like "Oh I was going to setup on AWS but XYZ makes it so easy". Only a few companies have achieved this type of awareness in the devops space. Heroku comes to mind. None of them are indie-hacker projects.
It can be faster and more effective to fallback to a smaller model (gpt3.5 or haiku), the weakness of the prompt will be more obvious on a smaller model and your iteration time will be faster
Yeah also prompts should not be developed in abstract. Goal of a prompt is to activate the models internal respentations for it to best achieve the task. Without automated methods, this requires iteratively testing the models reaction to different input and trying to understand how it's interpreting the request and where it's falling down and then patching up those holes.
Need to verify if it even knows what you mean by nothing.
Hi, nice idea. I recently learnt about framer, haven't tried it yet. They have a publishing features. Have you used framer? How would you compare your work with theirs?
As a non academic this is an example in how to express a simple opinion with structure and references. My first reaction was to think this is much ado about nothing, but then I saw it provides a small map one can use to start to navigate this topic.
Yes within a timezone is a good idea. I am based in Australia, teaching myself deep learning, and happy to connect with anyone in Asia. Of course happy to connect with anyone globally, but being in a similar timezone can lead to more serendipity
If the context size is unbounded, how does the time complexity scale with the size of the context, and what are the limiting factors that affect performance as the context size grows larger?
Maybe you just write like an LLM.