A well articulated blog, imo. Touches on all the points I see argued about on LinkedIn all the time.

I think leveling things out at the beginning is important. For instance, I recently talked to a senior engineer who said "using AI to write programming is so useless", but then said they'd never heard of Cursor. Which is fine - but I so often see strong vocal stances against using AI tools but then referring to early Copilot days or just ChatGPT as their experience, and the game has changed so much since then.

This looks like a cool solve for this problem. Some of the other tools I tried didn't seem to contextualize the app, so the comments were surface level and trite.

I'm on Bitbucket so will have to wait :)

Thanks, really appreciate that! Yeah, giving the AI the ability to fetch the context it needs was a big challenge (since larger codebases can't all fit in an LLM's context window)

And totally hear you on Bitbucket—it's definitely on our roadmap. Would love to loop back with you once we get closer on that front!

Impressed by how accurately this identified and transcribed. Nice work

Thanks, did you try the editor?

The easiest way to understand unprocessed food is "nothing bad added, nothing good taken away".

For instance, pure peanut butter is unprocessed. While it runs through a mechanism to change it from peanuts to peanut butter, there is no oil added, nor are any of the healthful nutrients of peanut butter extracted. Opposite to this is peanut butter like JIF which is processed - the mix is diluted with sugar and vegetable oil to make the same amount of food for cheaper.

Same with tofu - it starts as soybeans and is ran through a mechanism to turn it into the blocks of tofu we see in stores, but we do not add sugar or oils to change the contents of that block, nor do we remove nutrients from the soybean (this may not be 100% accurate, but generally speaking, nutrients are not removed in this). However, many vegan meat products put a lot of unhealthy additions into the mix, thus making it processed.

Generally we put a curdling agent into tofu, so it usually has more of either calcium or magnesium than unprocessed soybeans.

the easiest way to understand processed is has it been changed at all since being harvested? peanut butter and tofu are both processed. raw peanuts and legumes are not. cooked legumes are also technically processed. does not mean that it's always bad per se but that is the definition.

Is low-fat milk processed or unprocessed?

I am very interested in seeing where this goes. I would love to see things get fleshed out a little more ala BlitzJS (auth, simple client/server session management, integrated database tooling), but I don't know if that goes along with Fresh's principles. But this is a very exciting start for this framework and looks like a great addition to the Deno ecosystem.

i <3 forwardemail. thank you for building this!

Anecdotally, every client that rejected a PWA approach has been due to insisting on push notifications. These apps are typically internal employee apps and the push notifications are important alerts that they do not want lost in the shuffle of emails.

Why would you want to push ‘important alerts’ using an off by default, unreliable api?

I typically write my Lambda functions as Nest apps, develop locally, and then deploy with the aws-serverless-express (or fastify) NPM package, and I enable The ability to trigger a kinesis/s3/etc events locally as well. The fact that my app gets deployed to Lambda doesn't really have any impact on my developer experience. What stops you from working locally?

This has worked very well for me, too. I suppose it might start to break down if you're using some of the more complex AWS-specific offerings.

But if your function more or less resembles a little web app that maybe talks to S3 and DynamoDB, this works really well.

+1 for code-first migrations. It's a bit of a learning curve, but the effort is worth it imo.

I prefer dB first.

Create an SQL project that defines the schema. It automatically compares the schema with your current dB schema and auto generates a migration script for you.

Then update entities from the dB.

Few steps involved but avoids writing and maintaing migrations yourself.

I would like to suggest code-first, at least try it once.

I don't want to go back to any sort of migrations outside of this.

Code-first does this too, but based on a schema you define in your code and not in your DB.

I'm surprised no one has pointed out the value of Ionic Framework (https://www.ionicframework.com). I'm a huge, huge proponent of this. TypeScript is a great language (in my opinion), UI code-sharing is inherent, and Capacitor (https://capacitor.ionicframework.com/) is great for all the native work you need to do. Worth noting you can do this in Angular, React, Vue, or pure JS.

This won't suit your needs for processing-heavy apps (though can WebWorkers help), but will work well for many apps (https://csform.com/top-10-apps-built-with-ionic-framework/ for a "top 10" list for examples).

I noticed after submitting that you mentioned machine-learning. Any reason you can't offload that to a web API and take the load off the client?