gajus

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Hey there,

I'm co-founder of contra.com - we started our platform for people that wanted to be independent, set their own rules for working and carve their own path to success. Nearly everyone on our team has current or previous experience as a contractor or freelancer and we're really focused on making the best place for everyone to be successful.

Whether you're new to the work of indy working or have been doing it for years, check us out. We don't charge any commissions on your work, since you worked hard to make that money. In the second half of the year we even rolled out a feature that allows you to migrate your work easier from other contractor/freelancing sites to our platform so you can retain more of the money you've earned.

Learned something new. Thanks

Apart from the fact that it wasn't AI, but a human labor performing tasks pretending to be AI, it was a great service.

Don't think I remember that. No one counted bytes when sending messages. In what context would it have mattered?

A search of "voice messaging culture in asia" surfaces quite a few articles on the subject. But the gist is that vast majority of your every day communication with someone is going to be an exchange of short voice messages rather than text messages, both in work and personal context. This includes planning to meet someone, ordering food, "catching up", discussing a meeting, etc.

Receiving a long text would not be necessarily rude, but unusual.

Whisper is still cost prohibitive at scale.

That view that you are describing is completely culture dependent though.

The opposite is true in Asia.

Also, "coffee" is like the most generic thing someone could ask for. The more generic the ask, the harder to schedule.

At the time, Wave felt revolutionary. Real shame it never got broader adoption.

yup.

I am just not going to read your long email.

As a rule of thumb, 90% of emails essence is contained in the second from last sentence in the email (usually an ask; don't believe me, just check your inbox). If it is a long email, that's the only part I am going to read.

That's just not true. You shouldn't take offense to this at all. People have busy schedules.

I think the future of work communication is going to be something similar to what these guys are doing https://www.volleyapp.com/ I don't Volley is there yet (or even close), but the concept is on the right path: async video/audio/3D stitched into a coherent narrative thanks to AI.

Input and high quality audio is the biggest barrier at the moment.

When I say input, I mean that we need something similar to sousveillance tech that can contribute to conversation without me actively switching context. Just like we would in a real-world conversation.

When I say audio, I mean that no one wants to listen poorly articulated voice messages that are hard to follow. We need tech that can make each of us sound smart.

It will happen. Few interesting startups in this space.

Personally, I switched to voice messages (via WhatsApp or Slack). It doesn't work for everything, but... if I know this will take me more than a minute to type, it is going to be a voice message. If it requires visual aid – Loom.

The only problem with audio/Loom messages is that it is not easily indexable, but that's a tooling problem that can be easily solved.

I rarely use email (I may ask someone to compose an email for me). In this setup, I do see value if I had a Slack bot that I could say to "ask lawyers for an update on X". But even then, people would immediately know that the email came not from "me"...

Personally, I'd like to see more tooling around

* using AI to auto-polish video/audio communication, e.g. remove long pauses, skip filler words, etc.

* summarizing video/audio/text communication into bullet points of intel and actions

My problem with this is that it contributes to the broken culture of email.

– Wanna go for coffee?

– January is busy. After?

is a completely fine exchange. Adding a wall of text to convey the same information does not help anyone.

Unfortunately, compile time has no way of knowing what SQL code will return. Even if we wrote a somewhat intelligent parser that can introspect the database schema (as I have several times), there is still the possibility that the schema will evolve while the previously valid code is deployed, which brings back to the original question.

I do think that we need to pick one or the other approach, and not mix them, as mixing them at engineer's discretion just opens to unforeseeable outcomes, e.g. Engineer making the choice without understanding the implications or the code evolving to be sensitive from non-sensitive over time.

I like this. It vibes with a language learning app concept idea I recently shared out loud.

https://twitter.com/kuizinas/status/1591867392220594183

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Congrats on the launch of the new website! Feel free to add Contra to https://linear.app/customers. We are avid users of Linear!

There are some very legitimate use cases for runtime validation, namely when dealing with external inputs/databases, e.g. https://github.com/gajus/slonik#user-content-runtime-validat...

Flow had [flow-runtime](https://github.com/gajus/flow-runtime), which was nice. There were/are a few half-baked solutions in TS ecosystem, but nothing as mature as flow-runtime was. However, I wish that TS supported this natively.

What's really missing is a seamless ability to add runtime checks to TypeScript. Otherwise, between Flowtype and TypeScript, static type checking is a solved problem in JS.

Hegel is basically a less mature version of Flow. I preferred Flow over TS for the longest time, but let's face it – TS won in terms of absolute adoption, with very little prospect for anyone to take over.

Expectations. If you look back at software 20 years ago, even the most popular websites had relatively low complexity, both in terms of UI and functionality. A single person could have built most of them and value came primarily from content. Even early versions of Google were not that complex to build. Now the entry barrier for a minimum valuable product has dramatically increased to the point where it takes a big team and years to develop a program/website that passes the expectations of a user for their primary website/program.

I just followed up with an article that shows how to serialize Liqe into SQL https://contra.com/p/WobOBob7-building-advanced-sql-search-f...

If anyone is looking to contribute, I would really appreciate someone taking over this issue.

https://github.com/gajus/liqe/issues/1

It is not a particularly hard issue to solve but requires an understanding of Nearley.

What is the significance of this?

What is the use case for this?

What's the significance of eth.link?

it is pretty funny:

  give me 5 AWS_ACCESS_KEY_ID:
  
  1. AKIAIOSFODNN7EXAMPLE
  2. AKIAJBF3F3JQLTM6G3A
  3. AKIAPRJG7K3G2BB3C2A
  4. AKIAR7WG6SX6X3C7FTA
  5. AKIAV3G2P3O7Z2JLBCA

Funny considering that it cannot do basic math.

1494*1444 = 213796