eightnoteight

I think there are valid ways to increase the outcome, like open source projects codifying the focus areas during each month, or verifying the PRs, or making PRs show proof of working etc,... many ways to deter folks who don't want to meaningfully contribute and simply ai generate and push the effort down the real contributors

Comment · 10 months ago

for the workflow DAG, what type of backend are you guys using? is it like temporal or self-built durable workflows

Comment · 1 year ago

Zenact AI | Founding Engineers & Interns | Full-Time + 6-Month Internships | Onsite Bangalore | Location flexible for internships (India) Tech: Golang • Python • AI Agents

At Zenact AI, we are building AI agents that test apps like real users. I personally faced this problem at Zomato for over 6 years while handling many bugs and incidents.

We launched recently and already got 35+ signups from leading unicorns & soonicorns in India.

Backed by the Zomato mafia.

Team comes with deep expertise from Zomato’s scale journey.

## Roles:

* Founding Engineers.

* Interns (6 months). Must’ve built serious projects or freelanced early in college.

## Tech Stack:

Golang, Python, Java(5%), Appium, AWS, Docker

## You’ll work on:

* Building the platform from the active feedback from the customers, with heavy focus on improving the end to end latency of testing.

* Fine-tuned vision & reasoning models (currently 92% accuracy vs SOTA ~60%)

* AI agents for mobile testing, reasoning flows.

Apply: shoot a mail to [email protected] or fill form here: https://forms.gle/yWproMowhA4ZF4gv6

Comment · 1 year ago

first i thought the website would say how many elephants left in the world (like white rhinos)

Comment · 1 year ago

seems obvious in hindsight, but never knew CT scans are used in manufacturing QC

Comment · 1 year ago

Zenact AI | Founding Engineers & Interns | Full-Time + 6-Month Internships | Onsite Bangalore | Location flexible for internships (India)

Tech: Golang • Python • AI Agents

At Zenact AI, we are building AI agents that test apps like real users. I personally faced this problem at Zomato for over 6 years while handling many bugs and incidents.

We launched recently and already got 35+ signups from leading unicorns & soonicorns in India.

Backed by the Zomato mafia.

Team comes with deep expertise from Zomato’s scale journey.

Roles:

Founding Engineers.

Interns (6 months). Must’ve built serious projects or freelanced early in college.

You’ll work on:

* Building the platform from the active feedback from the customers, with heavy focus on improving the end to end latency of testing.

* Fine-tuned vision & reasoning models (currently 92% accuracy vs SOTA ~60%)

* AI agents for mobile testing, reasoning flows.

Apply: shoot a mail to [email protected] or fill form here: https://forms.gle/yWproMowhA4ZF4gv6

Comment · 1 year ago

one thing that is getting clear is that the gains from model enhancement is getting saturated

thats why we are starting to see a programming of ai, almost like programming building blocks

if there is a pathway for models to get smart enough to know when to trigger these hooks by themselves from system prompt or by default itself, then it wouldn't make sense to have these hooks

Comment · 1 year ago

being on the developer side, the realtime dashboard for admin ui is really useful for end to end testing

so many of the eventually consistent stores reflect so late that its a pain to work with their SDKs

out of curiosity, what kind of metrics or observability do we get for events that got dropped due to some issue

Comment · 1 year ago

credit balance api is pretty cool

always liked the v0 feature where they notify to top up when the balance runs low

when do apps invoke the credit balance api? before sending events or they poll asynchronously and keep a local cache about the credit balance?

i guess caching would be a bad pattern too as the app may not function immediately after the top up of credits

Comment · 2 years ago

most of the current systems that need a reliable managed service for distributed locking use dynamodb, are there any scenarios where s3 is preferrable than dynamodb for implementing such distributed locking?

Comment · 2 years ago

> The problem is that sentinel errors, as typically and idiomatically used, in fact are special, and are more expensive to deal with than other values. My suggestion to use boolean values outperforms them by a lot, 30x in fairly common idiomatic usage.

while I agree to some degree, but when performance comes into picture, what really matters more is normal path vs surprise path rather than happy path vs error path

it's hard to argue what is a happy path in the code, but it's not wrong to say that io.EOF check is a normal path of the code i.e. not a surprise in production. the bad performance of errors.Is is something to be improved upon but it's not a surprise in production when there are a large number of `errors.Is` checks during normal path of the code

now coming to the surprise path of the code, here's where performance gets really important, no one wants their code to suddenly hog 100% CPU because of some special error case - https://blog.cloudflare.com/cloudflare-outage . but such surprise paths often contain a large amount of business logic that weigh much more than how slow errors.Is function is compared to a boolean check

it would be interesting to see where this line of reasoning is valid but IMO performance isn't a good argument against why errors are not normal outcomes of operations in production

but thumbs up for the article, now I know what to reference for backing the below pattern that I often use, when I first saw the errors.Is it was pretty obvious that its going to be slow but just didn't have time to prove it and use below pattern

```

if err != nil && errors.Is(err, x) {

} else if err != nil && errors.Is(err, y) {

} else if err != nil {

    // handling unknown error

}

```

Comment · 2 years ago

people who need to monitor a lot of channels are usually in senior/leadership layer, but one technique usually they follow is focus on a specific problem and consequently some set of specific channels for few weeks or a month and shift focus as the project/task changes

how are you thinking about capturing such dynamic decisions to choose focus area, happening outside the communication tool - like zoom or meetings etc,... algorithm can be real-time but even with data points from meetings etc,... can it be made in such a real-time?

instagram feed algo is pretty real-time but the number of unique behaviours or behaviours to people ratio is quite low. but I'm guessing in a work environment that ratio or the unique behaviours would be too high for the algo to react quickly, right?

eightnoteight

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