halamadrid

The need for actual lawyers will persist I think from my own experience. I attempted drafting a contract with some points myself using AI, but after several edits I wasn't sure if it was correct. Sending it to an actual lawyer ended up in so many corrections I couldn't imagine the first time. One big thing was the overly excessive protective clauses which didn't make sense for reality or conflicted with another.

Its just like code I suppose, if you can read and understand and validate, you can use it to scale and otherwise it could end up being a vibe effort.

If there is one company that I'd never ever use for running a personal agent, that would be Meta. But they have the advantage of a large user base who still uses the platform heavily and a working personal agent is a huge pull for most of their users.

The focus on tools like these is always on how you create. Which IMO is the trivial part. Folks will say you can use Claude to write the code. Claude can also write the definitions needed for tools like this. The big difference is always in how/where you’ll run it and how to monitor things and maintain it long term.

The runtime being the biggest value add from tools like this.

Like Airflow or Temporal or Unmeshed.

The value for me is the runtime not the ability to create stuff. Drag n drop is definitely dead. But so is coding by hand. Pick the right runtime for getting the value from tools like these.

I fail to understand the need to do this, isn't it obvious from the history that Apple will find out and will go after this? Why take this risk? I feel its better to start from scratch & redo things so that you get two things

1. a chance to correct problems you couldn't before because things evolved too much 2. don't break rules or agreements you have signed before

The first one is the key part - I think redoing something the second time almost always ends up in a better result. If you are paid to do it with enough resources and team then all the more easier.

What are all those oops for?

This is probably the first real thing that is affecting me personally with this whole AI business. Having to pay more for device upgrades going forward. I hope the demand settles or new memory production offsets the demand.

Just crossed the second year building out Unmeshed - Orchestration Platform.

This is basically a rewrite of Netflix Conductor which was the original platform we built while working at Netflix. At Netflix, infra was "free" so we were generous in all the dependencies we had on that - so we decided to rewrite for cost optimization in this version.

Unmeshed eliminates the glue code thats typically written for resiliency or connecting things together. And our design of execution also offers it the flexibility of being used as a real-time API orchestrator. It even comes with a managed SQLite service (as many as you need), which means we don't need a provider like Supabase to work with stateful workflows.

Fun fact is that in our company, everything we use is actually just static HTML UI built on top of the Unmeshed Platform as backend - like our CRM, SaaS management, Deployments, Finance etc.

Check it out here: https://unmeshed.io

Is Anthropic rushing to an IPO because investors also fear it’s the peak? I guess it can grow even after the IPO but is there a fear that the spending will rationalize and hurt the valuations?

I know AI companies make money, but the companies consuming these services, are they meaningfully making a revenue to justify the continued spend?

Is Anthropic rushing to an IPO because investors also fear it’s the peak? I guess it can grow even after the IPO but is there a fear that the spending will rationalize and hurt the valuations?

Like a few other commenters, other than reasonably making a software developers work easier I haven’t seen a lot of value creation or revenue boost from AI. I know AI companies make money, but the companies consuming these services, are they meaningfully making a revenue to justify the continued spend?

Operators of Unmeshed here, which is basically a rewrite of Netflix Conductor. In this orchestrator we heavily use a uniquely scaled version of SQLite and also offers “managed” SQLite instances for managing user data. Combining the durable executions of Unmeshed and along with workflow primitives like sleep, workers, etc you can actually build complex systems with a lot less code than ever.

Check it out here: https://unmeshed.io

They both hired some good publicists who is advising that change your tone and messaging to get the public to like and trust the companies.

Initially the goal was to convince investors which is pretty much done and now its the retail/public that will value these companies once they IPO. Either way the job market is definitely impacted and is changing rapidly.

Will one of these companies be the first to hit 10 trillion valuation?

Looking back it feels like GOOG, FB, TSLA etc. all went IPO at reasonable valuations. Retail & public investors did benefit long term and continuing to get higher valuations in public is not a small feat compared to a VC valuation.

A trillion dollar valuation seemed so hard back in the day and now there are so many companies in that list. What's the next level?

Is this just signs that $ is no longer the inflating at the same rate over time and its the realistic inflation that is reflecting in the stock market?

Prices of all goods surely has to follow to make up for the revenue needed to sustain these valuations and also the salaries to sustain the prices.

Unfortunately, those who are not in the loop is not going to have a good time.

We work on disk log based architecture for workflows at Unmeshed (https://unmeshed.io/) which helps it to scale at a fraction of the cost of traditional workflow systems that are based on expensive databases.

Postgres is not cheap to run in the cloud at scale. We went for the cheapest infra, which is basically the disk storage.

I suppose one way is that the Lawyers and Legal Assistants use Legal AI as a replacement for standard search. Instead of parsing content and creating new notes, let AI search and create but humans spend the same amount time instead for verifying what was created.

That way the billable hours can match, but like the article says, who does this benefit? Ultimately the transfer of time to another task will keep law just as expensive. Perhaps there is room to save time on verification vs creation. Is it worth all the investment though?

This is quite amazing. I remember being on the original friendster way back in the day. They had so much potential. And there was also orkut.com that was even better because of the simpler UX. Then came Facebook and you all know the rest.

This is true. Speaking only based on personal experience. My team had started treating AI like a super intelligent being.

“AI suggested we do it that way”

And we’ve been degrading our systems rapidly for last several weeks. We’ve decided to pause and reflect and change how we use AI on tasks that are not dead simple.

Really hard to look at these images given how not human like the humans are. A few are ok, but a lot are disfigured or missing parts and its hard to find a raccoon in here.

Buying stars explicitly is one mechanism. Another one is running Hackathons in India or lower cost countries with a prize, which is qualified by "Starring" said repo.

Easily 1-3k stars per hackathon from student or hackathon participants for a cost of $1-5k. And some free marketing comes with too since participants may post on LinkedIn or other social media if they win something.

"hundreds of calls per week" because the mechanic is under the hood every day seems a little off. Hundreds seems way too excessive. Perhaps an exaggeration to highlight the problem's seriousness?

With that kind of volume, I think even before AI could have helped, why not hire some staff and potentially even a receptionist. Given the volume, this seems like an easy choice.

This was such as interesting read, but I found this link via LinkedIn rather than hackernews.

I would have expected this to be somewhere at the top right now given how deep the article digs and evidence seems legit.

I pay $20 for OpenAI and codex makes me incredibly productive. With very careful prompts aimed at tiny tasks, I can review, fix and get a lot of things done.

I’ll happily pay up to $2k/month for it if I was left with no choice, but I don’t think it will ever get that expensive since you can run models locally and it could have the same result.

That being said, my outputs are similarish in the big picture. When I get something done, I typically don’t have the energy to keep going to get it to 2x or 3x because the cognitive load is about the same.

However I get a lot of time freed up which is amazing because I’m able to play golf 3-4 times a week which would have been impossible without AI.

Productive? Yes. Time saved? Yes. Overall outputs? Similar.

HubSpot CTO was very vocal about how AI is changing everything and how he is supporting by offering the domain chat.com to OpenAI etc. I say was because it has toned down quite a bit. I always thought HubSpot will transform into a true AI CRM given how invested the CTO was in the space from the early days.

Now the stock is down from $800+ to $200+ and the whole messaging has changed. The last one I saw on LinkedIn was "" No comment on the HubSpot stock price.

But, I strongly agree with this statement:

"...I don't see companies trusting their revenue engine to something vibe-coded over a weekend." ""

The stock dip is likely because of the true AI native CRMs being built and coming to market, but why couldn't HubSpot take that spot given the CTOs interest in the space.

If someone in the admin reads this, there is a chance this will be reversed and lead will be allowed in gas again :)

I don't think it was designed to handle the volume of traffic that HN generates.

Code is probably just 20% effort. There is so much more after that. Like manage the infra around it and the reliability when it scales, and even things like managing SPAM and preventing abuse. And the effort required to market it and make it something people want to adopt.

Nice we haven’t faced this cold start problem. We like the idea of Lambdas being offered in a simple runtime platform where you can store and run the code as needed.

And chain it with other stuff as well which is where workflow engines like n8n or Unmeshed.io works better. You can mix up lambdas in different languages as well.

Unmeshed.io is another alternative. You don’t even need to write code for your schedules

For the sake of argument 20x means you have basically suddenly got access to 19 people with the same skill set as you.

You can build a new product company with 20 people. Probably in the same domain as you are in right now.

We are using a workflow engine called Unmeshed - which has what you are asking about. Workflow definitions can be updated without running interfering with running instances and if you choose to you can patch updates on to running workflows. And you can also rerun workflows with the same input from an older execution.

Built on Lovable? Looks neat. If yes, how was your experience? Did you have to customize much by hand or did it take care of most of the work?