u/Worried-Nobody-2965

Wanted to share a project that I’m working on to make using Apify easier to use for ‘plug and play’ applications.

I posted before about using one of the Reddit actors for scraping for a personal project and I was considering making it more conversational so I built a nice way to query the api by literally saying what exactly I was looking for and it would go grab the relevant posts/comments, outputting a json.

It occurred to me that I could build this more multiple actors, because all I need to do is have the agent find the IDs, have it build a filter, then viola I have the data I’m looking for.

Still a work in progress, because I need to code validation features so the ai agent doesn’t start going on a tangent and blowing up my bill. Curious how others are making filters and how they figure out mapping fields from Apify API

Edit: Apps* in title, lol
I was considering building a personal app for monitoring particular subreddits for mentions of my ICP. Wanted to know what others experience has been with using some of the Reddit actors in Apify and how stable they are. I built a custom data scraper before but wanted to use Apify’s Reddit api since they’re an approved reseller.

I read online that one of the biggest problems with apify’s actors that a lot of times they seem to be pretty unstable, especially if the actor is offline for maintenance, there’s not much communication on the API side on what the issue is. Wanted to know how you guys navigate that.

Also wanted to know how you guys handle sudden API changes and custom infrastructure you build to make sure your pipeline is clean. My primary concern is filtering out noise and making sure there’s not irrelevant posts in my feed.

One of the other issues I was concerned with is the sudden cost explosions that others have complained about. Since I’m using this a as personal project, are these problems typically caused by poor deployment? What are some ways to prevent it?

If yall have other recommendations I didn’t ask about, please do mention. Thanks

I'm a founder of a SaaS I recently launched, but I'm running into a critical problem and not sure how to implement. I'm currently struggling to get sales in a B2B market and I'm divided between doing direct outreach (cold calls, DMs) or social media type outreach (reddit, X)

Addressed Problem:

* Agentic AI has one critical problem; no one can trust their outputs. Just recently Grok made a payment of 175k to a crypto wallet because a user's prompt injection. Put simply, agentic AI cannot be fully autonomous without significant tethers on the range of what AI agents are allowed to do, what they need is reliability infrastructure.

Solution:

* One of the last few months I've been building mechanisms to control AI and data structures, so the output of these automations is reliable and don't break your business. My original motivation came from building some simple AI automations myself and i noticed that AI agents and automations are not very trustworthy at and scale, and in some instances, they actually end up producing more work than it solved.

* In order to solve this problem i had to build some critical infrastructure, making a system that identifies what is expected versus what was received in terms of data. Over time I was able to build deterministic systems that enforce types, filter nulls, do some structural adjustments, and prevent schema drift by filtering out required downstream values versus received upstream values. Nevertheless, this infrastructure once built makes it surprisingly easy to introduce business logic filtering and contract cross checking.

Feedback Request:

Right now, I'm currently in the marketing phase. I just built my MVP and currently doing LinkedIn outreach but currently struggling to get traction because most enterprise customers won't buy from some random startup without connections. Reddit and other B2C outreach platforms don't seem to understand the problem, or they don't feel the problem. I know the problem exists but doing B2B without previous experience is tough to say the least. Anyone else experience this type of problem?

I'm the founder of DataCrawl, a governance layer for agentic AI. Wanted to share my journey of my Saas.

Agentic AI has one critical problem; no one can trust their outputs. Just recently Grok made a payment of 175k to a crypto wallet because a user's prompt injection. Put simply, agentic AI cannot be fully autonomous without significant tethers on the range of what AI agents are allowed to do, what they need is reliability infrastructure.

One of the last few months I've been building mechanisms to control AI and data structures, so the output of these automations is reliable and don't break your business. My original motivation came from building some simple AI automations myself and i noticed that AI agents and automations are not very trustworthy at and scale, and in some instances, they actually end up producing more work than it solved.

In order to solve this problem i had to build some critical infrastructure, making a system that identifies what is expected versus what was received in terms of data. Over time I was able to build deterministic systems that enforce types, filter nulls, do some structural adjustments, and prevent schema drift by filtering out required downstream values versus received upstream values. Nevertheless, this infrastructure once built makes it surprisingly easy to introduce business logic filtering and contract cross checking.

Right now, I'm currently in the marketing phase. I just built my MVP and currently doing LinkedIn outreach but currently struggling to get traction because most enterprise customers won't buy from some random startup without connections. Reddit and other B2C outreach platforms don't seem to understand the problem, or they don't feel the problem. I know the problem exists but doing B2B without previous experience is tough to say the least. Anyone else experience this type of problem?

I operate an unrelated SaaS startup, and I recently saw a piece about how this woman lost 500k via a phishing scam. So decided to build an application that protects people against scams by building a tool specifically for low tech users. I wanted to share this project and get some feedback on it.

Right now, I designed it to actively track and improve on every new scam that it gets. So, whenever a new user uploads a scam, it gets proactively more assertive that said message/email is indeed a scam. I recently added a feature that allows users to upload QR codes, and it actively explores the URL to see any possible attack patterns or query injections. I wanted to get feedback on the product and see what y'all think.

Scams are absolutely rampant now adays and there are not many people who are building tools/applications that help people from falling victim to it. Given how advanced AI has got, it's absolutely bewildering why there are not many options to choose from.

Let me know what you guys think. Also, if anyone wants to collaborate on the project, feel free to DM. I would prefer having another technical guy working with me.

Wanted to share a project/startup I'm trying to launch and want to get some feedback on the project. A few months ago, I was working with enterprise data systems, and I was building a custom integration into a client's no code platform to fix their crappy setup. One of the foundational things I noticed is that it was nearly impossible to get consistent execution across workflows once the APIs, automations and AI agents got involved.

Everything would work in isolation, but the silent schema drift was one of the primary concerns of the clients, combined with the fact that the AI output was consistently unreliable. After doing some research into the greater market I saw that this is a reoccurring problem, especially with the adoption of AI in enterprise contexts, so I decided to attack it head on.

I built a unique type of validation system that acts as a runtime trust layer for AI agents and automations. The core idea is executable data contracts that define expected state transitions, actions being validated against business logic, and having a clear execution lineage. If you're non-technical that means I can catch AI mistakes, which is one of the barriers of widespread AI adoption in enterprise contexts.

So instead of building another observability dashboard, I'm building the infrastructure that checks whether an AI should take action. I think autonomous systems are heading toward the same moment distributed systems had years ago, which is that they realize trust without validation does not scale.

Curious how others who have been building with AI handle dealing with this issue.

I had a friend that fell victim to one of those toll scam messages a while back ago and just recently I saw an NBC piece where a woman in Michigan also a victim of a similar strategy. Both of the scams had a similar strategy: Messages are sent to people who have actually crossed a toll section and somehow, they can send a toll message to said person and ask to give their credit card away.

Most people see the scam right away, some don't. There could be many reasons as to why a person falls victim to it. Maybe they're older, stressed, sick, or tired. Either way I wanted to build a tool that protects people in those moments and gives people a second opinion while still alerting others on the same method.

It got me thinking that these scams are repetitive and most have dead give aways that they are scams, but for humans who can get distracted or stressed they make these mistakes pretty often. Given how repetitive these scams are I wanted to build a way to have a tool that systematically interprets if something is a scam and improve its ability over time, while also being simple and cheap to use.

So, I built Guardian wire. Right now, it's pretty simplistic but I wanted to get some feedback on it and see what sort of features would be valuable. It's free for 10 analyzes. I don't have a paid tier yet. I actually fed it a scam I received personally on my cell and it marked it as 75% definitely a scam and the second time 85%. (100% being absolute confidence something is a scam, 0 being confident it's not).

Ngl i vibe coded most of it, but I think it's pretty good.

I do a lot of high traffic automation work in n8n and for a while I was just hand-rolling validators for every workflow that touched an external API. It was fine at first. Then I had like 8 workflows and it became this whole thing where half my time was maintaining validation logic instead of actually building.

The annoying part is it was the same problem every time, then I had to debug all over again.  Either the data coming in is slightly wrong, then the API call fires anyway then something breaks. Wrong type here, missing field there, nothing throws an error, you just find out later that something did something dumb.

So I built this validator that just handles it automatically, with some special business logic. It watches your outgoing calls, learns what normal payloads look like on its own, and then either fixes what it can or blocks what it can't before anything gets called. No schemas to write, no manifests, nothing to maintain.

I've been running it on my own stuff and it's caught things I genuinely didn't know were slipping through. Ive been building AI agents for property managers and recently an anti-spam AI, which i could talk more about.

Nevertheless, i put a free tier on it that handles 3 webhooks, I’ll probably add more when I put authentication on it so it’s not abused. I thought about putting AI on it and selling it but I’m pretty busy so I figured I can at least help some folks until I do.

Would love feedback especially from anyone else doing serious volume in n8n or similar. And if something's broken or the onboarding is confusing, please tell me.

Link in comments.

Hi all,

Does anyone know of any AI automation and /or automation communities on platforms such as discord/slack/private apps? I've been looking for a platform to talk to agencies or consultants and besides very expensive consultive communities; there doesn't seem to be any.

Especially considering how fast this niche is growing, many of the communities seem to be fragmented and hard to find b2b connections.

Personally I spent months developing a product no one wanted and another where competitors were already mature and dominated the market. If I had a service that successfully validated my idea, from real people who feel the problem, I would have saved time, money, and maybe a bit of reputation. Curious as to what the blocker is here for.

I’m not talking about open source forums. Like a private service where professionals from an industry roast you and tell you if your idea sucks or not.

Thoughts?

Edit: I don’t think I properly conveyed my meaning lol. I’m not saying you just pitch industry professionals like you would a customer and get low tier responses(like you would on Reddit). But rather have your approach / product model/ target market validated before you attempt to build a product, like a comprehensive review. I read on Reddit every day that someone wasted months building something no one wanted, I went through the same thing myself. Why waste time building something no one wants?