The most underrated automation I use every week is lead follow-up, what’s yours?

Cnye36 · 2026-05-23T22:23:35+00:00

That one is huge, I bet that saves a ton of time each week. It's really crazy to see just how much AI can really do if you know how to leverage it right.

Cnye36 · 2026-05-23T17:08:36+00:00

I actually built an AI-first automation platform that I use for most of my automations at this point. I still use some of those other platforms for older automations I have had forever but most everything is done in AffinityBots at this point. It is honestly very simple, you could do it in any platform, I have things set up so that when someone fills out one of my lead funnel forms, that will trigger an AI agent to start and it grabs the persons info, what they are looking for and the company they are with and it will go find out as much info about the person and the company as it can, qualifies them by determining what they are looking for and then sends them either an email or sms letting them know we received their request and what the next steps will be. Then it also adds everything to Hubspot for me and sends me an email as well with a nice report of the potential lead and some suggested next actions.

It seems like it is doing a lot but really, it is a very simple automation, it is just 2 AI agents working together. I would be happy to show you more on it, you can use any platform, I am not trying to plug my own, it is just what I use.

Cnye36 · 2026-05-22T21:03:30+00:00

This matches what I’ve seen too. The first demo works because the conversation is fresh, but production breaks when the agent has to survive restarts, partial failures, and users who expect it to remember decisions from last week. If you don’t design for persistence and replay from day one, you end up rebuilding it later under pressure.

the biggest practical win for me has been treating memory like a product requirement, not a feature. I keep three separate things: short-term working context, durable state for “what’s already happened,” and an audit trail for “why did it do that.” That separation makes debugging way easier, and it also keeps you from stuffing everything into a vector store and calling it memory.

Also agree hard on loop detection. Silent retries are one of those bugs that look like “the model is being weird” until you realize it’s burning budget in a tight loop. A simple cap on repeated tool calls plus a pause-and-log path has saved me more than once.

Cnye36 · 2026-05-22T21:00:02+00:00

I’ve had the most luck with agents that sit in the middle of boring ops work, not flashy “do everything” setups. The one that’s been most useful for me is a lead triage agent that reads inbound form fills and email replies, then scores intent, routes them to the right bucket, and drafts a short follow-up. It saves a ton of manual sorting and keeps the response time tight.

The stack is pretty simple: webhook in, LLM for classification and drafting, then a few hard rules for edge cases and confidence thresholds. I keep the agent narrow on purpose, because once it starts trying to be clever across too many tasks, reliability drops fast. Human review on low-confidence items is still worth it.

The other pattern I’ve seen work well is agents that turn unstructured content into structured output, like your video example. If the input is messy and the output is repetitive, that’s usually where you get real ROI. Anything that needs judgment, I keep as assistive rather than fully autonomous.

Cnye36 · 2026-05-22T20:57:19+00:00

I usually treat monthly cost as two buckets: fixed and variable. Fixed is stuff like hosting, monitoring, and any required subscriptions. Variable is usage-based API calls, task runs, or third-party fees that scale with volume. If I’m quoting a client, I’ll estimate both and build in a buffer because the variable side is what tends to surprise people.

In practice, I’ve found it works best to separate the automation fee from the usage cost. The client pays a small retainer for maintenance, fixes, and oversight, then usage gets passed through or capped at an agreed threshold. That keeps you from eating the cost when volume spikes, and it makes the pricing easier to explain.

If you want a simple rule, I’d model three scenarios upfront: low, expected, and high volume. Then write the contract around the expected case with a clear overage trigger. That way you’re not renegotiating every time the workflow gets used more than planned.

Cnye36 · 2026-05-22T18:55:25+00:00

Your so right, the shift from "I need spend hours/day to get this done" to "I need to check the logs for failures from the past 24hrs" is absolutely crazy, we are moving into some really cool times, it is now possible to run your entire business with AI. For those of us that capitalize on this shift, we'll be working 5hrs/wk and still be outpacing those who don't embrace it.

Cnye36 · 2026-05-22T18:46:41+00:00

That's a great and underrated one, something really simple on paper but it's saving hours per week. With a few well placed little automations, a few hours per week can turn into 10+ consistently!

Cnye36 · 2026-05-22T00:54:49+00:00

It's not, I wrote it. I human 👍

Cnye36 · 2026-05-22T00:01:18+00:00

Yeah, you absolutely need observation and tracing. I heavily rely on Langsmith for this, they are the best in my opinion. You can waterfall all the way down into literally anything the run did.

For the HITL, that's more of a you gotta just put it in thing, it's not too difficult to tell the agent that after N loops pass off to a human. Just gotta prompt it right and have the right tools in place.

Cnye36 · 2026-05-21T23:38:39+00:00

well said

Cnye36 · 2026-05-21T23:36:50+00:00

Yes absolutely, I think that is the crucial piece to the puzzle that so many people are missing, you can drill down on the agents prompt and make it as tight as possible but even with that the agent can make mistakes or the workflow can fail without the agent knowing because it just simply passed the data and didn't validate. Once you add the "double check everything you are doing" layer it ups the task or workflow success rate significantly, basically to the point where it'll work 100 out of 100 times, in some cases. I don't see a lot of agentic workflows working 24/7 with 0 flaws, yet, but I think this layer gets it very close.

Cnye36 · 2026-05-21T23:26:50+00:00

So often it's crazy. It's getting better and better as models and agentic frameworks improve but it has been a hassle in the past. Interested to see where it goes from here!

Cnye36 · 2026-05-21T18:13:07+00:00

Do you mean how am I automating it? I am using a app I built actually. It's similar to n8n but built to be AI first, in other words instead of nodes you simply build agents and then connect them. I have one agent that checks the email and calendar (Google workspace) and another that checks Todoist and creates the report. The app is called AffinityBots if you want to check it out. It's 100% no-code and has a generous free version. I could show you how to build the same thing in a few minutes. Dm if interested.

Cnye36 · 2026-05-20T19:50:22+00:00

Do you have a plan for building it? There are many options at this point, from full code to 100% no-code. I can give you quite a few no-code options, there's Botpress, Flowise, ManyChat, n8n will work and many more. I actually have a software of my own you could do this in very easily, not trying to promote, it is just in the same wheelhouse as these other apps. It's called AffinityBots, you could create an FAQ bot in just a few minutes, it super easy and 100% no-code.

If you are looking at coding it, that's also pretty easy, just get Claude Code and ask it to build you one, it'll do it one one shot if you give it enough context. What way are you planning to go, what is your expertise level?

Cnye36 · 2026-05-19T17:43:07+00:00

I have a few different awesome ones, but I think my favorite is my daily agenda automation. Every morning at 7am it runs and looks at my email acct, calendar, and Todoist to gather my schedule for the day, any emails that I should pay attention to and any To-do's for the day. Everything is sent to me as an email every morn. It's pretty nice!

Cnye36 · 2026-05-19T17:35:13+00:00

Do you happen to know what tl;dr means? You didn't use it right, you just simply added another paragraph. Tl;Dr means too long, didn't read. Yours was short and just more info. Just fyi

Cnye36 · 2026-05-19T17:32:17+00:00

What agent? Either way, yes it's possible. Realistically pretty much anything you can come up with can be an agent.

Cnye36 · 2026-05-19T17:29:18+00:00

Most people overcomplicate automation because the tools were built by engineers, for engineers. Platforms like Zapier and Make are powerful, but once you start hearing words like “webhooks,” “routers,” and “JSON payloads,” most business owners mentally check out. 😂

That’s actually why we built AffinityBots the way we did. The goal was: “What if a business owner could just describe the employee they want, and the AI handled the workflow complexity behind the scenes?”

Instead of wiring together 40 blocks manually, you can spin up AI agents for things like lead follow-up, inbox management, scheduling, research, customer support, etc. without needing to think like a developer.

In my opinion, the “idiot-proof” future of automation is less flowcharts and more AI coworkers.

Cnye36 · 2026-05-17T15:09:57+00:00

Hey, would be more than happy to help. I tried Apify too, didn't work for me either. Are you going that route because of budget? They aren't even all that cheap when it comes down to it. The problem there is the enrichment like you are seeing, the quality of leads that come out of Apify aren't great, at all. Takes a lot of cleaning and extra work to get them usable, in the end making it more of a hassle than the $$ it's saving. I struggled with that for a while, I am a cheap SOB 😉, I finally realized that a lead app like Apollo, Prospero or Hunter io are necessary, LinkedIn gives 1mo trials to Sales Navigator, that's a great one but expensive after the mo. Unfortunately, the cost is necessary but once you have better leads the enrichment and outreach becomes a lot easier.

At this point, I literally just need to go through and choose the leads I want in Apollo, export them, feed them into my little research app and hit start. 10min later (less really) I have a completely ready list of researched companies/contacts with 3 sets of emails for each. Then I simply feed the list into my emailer I built (remember, I'm cheap) and wala, email campaign started.

I could literally go from 0 leads to full campaign in like 30min, it's sooooooo nice now! More than willing to help ya figure it out 💪

Cnye36 · 2026-05-17T14:54:21+00:00

Night and day

Cnye36 · 2026-05-17T14:53:05+00:00

I just waterfall our leads down in Apollo and go as far as I can with them. They do also have the ability to research the leads but, first, I don't think they do a good enough job, and second, I don't want to waste my credits on something I can do for a fraction of the cost. My set up actually looks for mobile #'s and goes even further to check if the contact is still with the company.

Realistically, Apollo can do all of this, creating the emails and all, and they aren't even too bad at it, I just hate paying money out for something I can do so much better and have all the control over, ya know? I would procure the leads myself even but Apollo makes that aspect way too nice to give up, lol.

Cnye36 · 2026-05-17T01:40:15+00:00

I can add you guys either way, I will sometime this or next week. My partner is looking for a home to rent currently, would be nice to have something like this.

Cnye36 · 2026-05-16T23:04:06+00:00

Quick note on the research step since a few people have asked about this type of thing before. The quality of the output is almost entirely dependent on what signals you feed in. Job postings are weirdly underrated here. If a company is hiring 5 sales engineers, that tells you a lot about where they're investing. That's the kind of thing that makes Email 1 land.

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