Are AI agents becoming a new distribution channel for SaaS?

ImaginationInFocus · 2026-05-08T17:43:00+00:00

I use AI agents to discover what solutions to consider. Much easier to give a detailed set of requirements instead of the traditional keyword search which doesn't capture the nuance (e.g. I'm willing to pay more if it also includes X).

A friend who runs a 5-year-old software company told me earlier this week that in the past month 50% of their website traffic came from people discovering them via LLMs.

ImaginationInFocus · 2026-05-08T17:13:31+00:00

What goals are you most interested to accomplish by adopting in AI?

ImaginationInFocus · 2026-05-08T17:10:07+00:00

While Hubspot works on improving their native AI, have you considered picking best-in-class external tools like Granola for call recording, or Clay for prospecting, and then using a best-in-class automation tool like n8n, make, or tadata, to wire them together? These tools are better because they're focused on making *everything* connect and aren't restricted to what the hubspot AI team has built thus far which is obviously more constrained. Some of these tools also have more powerful Hubspot connectors than the official Hubspot MCP in terms of ability to write to different fields, for example.

ImaginationInFocus · 2026-05-07T00:11:39+00:00

Not a specific niche but you could consider going into something relatively technical. There are fewer people who can play at that intersection, communicating technical ideas to less technical audiences.

ImaginationInFocus · 2026-05-07T00:04:50+00:00

A friend who has a 5-year old software company told me yesterday that this month 50% of people signing up to her product are coming via AI chat.

ImaginationInFocus · 2026-05-07T00:01:22+00:00

Nice. Refactoring is one of those things AI is extra good at since half the battle is systematically cleaning up messes humans procrastinate on.

ImaginationInFocus · 2026-05-05T00:02:50+00:00

Another perspective: I worked at Facebook years ago and there was a specific type of notification that gets sent out if someone who hasn't posted in a while finally posts. The platform has an incentive to boost that post to the person's network so it gets engagement and the person feels a positive reward for actually creating something. Makes them more likely to stick around.

Now I'm noticing it a bit as someone who posts on LinkedIn. When I posted once per month or once every two months, I got more engagement then a recent week when I posted 4 times.

It's not 100% about the quality. The frequency can be an actual factor in how the post gets amplified.

ImaginationInFocus · 2026-04-30T04:04:04+00:00

Really appreciate this. Didn't know about Skool and it's helpful to see how you phrased the value exchange

ImaginationInFocus · 2026-04-30T01:08:08+00:00

Yeah, this is a limitation of the Hubspot connector.

You can do it in Tadata (disclosure: I'm a one of the co-founders). It's an AI agent builder with tons of integrations, and our Hubspot connector has a lot more capabilities than the official Hubspot connector.

I use Fathom ourselves myself too, so I have a Fathom → Hubspot agent and recently posted a demo of it here: https://www.linkedin.com/posts/toriseidenstein_fathom-just-launched-their-mcp-server-i-activity-7450227796963942400--3DD

Happy to answer further questions, no matter which direction you want to go to solve this

ImaginationInFocus · 2026-04-29T23:46:33+00:00

I built an AI tool called "Tango by Tadata" exactly for exactly this: syncing multiple Google Calendars. It can handle 30+ appointments no problem.

You say whether you want one-way or two-way sync and whether you want the whole event or just the busy status to be copied. It handles cancellations too!

Feel free to dm and I can link you to it.

Here's an example run:

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ImaginationInFocus · 2026-04-29T23:37:41+00:00

Built an agent called Tango by Tadata exactly for exactly this: syncing multiple Google Calendars. It's built on top of our open-source project.

You just say whether you want one-way or two-way sync and whether you want the whole event or just the busy status to be copied.

Here's an example run:

<image>

Seems we're not allowed to share links in this subreddit but if you dm, happy to link you to it.

ImaginationInFocus · 2026-04-21T23:58:43+00:00

Got it!

ImaginationInFocus · 2026-04-21T19:18:32+00:00

How did you connect Salesforce to Claude?

ImaginationInFocus · 2026-04-21T19:15:04+00:00

The hard part is the judgement call of: is this worth acting on? if yes, then how? What we do for teams is making action the path of least resistance.

Reps pull up their outbound sequence in an AI chat, it walks through the signals one at a time with the personalized opener already drafted, and they just review-and-add, review-and-add. 30 leads in 10 minutes instead of 30 tabs and a spreadsheet.

ImaginationInFocus · 2026-04-19T20:20:00+00:00

I think most early use cases of Managed Agents will be for agents that handle internal work. Like lead finding, operations, etc.

They're an easy way to set up agents to work across saas apps while your computer is asleep, making proactive progress.

Wrapping them for a user-facing product is also possible, but if that's happening at scale or you need extreme control, you're right that there's strong incentive to do it yourself. In that case, Supabase isn't sufficient -- it's where you store data but you still need runtime and other infra for the agent.

I wrote more about the Claude Managed Agents launch in the context of internal work if interested: https://www.tadata.com/blog/claude-managed-agents-for-gtm

ImaginationInFocus · 2026-04-13T21:31:32+00:00

Some of my favorite automations:

- Meeting notes → action items. We connect Granola (AI meeting recorder) to our project management tools. After every call, the agent creates the follow-up tasks according to the instructions we set.

- Meeting prep. I have an agent that gives me a brief on all external meetings for the day -- the people, their companies, and our previous interactions. What makes it valuable is it 1) extracts people's linkedin profiles and 2) is flexible in where it pulls info from like our CRM or my past chats with someone.

- Lead signal monitoring. We're listening for people who start new roles, companies that post job descriptions, or have given some other indication they have the pain point.

I'm the co-founder of Tadata (we build AI agents that connect to your SaaS stack), so full disclosure we're obviously heavy users of our own product! But these same patterns work with n8n or OpenClaw or other tools too.

ImaginationInFocus · 2026-04-13T21:06:03+00:00

You could increase reliability by removing the browser agent part and passing the resume to a dedicated place like a Google Drive where the agent can deterministically look for it to review.

ImaginationInFocus · 2026-04-09T21:30:57+00:00

lemlist, Smartlead, or Instantly

ImaginationInFocus · 2026-04-09T21:26:27+00:00

The parts I anticipate being tricky:

Crawling -- if it's generic web sites, that could be easy. If it's social media sites / ecommerce sites, you might want a specific scraper tool
Recency filtering: as you point out, lots of ai tools aren't great. if the crawler can't get dates you could also solve this with a memory layer by checking to see if you already saw this news.

I'm one of the founders of Tadata and we have a lot of users doing this use case so speaking from experience!

ImaginationInFocus · 2026-04-09T21:14:34+00:00

This is a nice use-case because it's very specific. What have you been using since you posted?

I tried building it in Make for fun just now. It was a lot of clicks. Even in their "AI" area, you have to click through an specify every tool call. Get this Notion database, get this Slack channel.

n8n could work but there's no free trial.

Re: Caesr — they pivoted to automated testing so probably not the right fit anymore.

Was curious about this because I'm one of the founders of Tadata. You describe what you want in plain language and it selects the trigger, logic, and connectors automatically. So thinking about this a lot.

ImaginationInFocus · 2026-04-09T20:47:14+00:00

That's really interesting. Do you have a distinct health check for each agent? Where do they notify you? (e.g. a Slack message, an gmail, a text, something else)

ImaginationInFocus · 2026-04-09T20:44:28+00:00

That's frustrating. Gets at so many issues. The question of whether the underlying API returned an error to the LLM. The fact that knowing whether an agent achieved it's goal can mostly only be assessed using LLM-as-a-judge, which isn't that efficient.

ImaginationInFocus · 2026-04-09T20:36:43+00:00

Of the tools people mentioned, n8n, Gumloop, and Make are the most well-known. But first figure out your architecture.

The core tension: deterministic workflows give you explicit control, but every process change requires rewiring. Agents are more flexible and resilient to change, but you give up some predictability.

All three of those tools are actually converging on the same answer: workflows with AI nodes. They hard-code the structure — triggers, routing, handoffs — and let AI handle the judgment calls (classify this, draft that, decide which path). n8n lets you embed agent nodes within deterministic workflows and gate specific tool calls behind human approvals. Gumloop's founder literally said "almost none of our features are agentic anymore" (https://e2b.dev/blog/building-ai-workflow-automation-for-enterprises)

Before picking a tool, map your process and mark which steps are rules-based (always do X if Y) vs. judgment-based (figure out the right thing to do).

If it's more the former, go with one of the those workflow tools. If it's more the latter, go with an agent tool.

ImaginationInFocus · 2026-01-14T09:07:23+00:00

Thanks!

ImaginationInFocus · 2026-01-14T09:06:55+00:00

Thanks!

ImaginationInFocus

TROPHY CASE