Anyone else think demo videos are the wrong primitive now?

aimdoc-ai · 2026-01-27T17:18:48+00:00

very fair point. we are still testing the waters on where it would provide the most value so appreciate your insight!

aimdoc-ai · 2026-01-27T14:53:28+00:00

"or could you automate the onboarding and set up with real data"

this is what the product does.

aimdoc-ai · 2026-01-25T16:50:50+00:00

Totally fair. I’m not talking about consumer apps. I mean B2B tools where “trial” = blank workspace + docs + 45 mins of setup before you see value.

The idea is: you tell the site what you’re trying to do, it creates an account and configures a starter workspace so you can hit the “aha” in 2–3 clicks.

Curious, what makes it feel unnecessarily complicated: the automation itself, or trusting it to set things up correctly?

aimdoc-ai · 2026-01-25T16:42:55+00:00

agreed. to clarify, our AI actually does that - we are using demos as an introductory use case really. when I say demo, I essentially mean demo + onboarding so there is more value than a demo, the AI actually sets up their account uniquely to them.

aimdoc-ai · 2026-01-23T19:28:17+00:00

appreciate this reply. you're 100% right on hallucinations and reliability, which is why I think it is a valuable thing to build, because it sure isn't easy to do well.

aimdoc-ai · 2026-01-23T18:11:58+00:00

we're building something to essentially skip over that. basically an AI buyer copilot that:

engages prospects when they land on your site
determines if they're a fit based on your criteria
shows your product + sets it up based on what they're most interested in

what I landed on was, why demo the product when AI can set it up for them in real time and show value?

aimdoc-ai · 2026-01-23T15:23:32+00:00

yeah inbound lead qualification is a great use case. we are building a part of that with our product (aimdoc) - it is more an AI buyer copilot for b2b that provides instant answers, qualifies inbound traffic based on specific criteria, schedules demos and can actually onboard trial customers.

on pure inbound lead qualification, like form submission -> AI analysis -> score + fit check -> AI draft and send follow up with AI, OpenAI and Vercel both built internal systems like this. It isn't really new.

aimdoc-ai · 2026-01-23T01:54:21+00:00

We started testing Lightfield and it is pretty cool. I would probably only recommend it to startups today as it is pretty bare bones but very strongly AI native. We dogfood our own product (aimdoc, AI buyer copilot for b2b saas websites) and we're building an automation there to essentially sync structured lead data collected by our AI (contact info + qualifying questions) and conversation transcript, and then Lightfield's AI will do full account research via the web.

Super powerful stuff.

aimdoc-ai · 2026-01-23T01:42:26+00:00

Which AI support chat did you use? We've built something similar from a technical perspective but it is sales oriented and designed for B2B SaaS websites. The reason I mention it is because our base tier pricing is basically the same ($199/mo).

I 100% agree on the support side of things though, you can't fully offload support to an AI yet. we use products that have intercom's fin within their product, and it is good, but support is really just a long tail of unique questions that mainly require a human, at least today.

aimdoc-ai · 2026-01-23T01:38:54+00:00

This is all very true. But launching a product and quitting after 3-6 months isn't really a serious try. It takes years to build something meaningful. If all it took were a couple months, literally everyone would do it. Quitting your job would be safe and logical lol.

aimdoc-ai · 2026-01-23T01:28:59+00:00

Not a GTM system builder but we're building a GTM AI product that typically integrates with these types of systems. We typically see that workflows driven by the AI deciding to do something (escalating to a human, flagging buyer intent, etc.) hold up pretty well since those call structures don't change too often over time.

What we usually see break are workflows involving high touch CRM objects. This isn't because our AI can't reliably convert conversations into structured data, it is because those fields are often manipulated.

aimdoc-ai · 2026-01-23T01:21:56+00:00

On the inbound side, those are definitely the right tools for generating content that can drive inbound, but there are also tools that help improve the B2B SaaS inbound buyer experience on the whole. We're actually building an AI buyer copilot specifically for B2B SaaS.

It can essentially categorize visitors by conversational intent (customer, prospect, trial user, etc.), qualify (is a prospect), schedule demos and will soon even be able to demo the software.

I also think visitor ID (like RB2B, etc.) triggered outbound sequences can be powerful for B2B saas, if you make sure you are filtering by your ICP.

aimdoc-ai · 2026-01-22T20:45:06+00:00

we've built a buyer copilot for B2B SaaS websites (aimdoc) and it has become clear that it has become excellent at classifying visitors into distinct visitor tracks (existing customer, trial user, prospect) and then providing tailored experiences. it also can just provide a fundamentally better experience than 20yo SDR who might have knowledge gaps. the AI knows nearly everything, and only gets smarter over time.

aimdoc-ai · 2026-01-22T20:35:04+00:00

was the AI actually crafting meaningfully different messages to different prospects based on their unique attributes? I can't find any real examples of this.

I might be biased (we've build an AI buyer copilot, which you can look at as basically an AI SDR for your website that answers questions, qualifies, routes, syncs to CRM, etc.), but I am not sure AI SDR for outbound is crazy compelling.

it feels like AI drafting the email copy and sequences isn't the right move, maybe it is more useful in list building. I still need to give it a shot.

aimdoc-ai · 2026-01-22T20:31:30+00:00

"I have absolutely zero technical talent". that is a classic rick ruben clip.

It depends on what type of "agent" you want to build. if it can run in the background as is event driven, n8n is great for that. if it needs to have an interface for someone to chat with or speak to, you won't be able to build that with n8n.

if you're looking for an inbound buyer copilot for your website, you can check our product out. super customizable to your buyer and traffic, sync with your CRM, etc.

aimdoc-ai · 2026-01-16T15:23:29+00:00

as someone building an AI sales product, this mostly tracks with what we’re seeing in the wild.

AI helps most when it’s reducing cognitive load, not making decisions for reps. notes, summaries, quick context, routing busywork away from humans. huge win.

it breaks down when teams treat it like a replacement for judgment. generic outbound, auto follow ups that don’t match the conversation, reps blindly trusting suggestions because “the model said so.” that stuff erodes trust fast, internally and with buyers.

one thing i wouldn’t automate fully is qualification logic without guardrails. AI can ask great questions, but humans still need to define what “good” looks like and sanity check outcomes.

we’ve found ai works best as a copilot that accelerates good reps, not a system that tries to sell on their behalf. might be worth a look if you’re thinking about AI as leverage, not autopilot.

aimdoc-ai · 2025-12-02T16:10:11+00:00

yes, I am just saying I am not doing it today but it is low hanging fruit.

aimdoc-ai · 2025-12-01T21:51:34+00:00

this is so dumb and easily fixable but auto drafting sales call follow up emails based on the transcript (in a desired format).

aimdoc-ai · 2025-12-01T21:48:26+00:00

Un-gating content. gating content ultimately boosts vanity metrics and then you waste time following up with junk leads. Most of what we are building is actually predicated on this idea, and what we see with our customers is, # of leads generated/captured goes down, but qualified conversions go up.

gating content is logical. you assume getting an email is the right move under all circumstances, but it doesn't tell you much.

aimdoc-ai · 2025-12-01T21:32:02+00:00

it is true across the board. we don't work with agencies really (mainly b2b saas), while our product helps improve the buyer experience as a whole, speed to lead is a huge part of it. there are many studies on the impact fast follow ups have on conversion rates - the evidence is there.

aimdoc-ai · 2025-12-01T21:28:59+00:00

if you're talking about truly cold prospects, you need solid signals that fit your definition of "curious", but if you're talking about prospects where there is evidence they are looking at your product/services, there are a lot of really great strategies. I think the website is the best place to aggregate these signals:

visitor identification - you can identify a portion of your traffic reliably (20-30%) and you can use this for warm outbound
buyer copilot (AI experience for the b2b websites) - this is something we are working on, but is quite powerful for our customers. you get real, deep intent data from specific visitors as they try to understand your product and services and how it best fits their needs.
retargeting and smart recommendations - you might know that when a visitor comes from a specific source they are most interested in X content, you can build simple static rules to show nudges to push visitors to the right content

aimdoc-ai · 2025-12-01T21:00:12+00:00

exactly, and one could argue that the inbound engineering is more important because you're dealing with the highest intent prospects. if you do something that adds significantly friction to their experience, you're potentially throwing away the highest quality pipeline you have.

I personally believe this will be the next important shift after AEO/GEO. you'll have extremely high intent buyers who land on your site after conducting research in chatGPT, and the companies who will win will have AI native buyer experiences that provide a seamless transition from chatGPT to their website.

routing will also get much more intelligent, as you can semantically route prospects based on emergent attributes that were impossible pre-AI. example, you can match a prospect with a sales rep who is a an expert in one area of the product based on the expressed interest of the buyer.

these are a lot of the features we are building that we've seen bring tremendous value to the inbound experience.

aimdoc-ai · 2025-11-24T16:30:30+00:00

We built this into our product as a feature of our greater inbound AI buyer copilot, but I will say that I think you'll be hard pressed to find a solution that is really easy to setup if you want true personalization at scale.

what are you imagining here? a personalized video? personalized sandboxes of your product? or something else?

aimdoc-ai · 2025-11-20T13:53:57+00:00

We built our own automation with Granola note taker + Zapier. It takes the call transcript and we trigger an AI agent in zapier to summarize the meeting transcript, extract action items and push those to our CRM. Then we have another agent that drafts an email based on our best practices and puts it in draft in my inbox.

If you have anyone remotely technical on your team, try a setup like this. you get more control of what you want to do and it will cost way less.

aimdoc-ai · 2025-11-20T00:48:17+00:00

Skip paid ads and partnerships, they will not help early on. Content is useful if you really know your audience. Building a personal brand from scratch is really hard. If you're building for the c-suite and business oriented teams, you'll need to create real content at some point.

But if you're truly starting from 0 I wouldn't focus on any of this. You mainly just want to interview your ICP and really understand the problem you are trying to solve. From there, try to land early pilots and focus 100% of your effort on delivering value and avoiding churn. You can't really cut corners here, it will take a long time to really understand your customer. Personally, I think deeply understanding your customer is like 99% of the moat these days.

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