‎I’d also look at how much control you have over what the AI is allowed to do. Answering FAQs is one thing, but letting it check orders, update information, or trigger workflows is where these tools get much more interesting.
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‎I’d be interested in seeing the actual monthly cost after usage, not just the advertised plan price. AI usage can change the economics pretty quickly once you have real customer traffic.

This makes a lot of sense for customer support. Customers shouldn’t get completely different answers depending on who happens to respond or what time they reach out. An agent can help keep the experience more consistent while still handing complicated cases over to a person.

‎I don’t think traditional SaaS is going away though. There are still plenty of situations where I’d rather have direct control than let an agent make the decision. I see the future as a mix of automation for routine work and humans stepping in when judgment actually matters.

‎What I’d really want to know is how well it handles more complicated requests. Updating a simple instruction sounds easy, but being able to analyze conversations and actually suggest useful improvements would be much more valuable to me.
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I’d probably avoid building another general AI assistant. There are already too many of those. I’d rather pick one specific industry and solve one painful workflow extremely well.
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I’d start with one capable agent, but I wouldn’t try to make it do everything on day one. Once the workflows become complex enough, I’d split specific tasks into specialized agents where it actually improves reliability.
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I think the fastest way to get the first 100 SaaS users is to start with a specific audience rather than trying every growth channel at once. Personally, I would focus on solving a real problem for a small group, engaging with them in communities where they already spend time, and using their feedback to improve the product.<div> Referrals and word of mouth can become powerful once users see real value.</div>

I wouldn’t switch from Zendesk or Intercom based on AI capabilities alone. The real test is how well the platform handles complex tickets, escalations, and human handoffs in everyday operations. The biggest differentiator would be whether AI genuinely reduces the workload for support teams while maintaining a great customer experience. Ultimately, it’s not about having the most AI features. It’s about making customer support simpler, faster, and more reliable.

I think the biggest advantage is consistency. One agent across channels can reduce duplication and maintenance, as long as the workflows are flexible enough to handle the differences between each channel.

I think customization is valuable early on, but too much of it can become technical debt later. The key is keeping the AI flexible enough to evolve without rebuilding everything whenever the models or product change.

I’d launch immediately. A waitlist can build anticipation, but real users give you feedback and insights that interest alone can’t provide. You can always build a community after launch as the product grows.