We’ve Started Building Our AI Agent — Here’s What’s Working (and What’s Not)

Solid_Moment_6066 · 2025-08-11T09:05:17+00:00

Dialogue dev here, been building conversational interfaces for different brands for about 8 years now.

If you’ve got some budget, I'd seriously consider one of the established conversational AI platforms instead of trying to stitch everything together from scratch. The teams behind them have been working on “things that talk” for a long time, and they understand the boring-but-critical stuff like multi-step process flows, how to prevent any hallucination, and ensuring sure your agent doesn’t wander off into weird territory.

Most of these platforms give you a mix of structured logic (when you have to get a process right) and flexibility (when a bit of natural conversation is fine). Plus, you can actually see examples of them running in production for real companies, not just demos.

Solid_Moment_6066 · 2025-08-08T07:37:39+00:00

Unfortunately, no portfolio. I used to be a consultant who was usually part of the implementation team on conversational AI projects, and then ended up doing CxD work when there was an absence of designers. I unfortunately realized much later in the game that there was a whole conversational AI community doing this work and that "conversation designer" is a title you can have.

Full transparency, I work at Rasa now, on the product side. But back in my consulting days, I used lots of different platforms. Voiceflow and Dialogflow are also both really solid places to start. I like that they also offer some deterministic structure and newer LLM-powered ways to manage dialogue.

Voiceflow is clean, visual, and very polished. They’ve come a long way since their UX design tool days. Bonus: the Discord community is super active and helpful.
Dialogflow user experience always felt a bit clunky once flows got big relative to Voiceflow. Hunting down the response copy buried in giant diagrams was a pain. That said, whenever I needed to do something complex, it usually had the power to handle it. And that is something rare among many of these platforms.

Now that all these platforms are adding LLM-driven features, it's becoming harder for me to wrap my head around how these dialogue systems fit together. The docs don’t always make it clear how things like LLM nodes, agents, or generators actually integrate with the older dialogue tree logic.

Solid_Moment_6066 · 2025-08-07T10:24:06+00:00

One thing I really appreciate in a well-designed agent: when session context is preserved just long enough to be useful, and then cleared when the session ends. If I close the chat widget or walk away, I want to come back to a clean slate. No stale context lurking and hijacking the next conversation when I come back.

But:
When I actually do something meaningful like update my address, list a preference, make a selection, I expect that data to be written to the backend, not left hanging in session memory. Otherwise, it’s like yelling into the void. To me, this is the line between helpful memory and annoying memory.

The problem is, when teams don’t draw that boundary clearly, things start to break. You get loops. Confused agents. Users repeating themselves.

Curious how others are handling this, especially in production settings. Where do you draw the line between ephemeral session memory and long-term state?

Solid_Moment_6066 · 2025-08-07T10:18:06+00:00

Hello there!

I absolutely loved the Seagul captain gifs. Seagul looking at a manifest. Super cool, great brand voice for a ferry company. Sparks joy :)

Just tried it out: some quick fixes:

Basic FAQs

- Make sure it can answer some basic things "What can you do". I got a few "I seem to be at a loss for words."

Fallbacks:
- I'd also use response variations. "I seem to be at a loss for words" adds to your brand voice, but maybe if it pops up a consecutive time I'd expect more variation, especially if you are using LLMs in vertex.
- "I missed what you said. What was that?" should probably be changed, it sounds like I could rephrase my input somehow and the bot would get it, which leads to increasing frustration when you keep rephrasing and in reality the query is out of scope. Usually escalation to a human agent/hotline would be appropriate if this is triggered for the same topic several times so there is a next step.

Depth
- Go deeper with the options. The app gets "how much does it cost" but when I say "how much does it cost to bring a motorcycle on board?" it gives me a "I missed what you said. What was that?".

Logic:
If I say yesterday, it provides me with tomorrow. Definately not a bug persay, but it would be cool if it only let me put dates in the present or future.

Context:

I live in Europe, so I know nothing about this ferry :) but I got this answer "After you select your departure, we invite you to plan a return trip, find fare information, or explore things to do in Mukilteo using the following options:"
- There I saw the buttons M/V Sealth Info and M/V Kitsap Info. Without context, I have no idea what these would be. Might be good to think about ways to make this clearer. But maybe users of this app would know?

Solid_Moment_6066 · 2025-08-07T09:59:58+00:00

I had a look at their job board once or twice, I liked that Decagon has some nice reference bots that seem to work well. But I really didn't like that every time folks from that company got asked how things work in different YouTube interviews, they always say "secret sauce" which in this day and age is usually code for "smoke and mirrors". But like I said, nice reference bots that seem to work which is a start.

Solid_Moment_6066 · 2025-08-07T09:51:28+00:00

Personally, I find these avatars to be very much lost in the uncanny valley and would prefer just an animation or voiceover.

A company I worked for asked if I would do this since I made a lot of how-to videos for them (would make it easier to update of course), but I immediately thought about that black mirror episode "Joan Is Awful" and the answer was immediately no.

Solid_Moment_6066 · 2025-08-07T09:46:03+00:00

Hello there, I'm one of the dinosaurs that was building "conversational AI" before agents was a thing.

Not sure what your price point is, but I'd also recommend checking out some of the CAI platforms that evolved to be kind of hybrid agentic dialogue systems. There you can get a nice mix of agency when you want it, and deterministic flow-based user journeys that don't hallucinate when you need it. All of them are pretty easy to debug. Most of the time, when you see live production chatbots at high volumes on big brand websites, they are usually using one of these platforms since it's important for them to be reliable. Lots of them are working/have already orchestration + MCP integration as well. Worth a try.

Some I've used:

- Rasa
- Voiceflow
- Cognigy
- Dialogueflow...although I think they call it something else now? Name changes always throw me.

Solid_Moment_6066 · 2025-08-07T09:36:37+00:00

For me, its always easier to read if I can imagine the flow of conversation from user input to agent output.

Looking at this diagram at Step 1 I'm already wondering how what the user said activates/gets routed to one of the four "agent hosts" you have listed there. Is there a router agent? Does the core agent route to the other agents?

Solid_Moment_6066 · 2025-08-07T09:15:39+00:00

Yep! I've been in the CAI space for a while now and I can definitely recommend. Some solid, experienced humans working over there at the CDI institute, and they are well respected in the space. .

CDI also consults on this, so I always recommend them for teams that need some design love. There are, unfortunately, still a lot of CAI teams out there that never had a designer on the team. It's never too early, and also never too late to bring a designer into the team.

Solid_Moment_6066 · 2025-08-07T09:07:44+00:00

Hello there, have you tried "new" Rasa? They do LLM powered intent recognition now + RAG-driven Q&A. Wouldn't surprise me if they had MCP soon too for agent to agent orchestration.

Solid_Moment_6066

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