Most ai chatbots' conversations are very hard to get right and they bloat as context grows.
I think its because most builders treat conversations like a straight line.
To ACTUALLY build high level agents, you need to master conversational branching logic.
Here is the blueprint we use at @akapulu_ai to build these chatbots at a high level🧵:
Everyone benchmarks realtime Ai avatars on latency
But i believe the real test is what it does when nobodys talking
Bad ones freeze or loop. Good ones kind of just sit there and breathe
Idle behavior tells you way more about render quality than raw speed does!!
Hey guys!
I'm so excited to finally show you what I've been working on for the better half of a year. Our avatar platform, Akapulu Labs, is finally ready.
The way it works is you design the whole conversation yourself beforehand (scenarios) and then you choose which avatar you'd like to speak with. It sees you through your camera, answers from its own knowledge, and can even take actions like booking an appointment from your browser.
I put together a full tutorial walking through how to build one from scratch, start to finish. Would mean the world if you checked it out :)
Hope you guys like it!
https://t.co/MCMYePoyhZ
Got a black eye in jiu jitsu yesterday and i was actually able to use it for my AI avatar tutorial today. Helped show the vision function while booking my appointment lol
Full tutorial drops Friday!
Dropping a new tutorial this week , building a healthcare intake AI avatar with @akapulu_ai . Vision, real appointment booking , full transcript analysis, all in about 20 minutes or so
Changing environments temporarily has been the greatest productivty hack ive experienced haha.
Visted my sister out in utah and ive been here for almost a week.
Nothing to do except cook, workout, and grind🥀
Built this with Claude Code + Livekit agent Skills cool to see self-fixing errors and working voice agent in 15 min.
The skill vs MCP distinction is a game changer for voice agent dev
New tutorial: i got claude code to build a voice agent 40x better using LiveKit's new Agent Skills.
2% success from scratch → 80% with the right setup according to this blog: https://t.co/461d8yzO2o
Full build in 27 min plus why single-prompt agents break at scale.
https://t.co/A2sWoBwWNb
Best ai agents ive used in prod are the ones that dont have much freedom
Like heavily constrained as opposed to being able to do whatever they want
Freedom is a UX problem in disguise lowkey
@agenticgirl Wild benchmark numbers. Curious how it holds up in a live conversation loop. Synthesis + latency is where it gets real, i assume it would do really well!
Guys there are two 'ai avatar' markets that i think people combine but theyre really separate
Type 1: avatar renders video from your script.
Type 2: Avatar holds a live conversation in real time.
Different tech and different buyers, bc theyre fundamentally different problems
Important to know which one youre building
Weve documented this mini philosophy and the specific node structures at:
👉 https://t.co/WnazLWX86S
If you want to see me actually build these live feel free to check the YouTube channel @JamesAkapulu
Follow for more deep dives into this type of stuff!
Most ai chatbots' conversations are very hard to get right and they bloat as context grows.
I think its because most builders treat conversations like a straight line.
To ACTUALLY build high level agents, you need to master conversational branching logic.
Here is the blueprint we use at @akapulu_ai to build these chatbots at a high level🧵:
Id say majority of builders only design the "Happy Path" (the perfect conversation)
But in reality you need to build for "Detours."
Eg recursive fallbacks. If the AI doesn't understand the intent after 2 tries, the branch logic should automatically pivot to a human handoff or a simplified menu.
Complex branching logic is the difference between a toy and a tool.
When you solve for intent-switching and state-retention, it feels a lot less robotic and more like the (cliche i know) "digital employee" .