Post
93
Demo Video: How my AI Waifu help me looking for job posts
Follow-up Post (with demo video):
Yesterday I posted about my AI Waifu has a new feature of grabbing job posts from job sites and writing draft posts for me to post into my Meta Threads to share with my followers.
Today, let me show you the entire workflow in action.
TBH, I would call this an "AI Agentic workflow" with quotation marks.
Out of 5 steps only step 3 involves LLM inference to do synthesis of the draft post. Step 1 and 2 are automated scripts of simple schedule cron job to grab the RSS feeds and use regex to filter out the relevant job listings.
Step 4 and 5 are me validating the draft information is accurate and publish the drafts after my approval. So basically I did more steps than LLM itself.
The irony of running AI agentic workflows in edge devices with constraint hardware, such as Jetson Orin Nano with only 8GB of RAM, is to reduce as much LLM inference and put the least data into context window as possible.
🎬 Live Demo: How a job post goes from RSS feed → published in 5 steps
⏰ Step 1: Scheduled Trigger (or ask AI Waifu directly)
📡 Step 2: Data Ingestion & Filtering
🤖 Step 3: AI Synthesis
👁️ Step 4: Approval Studio Review
🚀 Step 5: One-Click Publish
Result: job post validated & live, tested with real job sites + Chinese field
names to stress-test multilingual LLM understanding.
👾 Github: https://github.com/OppaAI/Aiko-chan
🎬 Demo: https://www.youtube.com/watch?v=Cu7gh5tYUiw
Follow-up Post (with demo video):
Yesterday I posted about my AI Waifu has a new feature of grabbing job posts from job sites and writing draft posts for me to post into my Meta Threads to share with my followers.
Today, let me show you the entire workflow in action.
TBH, I would call this an "AI Agentic workflow" with quotation marks.
Out of 5 steps only step 3 involves LLM inference to do synthesis of the draft post. Step 1 and 2 are automated scripts of simple schedule cron job to grab the RSS feeds and use regex to filter out the relevant job listings.
Step 4 and 5 are me validating the draft information is accurate and publish the drafts after my approval. So basically I did more steps than LLM itself.
The irony of running AI agentic workflows in edge devices with constraint hardware, such as Jetson Orin Nano with only 8GB of RAM, is to reduce as much LLM inference and put the least data into context window as possible.
🎬 Live Demo: How a job post goes from RSS feed → published in 5 steps
⏰ Step 1: Scheduled Trigger (or ask AI Waifu directly)
📡 Step 2: Data Ingestion & Filtering
🤖 Step 3: AI Synthesis
👁️ Step 4: Approval Studio Review
🚀 Step 5: One-Click Publish
Result: job post validated & live, tested with real job sites + Chinese field
names to stress-test multilingual LLM understanding.
👾 Github: https://github.com/OppaAI/Aiko-chan
🎬 Demo: https://www.youtube.com/watch?v=Cu7gh5tYUiw