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Just shipped an AI resume screening system 🎯 Reads incoming resumes via Gmail, scores each candidate automatically with AI, and instantly alerts HR on Telegram — high score or low, no manual sorting required.
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• Aug 8
AI News Digest
I built an automated AI News Digest with n8n that collects the latest AI & automation news from RSS sources, selects the most relevant items, summarizes them using Groq AI, and delivers a structured daily digest directly to Telegram.
The workflow runs automatically every day, eliminating the need to manually check multiple sources.
Built with n8n, RSS, Groq API, Telegram API, and JavaScript.
A simple example of how AI automation can turn information overload into a useful daily workflow.
My core stack is less "generate pretty pictures" and more "build the pipeline that does the thinking":
n8n — the glue. Great for orchestrating multi-step agent workflows and connecting APIs without writing a service from scratch. Weakness: gets messy fast on complex branching logic, and debugging a broken node chain eats time.
RAG (usually with a vector DB + LangChain-style retrieval) — lets me ground LLM output in actual client data instead of hallucinated generalities. Strength: dramatically improves accuracy for domain-specific asks. Weakness: chunking/retrieval quality is finicky, and a bad embedding setup silently tanks results without throwing an error.
Claude/GPT for reasoning + code — my default for anything needing judgment: analysis writeups, SQL/Python generation, proposal drafting. Strength: fast iteration. Weakness: still needs a human check on numbers — confident-sounding ≠correct.
Power BI / Tableau — where the AI output actually becomes something a client trusts. AI can shortcut the analysis, but the dashboard is what gets signed off on.
The honest lesson: the "AI" part is maybe 30% of the workflow. The rest is validation, data plumbing, and making the output legible to a non-technical stakeholder.
Silent failures are what I watch closest. I treat an answer as untrusted unless I can show exactly which source text the model read, because fluent output can hide a bad match.
My topic:Livestream & VTuber
Hi, I saw online that IRL LiveStreaming is one of the hottest niches for some time now, but it is also the most dangerous one. I saw multiple videos of streamers being intimidated, provoked and even harassed.
This is not about streaming, its about humans feeling safe.
Today, in 8 full focused hours I put the pillars of the project PulseOS.
It gives updates to the creator about:
-Idle: basic state
-Notifications : ex: one new paid subscriber
-Ai-Summaries: ex: summary of the last 5 minutes of the live-chat energy
-Critical-Alert: ex: someone is following a creator, the chat is typing more than the usual flow of messages->activates triggering automation->creator sees what the chat is talking about
I projected this idea with 7 pillars, so here are the next 3, which I sacrificed for this demo, to be able to do the 4 pillars as intended.
The other 3 pillars:
-Stream health: ex: camera battery %, temperature of CPU
-Focus mode: ex: when streamer is serious, notifications are subtle almost non-existent for that time
-Achievement: ex: 1000 followers in the past month, 12 hours live in the past 3 days
I got around the paywall and prototyped a flux on notification with Make.com on HTML with POST Requests with the help of Ably.
Rive App Link:https://editor.rive.app/file/pulseos/2491853?linkId=2t4qGJlgK0GkdLA8qFPpDw
X link:https://x.com/ydgsgiwhs/status/2085972264185409606?s=20
future note, you can "share" a file on the rive freeplan by making a copy and putting it into the 'Shared Project',
then in the file using the invite button in the top right to get a link. I say a copy because once you put a file in a shared project you can't move it back to a...