
Nidhi Singh
@nidhisinghattri • 5,328 subscribers
everything about ai and tech | watch me on youtube brand collab dm me prev @pythnetwork @berachain @walmart
Videos

i tested Qwen3.8 27B locally on my M4 Pro to see how it behaves as a coding agent inside my project showing step-by-step the full guide on how you can run it, perfect for your first local model 00:00 Why I’m testing Qwen3.8 00:49 What Qwen3.8 includes 00:59 Qwen3.8 Max vs 27B 01:14 Qwen3.8 Max explained 02:13 Qwen’s benchmark claims 02:31 Its autonomous coding project 03:18 Qwen3.8 27B explained 04:30 Why I’m testing it locally 05:05 Download Qwen 3.8 in LM Studio 06:00 Pick the Q4 model 06:41 Run it as a local server 07:33 How fast is it? 08:36 Set up OpenCode 09:33 Connect LM Studio to OpenCode 10:03 Add Qwen 3.8 to OpenCode 11:34 Match the context settings 15:00 Give Qwen a real coding task 15:49 A mistake I caught live: session compaction 18:00 Review the code 19:30 My verdict
Nidhi Singh43,169 views • 2 months ago

if you switched away from MCP because it felt bloated, the latest update will make you look at it again i went through what changed, what hasn’t been fixed and why MCP deserves another look 0:00 Why everyone thought MCP was dead ? 0:38 What is MCP 1:25 Why companies started moving away 2:06 The real problems with MCP 3:34 July update 5:22 The tool bloat problem is still here 6:47 How progressive disclosure can help 7:42 Why I think MCP is here to stay ?
Nidhi Singh10,368 views • 2 months ago

My new video of DeFi series is out! In this one, we discuss the core primitives of DeFi. 00:00:16 - Core Primitives of DeFi 00:00:35 - Stablecoins and its types 00:05:03 - Lending and Borrowing 00:08:38 - Liquidity Pools and Market Makers 00:12:45 - Decentralized Exchanges and its models Follow my channel on YT to stay tuned for more such content. Like and RT if you find it useful ❤️
Nidhi Singh50,336 views • 1 year ago

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2
Nidhi Singh16,289 views • 4 months ago

i have built ghost work, a private freelancing platform where your rate is nobody's business -> fully onchain -> leverages Canton Network sub-transaction privacy -> no encryption, no access control lists(ACLs), privacy is there at the protocol level this demo was taken in one shot haha, at very early morning :D
Nidhi Singh12,099 views • 8 months ago
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