
@learning_dev1i
iAccount based inIndia
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Learner
Joined March 2022
- Tweets2.4K
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Pintu (Learner) retweeted
I couldn't f*cking believe this
Stanford AI research team gave Claude Code a human brain setup.
JEV is the fast gut brain.
It scans everything in milliseconds and makes the easy calls.
Claude is the slow thinking brain. It only wakes up for the hard ones.
Here are the commands that wire the two together:
/plugin marketplace add rashedInt32/jev-mcp
/plugin install jev@jev-mcp
-> Claude gets Jev as tools: classify, score, check
npm install -g @dzhng/jevgrep
jg "how are payments retried?" ./my-project
-> ask what the code does, get the right files back. the author measured ~30% lower cost on the same tasks
npx skills add altryne/jevify --skill jevify
-> teaches your agent to hand the bulk yes/no work to Jev on its own
> and fast-jev-compaction swaps Claude Code's summary for Jev decisions: it drops stale tool calls and keeps everything else word for word.
Faster runs, smaller bills, barely any compute wasted.
Save this before your next session.
Pintu (Learner) retweeted
Grok Bot + Opus 5.5 is the most INSANE trading bot setup ever built
i plugged Grok Bot and Opus 5.5 into one stack and built an ORDER FLOW trading desk that is running autonomously 24/7
here is the EXACT system you can build today:
1. 3 exchanges stream the order book, every trade and open interest live for free, the raw flow a fund pays thousands for
2. the liquidity heatmap shows where the big orders are stacked, price gets pulled into those clusters, so you see where the market wants to go next
3. CVD shows if the buying is real, price up but CVD down means the move is fake and about to fail
4. Grok scans X in real time for breaking news, whale chatter and sentiment flips, the stuff that moves BTC before the chart reacts
5. on every candle the order flow and Grok's read get packed into one clean snapshot
6. Opus 5.5 reads that snapshot and returns buy sell or hold with a confidence score, 0.82 opened the trade, 0.64 held it
7. after fixed time Opus 5.5 reviews which calls actually worked and rewrites its own rules, so the desk gets sharper by itself
8. a hard risk layer caps every position at 1.5% of equity and the order goes out in 42 ms, for ZERO dollars a month in data
it reads every post on X the second it drops, the same edge a fund pays an entire sentiment team for
the full build is in my article below:
Pintu (Learner) retweeted
10 GITHUB REPOS THAT LET AI EXPERIMENT, CODE AND EVOLVE.
1. SWE-agent — AI that fixes real coding issues.
Give it a GitHub issue and let it navigate a codebase, edit files and attempt a solution.
github.com/SWE-agent/SWE-age…
2. Aider — an AI that codes directly in your repo.
Let it modify multiple files, work with Git and help you debug real projects.
github.com/Aider-AI/aider
3. OpenHands — build an AI software developer.
Give an agent a task and let it use a terminal, edit code and run commands.
github.com/OpenHands/OpenHan…
4. DSPy — program AI systems instead of hand-writing every prompt.
Optimize language-model pipelines using examples, metrics and systematic experimentation.
github.com/stanfordnlp/dspy
5. TextGrad — optimize AI systems through feedback.
Use text-based gradients to improve prompts and multi-step LLM workflows.
github.com/zou-group/textgra…
6. EvoAgentX — experiment with self-evolving AI agents.
Explore frameworks for building, evaluating and improving multi-agent workflows.
github.com/EvoAgentX/EvoAgen…
7. ADAS — automatically discover agent designs.
Research how AI can search for better agent architectures instead of relying on manual design alone.
github.com/ShengranHu/ADAS
8. OpenEvolve — evolve code through iterative optimization.
Use evolutionary search to generate, evaluate and improve program candidates.
github.com/codelion/openevol…
9. SWE-smith — create training environments for coding agents.
Generate software-engineering tasks and datasets for training agents to solve code problems.
github.com/SWE-bench/SWE-smi…
10. AutoGPT — build autonomous AI workflows.
Experiment with goal-driven agents that plan tasks, use tools and work through multi-step processes.
github.com/Significant-Gravi…
All are open-source.
Bookmark this. The next big leap might be AI that can improve how it works.
Pintu (Learner) retweeted
7 Questions to Ask When an AI System Suddenly Gets Worse
Your AI system was working perfectly yesterday.
Today, answers are inaccurate, responses are slower, or users are reporting failures.
Before changing the model, ask these 7 questions to find the real problem.
Pintu (Learner) retweeted
Look closer at Google's own Argon benchmark slide.
Argon wins most rows but it loses on the agentic coding and terminal tests
Those are the closest to real agent work and argon loses all four on google's own chart
Maybe that's why google is reportedly already testing Carbon internally as an Opus level for coding
Pintu (Learner) retweeted
50 Useful GitHub Repositories for Developers & AI Builders 🚀
Want to learn coding, build AI apps, and automate tasks? Save these useful GitHub repos! 👇
💻 Coding & Learning
1. Build Your Own X
2. Free Programming Books
3. Developer Roadmap
4. JavaScript Algorithms
5. 30 Seconds of Code
6. You Don't Know JS
7. freeCodeCamp
8. Coding Interview University
9. Project-Based Learning
10. The Art of the Command Line
🤖 AI & LLMs
11. Ollama
12. LangChain
13. Hugging Face Transformers
14. LlamaIndex
15. llama.cpp
16. vLLM
17. NanoGPT
18. DeepSeek
19. Open WebUI
20. Dify
⚡ AI Agents & Automation
21. n8n
22. CrewAI
23. AutoGen
24. MetaGPT
25. Langflow
26. Browser Use
27. Stagehand
28. Firecrawl
29. OpenClaw
30. TradingAgents
🛠️ AI Tools & App Building
31. Aider
32. ComfyUI
33. Lobe Chat
34. RAGFlow
35. Mem0
36. Supermemory
37. MarkItDown
38. AI Misalignment Testing (iFixAI)
39. Public APIs
40. Open-source AI workflows
📚 Developer Resources
41. System Design Primer
42. Tech Interview Handbook
43. Awesome Self-Hosted
44. GitHub .gitignore Templates
45. The Book of Secret Knowledge
46. Maigret
47. Awesome Claude Skills
48. System Design Interview Prep
49. AI Agents Ecosystem
50. AI App Development Tools
🔖 Save this list for your next project!
Follow for more AI tools, coding resources, and useful tech content.
Pintu (Learner) retweeted
gemini 4 flash / argon is already showing up in antigravity 👀
model name: "gemini-3.8-flash-exp-a"
but it's running at ~60 tokens/sec while 3.8 flash averages 100–150
google created more hype by NOT releasing it
Pintu (Learner) retweeted
Why is everyone suddenly talking about MCP? 🤔
Because Model Context Protocol (MCP) is quickly becoming the bridge between AI models and real-world applications.
Instead of isolated chatbots, MCP enables AI to securely interact with:
🔹 APIs
🔹 Databases
🔹 Cloud services
🔹 DevOps tools
🔹 Internal enterprise systems
This infographic breaks the journey into 12 simple days, taking you from:
📚 Fundamentals → 🏗️ Architecture → 💻 Implementation → 🚀 Production
If you're preparing for the future of AI engineering, this is a great place to start.
Save this roadmap so you can revisit it whenever you're ready to build your own MCP-powered applications.
Pintu (Learner) retweeted
Best accounts to follow from each frontier lab to stay constantly up to date
Anthropic
@karpathy -must-follow account for AI; recently joined Anthropic
@bcherny- Claude Code creator, always shares great tips
@trq212 also a Claude Code developer; writes amazing articles on CC
OpenAI
@polynoamial- works on reasoning research, shares a lot of technical details
@gabriel1- Sora developer, great career path
@jxnlco - works on dev experience, shares a lot about Codex
Google AI
@OfficialLoganK- all the major Google Gemini and AI Studio updates
@ammaar- product and design; shares great things about vibe-coding in Google AI Studio
@fofrAI- cool use cases for generative models
Cursor
@leerob- the loudest voice behind Cursor updates
@ericzakariasson- shares great insights on using Cursor
@mntruell - Cursor’s CEO; major releases and usage updates
xAI
@ai_explorer25- ex-MSFT, covers all ai content and free resources
@milichab - recently joined xAI, shares updates on Grok
@skcd42 - also covers major Grok releases
Pintu (Learner) retweeted
Today we are announcing our biggest bet yet on our own silicon.
Starting next calendar year, we will scale our Maia family to multi-gigawatt deployments, making it the primary inference system for our own product and services.
And we’re introducing Maia 300, which delivers 40% more tokens per watt compared to leading GPU-based systems.
We are already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot.
Our goal is to build on the full-stack efficiency gains we’ve already seen, while continuing to bring the latest innovations from across the ecosystem into our fleet.
If you use opencode, bookmark these 10 github repos
some of the most starred skill collections worth checking out
1. Superpowers (292k)
2. Ponytail (147k)
3. UI UX Pro Max (131k)
4. Graphify (122k)
5. Caveman (108k)
6. Addy Osmani Skills (99.4k)
7. Understand Anything (84.3k)
8. Awesome Claude Skills (75.7k)
9. Archify (72.5k)
10. Impeccable (71.7k)
important: github stars don't guarantee safety must inspect the files before installing
save this list for when you need it
DEEPSEEK V4.1 FLASH JUST GOT UNCENSORED
a new uncensored build is live on hugging face
supports FP8, MLX, EXL3 and safetensors
if you like testing open models, this one's worth a look
get it here
huggingface.co/dealignai/Dee…
Pintu (Learner) retweeted
Ben Affleck?
the AI engineer?
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models
“I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that.
“With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor.
“You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something.
“That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’
“I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
Pintu (Learner) retweeted
Guys Nano banana 2.1 is out and I don't have good news
The drift benchmark pitted head to head against Flux 3
And I don't think I need to tell you who won
Pintu (Learner) retweeted
Nano Banana 2.1 is here!
This upgraded version outperforms our previous models across the board, with notable leaps in:
- visual design
- mask-based editing
- subject consistency
- more natural-looking imagery
Try it now in @GeminiApp, @GoogleAIStudio, and more.
Meet Nano Banana 2.1, our latest image generation and editing model 🍌
This upgraded version outperforms our previous models across the board, with notable leaps in visual design, mask-based editing, and subject consistency to help you create more natural-looking images.
Pintu (Learner) retweeted
introducing @NanoBanana 2.1 🍌
our latest image generation model outperforms our previous models across the board:
- better visual design
- mask-based editing
- subject consistency
- more natural-looking images
try it out today in ai.studio
The Agent Arena ranks agentic ability to solve problems across domains.
U.S. labs lead across every domain:
- @AnthropicAI models hold the #1 position in Code, Work, and Chat
- @OpenAI's GPT 6 Astra (Max) remains in the top four across all three categories: #2 in Code and #4 in both Work and Chat
The leading models stay strong across categories, but their order shifts:
- Claude Fable 5.1 (Max) leads both Code and Work and ranks #2 in Chat
- Claude Sonnet 5.5 (Max) leads Chat and ranks #4 in Code and #5 in Work
Code and Work rankings move together more closely than Chat:
- Gemini 4 Argon (High), for example, ranks #14 in Code and #12 in Work but #5 in Chat, highlighting a distinct strength in conversational agent tasks
Agent Arena ranks models based on overall net improvement against the current frontier, as well as performance across specific categories of agentic tasks. These rankings are grounded in live traces collected from agents attempting to solve real-world tasks submitted by humans around the world.
- Code: writing and debugging code, workflow automation, and data analysis
- Chat: creative writing, learning, personal questions, everyday research, and media generation
- Work: documents, professional research, planning, and professional writing
This visual outlines how selected models compare across Agent Arena categories as of October 5, 2026.
Pintu (Learner) retweeted
🚨Gemini 4 Argon is being heavily used by Google engineers
I find it interesting after all the Bloomberg slander about it not being good, employees are actively choosing to use it over other models now
The Google employees involved in this normally used claude models too, so it's a clear sign that Argon is good
Even after all these days, Google still hasn't brought Gemini 3.8 Flash or even 3.7 Flash to free users in the Gemini app.
Are they thinking 3.8 Flash is some Astra, Opus or Fable level model that's only supposed to be available to paid users?




























































