Phanindra Mangipudi

Staff SWE @ Grainger

[Anatoli Kopadze @AnatoliKopadze]

Google just dropped a free 8-minute lesson on building your first AI agent.

This is the clearest explanation of AI agents and loops you'll find anywhere.

People are paying $500 for courses that teach less than this.

Watch it, then read the step by step guide on building loops for your agents below.

[AdiiX @adiix_official]

Andrej Karpathy after watching some guy turn Claude Code + Obsidian into a $100K/month agent and realizing his 4-hour tutorial is now obsolete

[Phanindra Mangipudi @_thePhani]

@systemdesignone playbook

[そう｜Claude Codeで始めるAI自動化 @so_ainsight]

無料で使えるのが信じられないGitHubツール10選：

1. yt-dlp
YouTubeを含む1,800以上のサイトから動画・音声を最高画質でダウンロードできる。字幕・メタデータも一括取得。YouTubeの対策を毎回突破して更新し続けており、172Kスターを獲得している。
https://t.co/wkNtOJbtpp

2. Stirling-PDF
Adobe Acrobatの主要機能（結合・分割・署名・OCR・圧縮・墨消し・変換）をすべてローカルで完結させるPDF管理ツール。ファイルが外部に送信されることがない。81K+スター。
https://t.co/SleJ1n4FS3

3. homepage
自宅サーバーやアプリの稼働状況を1画面に集約できる自己ホスト型ダッシュボード。企業向けシステム管理パネルと同等の機能が、無料で手元に用意できる。
https://t.co/KYec5GJGic

4. LocalSend
AirDrop代替の全デバイス対応ツール。Windows・Mac・Linux・Android・iOS間で、アカウント・クラウド不要、容量制限なしでファイルを送受信できる。同じネットワーク内だけで送受信が済む。
https://t.co/jWVruhyqNo

5. AppFlowy
Notionと同等のメモ・ドキュメント・データベース機能をオフライン優先で使えるメモアプリ。データは自分のマシンに保存され、外部に送られない。70K+スター。
https://t.co/B9Iopyikr8

6. immich
Googleフォトと同等の自動バックアップ・顔認識・AI検索・共有アルバム機能を、自宅のマシンで動かせる写真管理ツール。一度使うと手放せなくなる人が続出している。
https://t.co/8NEJ3gpAPp

7. Reactive-Resume
職務経歴書を無制限に作成・公開・管理できる無料ツール。履歴書サービスの大半はダウンロード時に課金するが、これは一切不要。38K+スター。
https://t.co/LxcgFMo01g

8. Whisper
OpenAIが作った音声文字起こしモデルで、99言語に対応。文字起こしアプリが分単位で課金している、その処理を担うエンジンがローカルで無料で動く。
https://t.co/sfAXTl4EDm

9. n8n
Zapierがタスクごとに課金していた「アプリ間の連携・業務フロー自動化」を、自己ホストで手数料なしに実現できるツール。数百の連携先対応で190K+スター。フェアコード（ソースコード公開型）。
https://t.co/pvJGzLdiyo

10. Firecrawl
URLを1回指定するだけで、そのWebサイトをAIが読み込める構造化データに変換できるスクレイピング基盤。月に数万円かかるスクレイピングサービスと同等の機能がオープンソースで使える。
https://t.co/k3RgEkh7Pf

[Param @ParamSiddh]

If I had 6 months to become an AI Infrastructure Engineer.

I’d do this.

Stage 1 — Linux + Networking
Processes, memory, GPUs, sockets, HTTP, TCP/IP basics.

Stage 2 — Python + Backend
Async Python, FastAPI, queues, concurrency fundamentals.

Stage 3 — GPU Fundamentals
CUDA basics, VRAM, batching, quantization, throughput.

Stage 4 — LLM Inference
vLLM, TensorRT-LLM, speculative decoding, KV caching.

Stage 5 — Distributed Systems
Load balancing, queues, retries, autoscaling, distributed workers.

Stage 6 — AI Serving
Model APIs, streaming responses, rate limiting, observability.

Stage 7 — Data Pipelines
Kafka, Airflow, ETL pipelines, vector indexing.

Stage 8 — Kubernetes + Cloud
Docker, Kubernetes, AWS/GCP basics, infra automation.

Stage 9 — Monitoring + Reliability
Prometheus, Grafana, tracing, AI cost monitoring.

Stage 10 — Real AI Systems
Deploy scalable chat apps, RAG pipelines, inference clusters.

Stage 11 — Open Source
Contribute to inference tooling or AI infra projects.

Stage 12 — Apply
AI Infra Engineer, Platform Engineer, ML Systems Engineer.

AI apps go viral.

AI infrastructure prints money.

[Kyrie @KyrieCheungYep]

Codex 公认最强的 6个 Skill，有没有你没装的

1、Superpowers（227k star）

给 Agent 装上一整套资深工程师的工作方法：
先拆需求，再写计划，按测试驱动开发，最后再派一个子 Agent 回头审查自己的代码。
这是目前最强的 Skill 之一，实至名归

2、OpenAI 官方插件

把 Codex 变成不同岗位的员工，让它不只会写代码，而是进入全岗位工作流。
数据分析可以接 Snowflake，销售可以接 Salesforce，另外还能做投研分析、内容创意、PPT 生成等任务。
开箱即接入 62 个商业应用、110 个预置 Skill。
现在非开发者已经占 Codex 用户的两成，而且比例还在持续上升

3、claude-mem（82k star）

给 Codex 装上长期记忆。
每次对话里的关键信息会自动压缩归档，新开会话时自动注入，不用每次都从项目背景讲起。
多个 Agent 通用，多个代理也能共享同一套记忆资源

4、Agent-Reach（27.7k star）

给 Codex 装上一双互联网的眼睛。
一条 CLI 就能让它去读、去搜 Twitter、Reddit、YouTube、小红书、B 站、公众号等 17 个平台。
否则 Agent 只能搜网页；有了它，就能翻帖子、看视频、抓热点和用户反馈

5、GitNexus（42k star）

把几十万行的老项目整理成一张代码图谱，让 Codex 看懂藏在深处的依赖关系、模块边界和抽象命名。
接手老代码、重构项目、排查历史包袱时，不再像两眼一抹黑

6、Humanizer-zh（10.1k star）

专门去掉 AI 写作痕迹，比如滥用的破折号、空话套话、机械句式。
写文档、README、博客时，最后过一遍非常好用

[Ajit kumar @ajitcodes]

🚨 BREAKING: I asked Claude to improve my LinkedIn profile.

It didn’t just improve it. It made it a recruiter magnet.

Here are the 7 exact prompts I used:

[Vox @Voxyz_ai]

stop telling Claude Code/Codex "do this".
stop telling Claude Code/Codex "write code".
stop telling Claude Code/Codex "fix this bug".

you're using a 𝘀𝗲𝗻𝗶𝗼𝗿 𝗔𝗜 like it's a 𝗷𝘂𝗻𝗶𝗼𝗿 𝗶𝗻𝘁𝗲𝗿𝗻.

here are 8 prompts and goals you can copy-paste directly.

[Fitness Doctor 🩺 @FitnessDr_]

Small swaps, massive gains

1

[Eric Cole @erichustls]

If I got laid off tomorrow & had to replace my salary asap, here’s exactly what I’d do:

1. Go to Instagram and start a fresh account. Use a spare email. No one has to know.

[Prime AI @primemans]

🚨 BREAKING: Claude can now perform stock market research like a top-tier consulting firm — for free.

Here are 10 Claude prompts that replace $100K/year stock analysts.

(Save this for later) 📌

[Vaibhav Sisinty @VaibhavSisinty]

The person who built Claude Code just taught prompting in 28 minutes, free.

What he covers in the first 10 minutes beats $300 courses. Works for developers and beginners alike.

[Yosuep Esteban @YosuepEstebanX]

Tenía 29 kg de sobrepeso, una barriga enorme y quería alcanzar un 13 % de grasa corporal en 2026. Lo logré con estas 25 reglas:

Regla 1. DEJA DE CORRER.

[Harman @itsharmanjot]

10 GitHub repos so good they shouldn't be free.

1. AutoHedge

An autonomous hedge fund built in Python with four AI agents: a director generates investment theses, a quant validates them, a risk manager decides position size, and an execution agent places orders. Operates live on Solana. With 'pip install -U autohedge', you can start trading immediately.
repo → https://t.co/q22EzesLoD

2. Vibe-Trading

A trading system using a Directed Acyclic Graph (DAG) model, featuring 64 finance skills and 29 preset specialist agent swarms. Includes analysis methods like Ichimoku, Elliott Wave, SMC, Black-Scholes, full Greeks, and risk parity. Its crypto desk provides liquidation heatmaps and token unlock tracking. You can observe agents debating strategies in real time.
repo → https://t.co/LZ5CYGMC1W

3. Fincept Terminal

A Bloomberg Terminal replacement that runs on your laptop. CFA levels 1, 2, and 3 analytics. 20+ investor AI agents (Buffett, Dalio, Soros). 100+ data connectors, including Polygon, World Bank, and IMF. Bloomberg charges $24,000 a year. This is free.
repo → https://t.co/dMM1WZxrw9

4. LibreChat

Every model ChatGPT runs, plus Claude, Gemini, DeepSeek, and 20 more. Self-hosted. Native MCP support. You own the data, the history, the infrastructure. OpenAI charges $20/month to use their wrapper. This costs nothing to use your own.
repo → https://t.co/457utdZUIF

5. Open Higgsfield AI

A self-hosted cinema studio with 200+ AI models. Flux, Midjourney, Sora, Kling, Veo, GPT-4o, SDXL all in one interface. Text to image. Image to video. Cinema mode with pro camera controls. No subscription. Your data stays local.
repo → https://t.co/WHCzBSFBW4

6. Open-LLM-VTuber

A Live2D AI companion that runs offline, sees your screen, hears your voice, and never forgets. Inner thoughts are shown as a separate text layer, so you watch the reasoning happen before words come out. Pet mode floats it on your desktop. Swap the LLM in one config line.
repo → https://t.co/5XVKUPr35X

7. Claude Ads

A free Claude Code skill that runs 190 audit checks across Google, Meta, YouTube, LinkedIn, TikTok, and Microsoft Ads. 6 parallel subagents firing at once. Consolidates into a single Ads Health Score ranked by revenue impact. Agencies charge $4,000 a month for this.
repo → https://t.co/AJRfpSB7B6

8. Agentic Inbox

Cloudflare just open-sourced an email client where an AI agent reads your inbox and drafts your replies. Runs entirely on Cloudflare Workers. Each mailbox lives in its own Durable Object. Your email never leaves your Cloudflare account. One click deploys it.
repo → https://t.co/QEEMtzoliV

9. Camofox Browser

An open source headless browser that makes AI agents invisible to bot detection. Spoofs navigator properties, WebGL, AudioContext, and WebRTC at the C++ level. The browser does not look modified because it genuinely is not. Accessibility tree output drops token cost by 90%.
repo → https://t.co/95d0V3o7vO

10. Hyperframes

HeyGen open-sourced a video framework that does everything Remotion does without React, without JSX, without teaching your AI agent a new format. The agent writes HTML. The framework renders MP4. GSAP, Lottie, and Three.js all work. Same HTML always produces the same file.
repo → https://t.co/ekquvYvTNC

These are not toys. Each one replaces a paid product you're still being charged for.

Pick one. Install it. Plug it into your workflow.

100% free. 100% open source.

[Rubén (El Artesano de Wordpress) @Aqui_mi_casa]

El nutricionista de Novak Djokovic reveló parte de su sistema alimenticio:

En su dieta evita el gluten, los lácteos y el azúcar refinado, es decir, reduce al máximo todo lo que le inflama o le roba energía.

Y lo sorprendente es que Djokovic cada mañana...

[GG Bondo @GGxBondo]

🚨 CEO Anthropic Dario Amodei właśnie dostał nokaut na oczach całego świata.

Chiński founder Moonshot AI Yang Zhilin wziął i wrzucił za darmo całą rewolucyjną architekturę Kimi Agent Swarm.

Rój ponad 100 agentów działających równolegle. 1500 wywołań narzędzi jednocześnie.

Zadania, które Claude 4.5 i GPT-5.2 robią w godzinę, Kimi załatwia w 15 minut.
40-minutowy masterclass na NVIDIA GTC, w którym Yang tłumaczy wszystko krok po kroku:
• Orchestrator + parallel reinforcement learning
• MoE na bilionach parametrów
• Kimi Linear i 3D-synergia kontekstu
Efekt?

Kimi K2.5 miażdży Zachód w kluczowych benchmarkach agentycznych (HLE-Full, MathVista, OCRBench, multimodal) i robi to 4–5× taniej.

[Sahil Bloom @SahilBloom]

Everyone needs to read this...

The Crab Mentality

(a visual thread)

[jason @jxnlco]

If you're using Codex, you might not know about this repo `openai/skills`

if codex is open right now just ask codex `take a look at skills installer, what are some skills I should install` and it'll know how to scan this repo for skills and install the ones you need

[Tech with Mak @techNmak]

These are literally the kind of LLM interview questions most candidates wish they had seen earlier.

A curated list of 50 LLM interview questions - shared by Hao Hoang.

What's covered:

Fundamentals:
→ Tokenization and why it matters
→ Attention mechanisms in transformers
→ Context windows and their tradeoffs
→ Embeddings and initialization
→ Positional encodings

Fine-tuning & Efficiency:
→ LoRA vs QLoRA
→ PEFT to prevent catastrophic forgetting
→ Model distillation
→ Adaptive Softmax for large vocabularies

Generation & Decoding:
→ Beam search vs greedy decoding
→ Temperature, top-k, top-p sampling
→ Autoregressive vs masked models

Advanced Concepts:
→ RAG (Retrieval-Augmented Generation)
→ Chain-of-Thought prompting
→ Mixture of Experts (MoE)
→ Knowledge graph integration
→ Zero-shot and few-shot learning

Math & Theory:
→ Softmax in attention
→ Cross-entropy loss
→ KL divergence
→ Gradient computation for embeddings
→ Vanishing gradient solutions in transformers

You don't need to follow me (@techNmak) and comment "LLM". I will put the link in the comments.