Nishant

Project Management & ESL Teaching

[Marktechpost AI @Marktechpost]

NVIDIA AI's NOOA: An Object-Oriented Python Framework That Turns an AI Agent Into a Single Python Class

Here's what's actually interesting:

1. The whole agent is one classMethods are the actions the model can take. Fields are state. Docstrings are prompts. Type annotations are contracts the runtime enforces. A method whose body is ... becomes an LLM-driven loop; a method with a real body stays deterministic Python the model can call as a tool.

2. Pass by reference is the load-bearing pieceArguments stay live in the execution environment. The model sees a bounded preview — concrete type, true length, head/tail sample — and writes code against the real object. → SWE-bench sessions peaked at 22–72k prompt tokens against 200–400k windows → No context compaction needed

3. The benchmark numbers
→ 82.2% SWE-bench Verified with GPT-5.5, from a benchmark-agnostic 253-line agent
→ 86.8% CyberGym L1 with network access blocked, top open-source result reported
→ 85.1% mean RHAE on ARC-AGI-3 with GPT-5.6-sol, under $20 per game
→ ~1.1M tokens and ~28 model calls per task, against 2.2M and 66 for the compared harness

Full analysis: https://t.co/lXQ6GbbfOB

Paper: https://t.co/RCI2T9Y4Ck

Technical details: https://t.co/OoqdKhhBZl

Repo: https://t.co/9EoLRzBJe0

@nvidia @NVIDIAAI

[Marktechpost AI @Marktechpost]

If you want to build an agent that actually remembers what happened, our guest author from MongoDB published a full tutorial for it along with Codes.

It's an event venue operator agent built on MongoDB Atlas, Voyage AI embeddings, and LangGraph, with optional Langfuse tracing. The scenario is a fictional tennis tournament on Day 6 — rain approaching, covered hospitality constrained, two visitor journeys to protect.

Here's what you'll build:

1. One backend for the whole agent stack Operational records, semantic memory, visual document embeddings, agent actions, and LangGraph checkpoints all live in Atlas. No syncing into a second vector database.

2. A namespaced memory store

→ ("guests", guest_id) for visitor-specific memory
→ ("fleet", event_id) for event-wide operator patterns
→ ("docs", event_id) for visual operational documents
Scoped retrieval, single data layer.

3. Vector and hybrid retrieval you can curl

The hybrid endpoint returns vector score, lexical score, and combined score. Event-ops queries mix semantic intent with exact terms like "covered seating," so both signals matter.

4. Vision RAG over operational images

Five seeded documents — capacity charts, weather-response sheets, evacuation diagrams — embedded with Voyage multimodal, retrieved from Atlas, passed to Claude Vision.

5. A LangGraph loop that closes perceive → plan → hitl_gate → act → reflect. Reflect writes new inferences back to semantic memory, so the next disruption starts with context.

6. A FastAPI app you can deploy Python 3.12, uv, local run, smoke test against Atlas, and a Vercel deployment path for a hosted demo.

Full tutorial: https://t.co/lZTseFLnj4

Github Repo: https://t.co/QwwYyYxHPg

Live demo: https://t.co/f8lo6QEwNn

@MongoDB

[Nishant @_nishant_33]

@teaganyuen1 @bondhq_ @upstream_do @viktor_com @StudyFetch @Vokal_team We love Bond :)

[Nishant @_nishant_33]

𝐀𝐈 𝐓𝐨𝐨𝐥𝐬 & 𝐀𝐠𝐞𝐧𝐭𝐬 𝐔𝐩𝐝𝐚𝐭𝐞𝐬: Kimi Work, a local AI agent + 5 Claude Design Tips + ChatGPT & Gemini 101... 🧵

Starting something cool. Hope y'all like it :)

→ Free Newsletter: https://t.co/fpTqdt8Riu
→ Website: https://t.co/VGrtViizrZ

#AI #Free

[Nishant @_nishant_33]

Treading AI Tools & Agents # 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲

• @bondhq_ — https://t.co/4Y041Um4wR
• @upstream_do — https://t.co/HzBHNDwvdp
• @viktor_com — https://t.co/hpl86mrFfS
• Honen by @StudyFetch — https://t.co/QBeMYA1cSH
• @Vokal_team — https://t.co/3e53akeGFH

[Nishant @_nishant_33]

↗️ Top 5 Claude Design Tips to Get Better Outputs (Without Burning Your Tokens)

Claude Design is a dedicated tool to create designs, prototypes, presentations, and more. We spent some time digging into it to present the top 5 tips for good outputs.

→ https://t.co/7IgPWDyaG0

[Marktechpost AI @Marktechpost]

We at Marktechpost been building a GitHub repository of 300+ hands-on Jupyter notebooks covering the tools, models, and frameworks that actually matter for AI Agents and Agentic AI

Here's what's inside:

→ LLM fine-tuning, RAG pipelines, and agentic workflows — end to end
→ Notebooks for open-source models: LLaMA, Mistral, Qwen, Gemma, and more
→ Covers LangChain, LlamaIndex, HuggingFace, vLLM, and the full modern stack
→ Every notebook is runnable — Google Colab links included
→ Updated continuously as new models and frameworks drop

The goal was simple: if you read about something on Marktechpost, you should be able to run it the same day.

300+ notebooks. Zero paywalls.

https://t.co/B8Z6nRou83

[Nishant @_nishant_33]

@carolineb2799 Gunther vs Seth was the only decent thing on the show 🫠

[Marktechpost AI @Marktechpost]

TinyFish just shipped four products under one API key: Web Search, Web Fetch, Web Browser, and Web Agent.

Each one addresses a specific failure point in AI web automation:

— Web Search returns structured JSON via a custom Chromium engine at ~488ms P50. Competitors average 2,800ms+.
— Web Fetch renders the full page in a real browser, strips everything irrelevant, and returns clean Markdown or JSON. Native fetch tools in most coding agents dump the entire page — CSS, ads, navigation — straight into the context window.
— Web Browser provides managed stealth Chrome sessions via CDP with sub-250ms cold start and 28 anti-bot mechanisms built at the C++ level.
— Web Agent executes autonomous multi-step workflows on real websites and currently sits at #1 on Mind2Web with 89.9% accuracy across 300 tasks.

All four are also accessible via CLI (npm install -g @tiny-fish/cli) with an Agent Skill — a markdown instruction file that teaches coding agents like Claude Code, Cursor, and Codex how to use every endpoint automatically.

CLI operations use ~100 tokens per task versus ~1,500 over MCP. Output writes to the filesystem, not the context window. 2× higher task completion on complex multi-step workflows.

One API key. One credit system. Search, fetch, browser, and agent — all built in-house.

Full analysis: https://t.co/Ip1ft7H1qF

500 free steps, no credit card: https://t.co/EAwiE3noaA

@Tiny_Fish

[Nishant @_nishant_33]

@cobley_ben Did you vibe code? 👀

[AIToolsClub.com @AIToolsClubb]

Top 10 Best AI Tools to Automate Your Entire Workflow in 2026 (No Coding Required)

1. @atoms_dev - https://t.co/UTZPEe00tG
2. @n8n_io - https://t.co/SYZsKWlLi5
3. @make_hq - https://t.co/jIsG8zF7cL
and more...

Save for later 🔖

🔗 Full read: https://t.co/9YxJ1ohJdg

#AITools

[AIToolsClub.com @AIToolsClubb]

I gave the same hand-drawn sketch and prompt to ChatGPT, Claude & Gemini to test which AI can turn it into a working app.

3 Different AI models.
1 Sketch & same prompt.
3 Different outputs.

🔗 Full read: https://t.co/UfYshpWXjF

#ChatGPT #Claude #Gemini

[AIToolsClub.com @AIToolsClubb]

Excel just got ChatGPT — ChatGPT for Excel powered by GPT-5.4 can build & edit spreadsheets and give you insights using plain language prompts.

▶️ Automate your entire workflow using this AI tool

🔗 Full read: https://t.co/4EmXzWrRnG

@OpenAI #GPT54 #ChatGPTforExcel #ChatGPT

[AIToolsClub.com @AIToolsClubb]

Two AI models launched in one day:

▶️ Google Gemini 3.1 Flash-Lite, a ultra-fast & ultra-cheap AI model for devs & enterprises

▶️ ChatGPT-5.3 Instant, a fast new model for smoother, more useful everyday conversations

🔗 Full read: https://t.co/Yrj5GRo8bh

@GoogleAI @OpenAI #AI

[AIToolsClub.com @AIToolsClubb]

Stop paying $$$/monthly... 7 FREE Google AI tools—Stitch, AI Studio, Opal, NotebookLM, Pomelli, Gemini Canvas, Nano Banana 2—that can replace paid software.

If you’re paying for AI, this thread might cost you a subscription. 🧵

🔗 Full read: https://t.co/EmVrQncJUz

#GoogleAI

[AIToolsClub.com @AIToolsClubb]

I Made ChatGPT Agent Mode Run Claude AI to Automate a Full Workflow (Step-by-Step)

In this article, we made ChatGPT Agent mode use Claude AI to vibe-code a macOS simulation—completing the entire task on your behalf.

↗️ Full read: https://t.co/QEaHMdqNg7

#ChatGPTAgent #ChatGPT

[AIToolsClub.com @AIToolsClubb]

ChatGPT vs Gemini vs Claude vs Perplexity 🥊

I tested popular AI assistants (ChatGPT, Gemini, Claude, and Perplexity) to see which can help find the best deals on 3 random products.

Save for later 🔖

↗️ https://t.co/Q2twt12eWr

#ChatGPT #Gemini #Claude #PerplexityAI