Komes_c

[Vaishnavi @_vmlops]

MICROSOFT'S FREE AI AGENTS COURSE

The best resource to go from zero to building production ai agents.

→ 15+ lessons with code + videos
→ agentic RAG, multi-agent, tool use
→ memory, planning, browser-use agents
→ MCP & A2A protocols included

all free.... all open source

https://t.co/M4s5joeXrr

[Priyanka Vergadia @pvergadia]

Palantir's end-to-end Agentic AI Architecture!

[Daily Dose of Data Science @DailyDoseOfDS_]

Build a 100% open-source deep researcher that you can easily self-host.

[ae^((-(x-b)^2)/(2c^2)) @JohnGalt_is_www]

Que gran articulo, pense que era mucho mas simple armar mi propio harness, habia varias cosas que no habia ni contemplado, es todo un mundo, interesantisimo, mucho mas que los LLMs en si

[Gartner @Gartner_inc]

Announcements from Google Cloud Next 2026 marks a turning point ⏎ and it puts agentic AI squarely at the center of the enterprise operating model 🎯

The annual event highlighted a shift from standalone AI tools to agent-centric enterprise operating models. Spanning multiple layers of the stack, these announcements illustrate both opportunity ✅ and risk ⚠️ for enterprise IT leaders.

Enterprise IT leaders can take away these key lessons from our First Take: https://t.co/WUrHJhrpUw

[Khairallah AL-Awady @eng_khairallah1]

https://t.co/rqmJCCumMf

[Alex Xu @alexxubyte]

12 Claude Code Features Clearly Explained

- CLAUDE.md
- Permissions
- Plan Mode
- Checkpoints
- Skills
- Hooks
- MCP
- Plugins
- Context
- Slash Commands
- Compaction
- Subagents

[Shann³ @shannholmberg]

how to stop claude from being a YES-MAN

Ole built a skill that forces 5 AI advisors to argue about your question, blind-review each other, and hand you a verdict you can trust

Here's how it works and how to set it up 🧵

[Gartner @Gartner_inc]

Parts of AI are heading fast into the Gartner Hype Cycle’s Trough of Disillusionment, but don’t mistake the trough for a decline.

Rather, it’s a sign that adoption is maturing and expectations are stabilizing.

Prepare now for the AI shockwaves that will reshape your industry: https://t.co/SQIrOH35Lp

#AI #ArtificialIntelligence #AIAdoption #Leadership

[Microsoft Tech Community @MSTCommunity]

⏳ 2 days to go!

Join us March 18 for the Live AMA: Microsoft Agent 365. Get your questions answered by Microsoft product & engineering experts.

👉 Register now: https://t.co/eYM5yomuOm

[World Economic Forum @wef]

#AI delivers results, but the real advantage comes when it reshapes #work and decision-making.

Explore how organizations can scale AI successfully in this latest report, produced in collaboration with @Accenture: https://t.co/nt6nDw4acJ

[Komes_c @komes_c]

#AITrends #CNBC
China + OpenClaw: การ adopt AI ระดับประเทศ จีนกำลัง embrace AI agent "OpenClaw" อย่างรวดเร็ว โดย Tencent เปิดตัว suite ของผลิตภัณฑ์ที่สร้างบน OpenClaw และ ByteDance เปิดตัว "ArkClaw" ที่ใช้ได้ผ่าน web browserไม่ต้อง setup ซับซ้อน การใช้งานในจีนแซงหน้าสหรัฐฯ แล้ว

[McKinsey Global Institute @McKinsey_MGI]

AI will not make most human skills obsolete, but it will change how they are used. MGI research shows that most skills employers demand today are common to both people-led and AI-led activities.

Check out our new Skill Change Index, which shows what skills will be most and least exposed to automation in the next five years: https://t.co/YoEIiZ5q47

[Gartner @Gartner_inc]

AI literacy is now essential for government workforces aiming to harness AI’s full potential ➡️ https://t.co/s9rEbXCAJn

Discover why it’s a cornerstone of every successful AI strategy in our on-demand webinar.

#GartnerIT #AILiteracy #Strategy #AI

[elvis @omarsar0]

Efficiency in LLMs

Pay attention, devs.

This is one of the most comprehensive benchmarks to date on improving the efficiency of LLMs.

You don't see reports like this every day.

Here are my notes:

[Vasek Mlejnsky @mlejva]

We (@jamesmurdza) have been building Open Computer Use - 100% open source computer use agent.

The agent is using @e2b_dev's Desktop Sandbox as virtual computer.
🔗 Full open source repo 👇

The agent is using 3 different LLMs:
🔸Llama 3.2 (@AIatMeta)
🔸Llama 3.3
🔸OS-Atlas (@Alibaba_Qwen)

It's slow and makes mistakes but this is a big milestone for OS AI community!
Seeing the progress on this project, it's clear that the full computer use will be possible with the next generation of OS models (6-12 months?).

[Henry Shi @henrythe9ths]

There's a shocking fact about AI that nobody tells you: You can catch up to the public AI research frontier in just 2 weeks. Yes, really.

I've built a $150M annual revenue startup over the last 8 years and If I were to start a company today, I’d drop everything and go all-in on AI.

But like many busy software builders, I felt lost—overwhelmed by the noisy, crowded and fast-moving modern AI landscape. And I wasn’t alone.

So I spent my entire holiday diving deep into AI research—reading 30+ papers, watching hours of lectures, analyzing trends, and catching up to the research frontier.

✨ Here’s what I learned:
- You don’t need months (or years) to catch up.
- You don’t need a PhD or decades of ML experience.
- You need fewer than 20 papers and 2 weeks to understand the major breakthroughs shaping AI today.

It's because the technology is extremely nascent and most techniques that came before are no longer relevant:
- ChatGPT is barely 2 years old and Transformers are only 7 years old.
- Most game-changing discoveries happened within the last 4 years, driven by a few breakthrough ideas, scaling laws, and efficient matrix multiplication.

The biggest secret?
Many groundbreaking AI papers with thousands of citations are surprisingly simple and applied, like adding "let's think step by step" to the prompt, or simply asking the LLM over and over again to improve its answer (Self-Refine).

I realized there are tons of founders and builders in the same boat—wanting to dive deeper into AI but unsure where to start.

I've created an essential AI Guide that helped me catch up, in just 2 weeks, to the frontier of public AI research to figure out where the next opportunities and gaps were:
- Curated list of only the most important papers
- Simple explanations of key concepts
- Clear pathway to understanding the frontier of modern AI

It’s perfect for:
- Founders expanding into AI
- Builders wanting to innovate at the frontier of AI
- Investors looking to separate the signal from the noise

👇 Want the full guide?
- Like and Share this post
- Comment "AI Guide"
- I'll send you the complete guide

(ps, I’m also teaming up with @VishalVasishth, co-founder of @obviousvc with @ev (focused on large-scale societal impact companies like Twitter, Medium, Beyond Meat), to host a small meetup to discuss what's working and needs to be solved in the AI stack in SF. Message me if you're interested)

[Kirk Borne @KirkDBorne]

LLM Engineer's Handbook — Master the art of engineering Large Language Models #LLMs from concept to production: https://t.co/mVpoE6jfXG v/ @PacktPublishing
——
#DataScience #LLMOps #ML #GenAI #AI #GenerativeAI #MachineLearning
——
𝓦𝓱𝓪𝓽 𝔂𝓸𝓾 𝔀𝓲𝓵𝓵 𝓵𝓮𝓪𝓻𝓷:
🟢Implement robust data pipelines and manage LLM training cycles

🔵Create your own LLM and refine with the help of hands-on examples

🟢Get started with LLMOps by diving into core MLOps principles

🔵Perform supervised fine-tuning and LLM evaluation

🟢Deploy end-to-end LLM solutions using AWS and other tools

🔵Explore continuous training, monitoring, and logic automation

🟢Learn about RAG ingestion as well as inference and feature pipelines

[Alex Reibman 🖇️ @AlexReibman]

Model Context Protocol (MCP) is a new open standard for connecting LLMs to tools, data, and dev environments

Anthropic invited 100+ developers to SF to see what we could build in only 3 hours.

Here’s what we saw at the @AnthropicAI MCP Hackathon (🧵):

[Komes_c @komes_c]

My Learning from LLM Agents at Berkeley RDI Center https://t.co/C93ddH1VjG