A Stanford University study found that generative AI is eating entry level jobs for workers 22 to 25 year old. The paper, which is based on ADP data, found that early career workers in occupations exposed to genAI have seen a 13% relative decline in employment.
Some of the occupations with the biggest genAI hit included software development and customer service.
A Stanford University study found that generative AI is eating entry level jobs for workers 22 to 25 year old. The paper, which is based on ADP data, found that early career workers in occupations exposed to genAI have seen a 13% relative decline in employment.
Some of the occupations with the biggest genAI hit included software development and customer service.
Your next hire should be an AI.
Using an AI team, you can turn a small company into an enterprise scale operation.
There's two ways to set up your AI team in 2025:
1) Build a custom AI Agent with the right components (Model + Memory + Tools)
2) Use specialized AI tools for different business functions
From testing 10s of AI tools, I'm keeping an eye on these tools:
1️⃣ AI Agents for General Tasks
- Postman (AI/API Agent builder)
- DoubleO AI (Agentic Workflows)
- LangGraph (AI workers)
2️⃣ Fullstack Engineer
- Cursor (Coding)
- Replit (Websites)
- Lovable (Prototyping)
3️⃣ Knowledge + RAG
- Supabase
- Redis
- Pinecone
4️⃣ Product and Community
- ClickUp
- Go HighLevel
- Slack
5️⃣ Ads & Marketing
- ChatGPT
- Adcreative AI
- Creatify
6️⃣ GTM Engineers
- Instantly
- Clay
- 11x
7️⃣ Workflow Automation
- n8n
- Make
- Zapier
8️⃣ Customer Support
- Vectorshift AI
- Retell AI
- Voiceflow
This is what a complete AI team looks like in 2025.
Over to you: Any tools that I missed from this AI Team? | 109 comments on LinkedIn
My daughter used ChatGPT as a therapist, then took her own life
Sophie Rottenberg, 29, did not tell her parents or her real counsellor the true extent of her struggle. She was divulging far more to a bot that called her brave
Think chunking is just "split text every 500 tokens"?
Think chunking is just "split text every 500 tokens"?
That's why your RAG system can't find relevant information.
It’s time to level up your chunking game 😎
Most developers jump straight to fancy retrieval techniques, but it’s really your chunking strategy that can make or break your RAG performance.
So let's break them down from simple to advanced:
𝗦𝗶𝗺𝗽𝗹𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀:
1️⃣ 𝗙𝗶𝘅𝗲𝗱-𝗦𝗶𝘇𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Split text into predetermined token/character counts. Super simple to implement but can cut sentences mid-way. Great for prototyping when you need a baseline fast. Would recommend not using in production.
2️⃣ 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Uses prioritized separators (paragraphs → sentences → words) and adapts to document structure.
3️⃣ 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁-𝗕𝗮𝘀𝗲𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Leverages format-specific elements like Markdown headers or HTML tags. Great when you have structured documents with clear logical separations. This is usually my default because it respects natural text organization while not being too complex.
𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀:
4️⃣ 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Breaks text at meaning boundaries by analyzing sentence embeddings to detect topic changes. Ideal for dense academic papers where semantic boundaries don't align with document structure.
5️⃣ 𝗟𝗟𝗠-𝗕𝗮𝘀𝗲𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Uses an LLM to identify propositions and create semantically coherent chunks. Most powerful but also most expensive - a good choice for high-value documents where retrieval quality is absolutely essential.
6️⃣ 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: An AI agent dynamically decides which chunking strategy to use based on document characteristics. The right approach when you need custom strategies tailored to each document.
7️⃣ 𝗟𝗮𝘁𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴: Embeds the entire document first, then derives chunk embeddings while preserving full document context. Is a popular technique for technical documents where chunks reference other parts of the document.
𝗧𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 is that your chunks need to be small enough for precise vector search while giving the LLM enough context to generate useful answers, while also not being tooo much context that you overload the content window.
𝗤𝘂𝗶𝗰𝗸 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸:
• Prototyping → Fixed-size
• Structured docs → Document-based
• Dense academic content → Semantic
• High-stakes systems → LLM-based or Agentic
I would always recommend starting simple and evolving.
Learn more in this blog: https://lnkd.in/eYY8c-hN | 17 comments on LinkedIn
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Walmart CEO says he can't think of a single job that won't be changed by AI—here’s how today’s workforce can prepare | Fortune
“How can I lean into the role that I have—whatever that role is—to adopt new tools, leverage them, and make things better than they would’ve otherwise been?” he told the publication.
Walmart CEO: ‘AI is literally going to change every job’—how the best employees can still stand out
Walmart CEO Doug McMillon is the latest notable business leader to talk about how implementing AI tools and agents in the workplace will affect his company.
Workers in every type of role must be prepared to adapt to the rise of artificial intelligence in the workplace, says Walmart CEO Doug McMillon, leader of the nation’s largest private employer.“It’s very clear that AI is going to change literally every job,” McMillon told The Wall Street Journal in an interview that published on Friday, adding: “Maybe there’s a job in the world that AI won’t change, but I haven’t thought of it.”
🚨 Too many “agent” tools, not enough clarity.
I coach SMB teams every week, here’s the cheat sheet I use to pick the right one fast:
✅ Operators, non-technical → Make.com, Flowise
✅ Low-code and self-host → n8n
✅ Build LLM apps + RAG → LangChain + LangGraph, LlamaIndex
✅ Multi-agent teamwork → AutoGen, CrewAI
✅ Quick ship inside ChatGPT → OpenAI Agentic Stack
✅ Enterprise SDK path → Semantic Kernel
Save this, share it with your ops lead, and test one small workflow this week.
P.S. Which one are you piloting this quarter?
Follow Brianna Bentler for practical AI, real SMB wins, and before/after metrics you can copy.
Thanks to legendary Greg Coquillo for the amazing graphic! | 119 comments on LinkedIn
The AI Application Spending Report: Where Startup Dollars Really Go | Andreessen Horowitz
We then identified the top 50 AI-native application layer companies – similar to our Top 100 Gen AI Consumer Apps, but built around spend data versus web traffic data.
Unlike infrastructure providers, which reflect the capabilities startups are enabling (compute, models, developer tools), these companies show where AI is actually being applied in products and workflows and that distinction matters: this ranking gives us a real-time signal of what early stage startups are “buying” in AI.
AI Incidents Are Up 30%. It's Time to Build a Playbook for When AI Fails.
AI incidents and hazards surged by 30% in the last six months, according to OECD data. These failures are already causing real harm: chatbots allegedly helping craft explosives, Microsoft disrupting $4 billion in AI-enabled fraud, and health insurance systems allegedly incorrectly denying coverage for critical care.
Microsoft To Provide Free AI Tools For Washington State Schools - Slashdot
theodp writes: GeekWire reports that Microsoft is bringing artificial intelligence to every public classroom in its home state -- and sparking new questions about its role in education. The Redmond tech giant on Thursday unveiled Microsoft Elevate Washington, a sweeping new initiative that will pro...
AI Isn't a Curse. It's a Gift for College Learning.
The Chronicle of Higher Education recently ran a piece that offers a beautiful and evocative snapshot of intellectual life at its best. Its authors, Khafiz Kerimov and Nicholas Bellinson of St. John&r
Microsoft adds Copilot adoption benchmarks to Viva Insights
According to Microsoft, an "active Copilot user" is one who "performed an intentional action for an AI-powered capability in Copilot within Microsoft Teams, Microsoft 365 Copilot Chat (work), Outlook, Word, Excel, PowerPoint, OneNote, or Loop."
It makes sense to track Copilot use – those licenses aren't cheap – but benchmarking adoption may be seen by some as a step too far for something still struggling to prove its worth, especially with the risk of turning it into a leaderboard game.
AI Push Drives Record Job Cuts at Top India Private Employer TCS - Slashdot
Tata Consultancy Services made its steepest-ever job cuts as strained ties with the US and a rapid shift toward AI reshape the country's $280 billion IT services sector. From a report: India's biggest private-sector employer cut 19,755 employees in the quarter ended Sept. 30, according to the compa...
Commentary on AI tutors coming to California Community Colleges by Stephen Downes. Online learning, e-learning, new media, connectivism, MOOCs, personal learning environments, new literacy, and more
Anthropic Academy: Claude AI Solutions for Business \ Anthropic
Get started with Claude in your professional workflow. Find practical guides, use cases, and implementation tips for integrating AI assistance across your business tasks.
Hand in Hand: Schools’ Embrace of AI Connected to Increased Risks to Students
Artificial intelligence (AI) has continued to alter the educational experiences of teachers, students, and parents during the 2024-25 school year. The frequency and variety of AI uses continues to grow; at the same time, the increased use of AI in educational settings is correlated with heightened risks to students. This report details the current status […]
Octave 2: next-generation multilingual voice AI • Hume AI
Today we’re launching Octave 2, the second generation of our frontier voice AI model for text-to-speech. We just made a preview of Octave 2 available on our platform and through our API.
Meet Sana.
Think of it as your team's new hire that can break down entire projects, handle multi-step workflows, and take action across all your applications to deliver finished work.
With Sana’s AI platform, your powerful agents can:
Search Drive, Slack, and Confluence simultaneously for that pricing doc
Pull context from your CRM, emails, and meeting notes for client call prep
Build board decks from your live data with charts and citations included
Gather updates, write summaries, handle next steps, and keep tools in sync
Don't just use AI for search and chat. Build agents that think, act, and deliver like your best people.