I build AI products from zero to one, and I teach others how to do the same.Over 12+ years, I've taken AI/ML products from proof-of-concept to launch at Amazon, Nike, T-Mobile, and Disney. The work I love most is early-stage: validating ideas, getting executive greenlight, and shipping MVPs that prove value before scaling. At Nike, that approach drove a $100M annual reduction in product returns.I also teach what I build. I co-created and lead the AI Product Management Certificate at the University of Washington, where experienced PMs ship real GenAI products complete with evaluation plans and GTM strategies. Previously, I trained 4 cohorts at Product School.What I bring: the ability to translate messy AI capabilities into clear product value, align technical and business stakeholders, and move fast without breaking trust. I write about AI PM craft at aipmguru.substack.com.I'm currently exploring opportunities to lead 0→1 AI product work at companies solving meaningful problems. I'm especially energized by AI in healthcare and education, though I'm open to any domain where the product can genuinely improve lives. 

Shaili Guru

Hemant Bothra and I are running an in-person workshop where we're going to build something together - in the same room, like the old days.

3 hours. You'll leave with a working tool.

No coding experience needed (you read that right). We'll use Cursor (an AI coding assistant) and walk through everything step by step. If you've ever been curious about "vibe coding" but didn't know where to start, this is it.

Good fit if you're a PM who wants to actually build things, or just someone who learns better by doing than watching.

AI/ML Product Leader | Driving Innovation with AI | PM Mentor and Advisor

Open article: Build Your First AI Tool: ChatGPT Output Cleaner Workshop · Luma by luma.com

Build Your First AI Tool: ChatGPT Output Cleaner Workshop · Luma

AI Product Leader 🔥 | AI PM BY DESIGN ✨ Level Up with AI | Agentic AI @Verizon

👋 Hey, I'm Will. I'm an Agentic AI Product Leader driving $168M+ in value 🔥

My work bridges the gap between cutting-edge AI capabilities and practical customer value: I lead enterprise (0→1) AI transformational products that deliver real business impact and customers ❤️

🚀 AI Product Lead at Verizon for Contact Center Gen AI, serving a globally distributed frontline workforce and 100M+ subscribers.

🏆 Delivered 10% AHT reduction via agentic capabilities for real-time listening, IVR routing, real-time transcription, customer bio summarization, sentiment analysis, retention nudges, case management, conversational intelligence, and personalized sales recommendations.

🦾 Leading the dev of OSS deep-agent-one: a general-purpose deep agent that reduces AI tool costs through intelligent reasoning optimization.

✍️ Creator of AI PM BY DESIGN: Making complex AI concepts accessible for product leaders and data science practitioners.

❝With everything happening in the world, I know how easy it is to put yourself last. But the truth is, your mindset shapes your success.❞

Let's get to work!
——

𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗣𝗿𝗼𝗳𝗶𝗹𝗲

✅Top 6% of LinkedIn Voices
✅12-year track record of launching 0→1s
✅>700 GitHub contributions in <1 year
✅People Leader empowering 100+ missionaries
✅Recovering Data Scientist with 100+ tech certs
✅Recognized SOTA AI Product SME cross-industry
✅Baruch College Master's, born and raised in NYC
✅Consistently ranked Top Performing
✅Black-belt Taekwondo Champion

Product Strategy
Value Prop → Realization
OKRs
Product Vision to ROI Mapping
Business Case Studies
Advanced Critical Thinking
Negotiation
Emotional Intelligence
Roadmap Planning
Evangelization
End-user Adoption
GTM
Stakeholder Relationship Management
Cross-Functional Leadership
Coaching
Design Thinking
User Research
Competitive Analysis
Customer Delight
Customer Journey / Empathy Mapping
UX Improvement
Continuous Discovery
AB Testing
Lean Dev
MVP Scoping
POCs 
SDLC Agile
CI/CD
Cloud Architecture
Personalization
Generative AI
Responsible AI
Content Moderation
OpenAI
Gemini
Claude
Hugging Face
Reasoning
AI Prototyping
Machine Learning
Deep Learning
NLP
LLMs
SLMs
RAG
AI Agents
Agentic Workflows
Multi-agent
Supervisor
Swarm
Deep Agents
Agents SDK
Langchain
LangGraph
MCP
LLMaaJ
OCR
Multimodal
Fine-Tuning
Embeddings
Vibe Coding
PRD→Prototype→Prod
Reinforcement Learning
RLHF
Hallucination Detection
LLMOps
Observability
Vector Dbs
Relational Dbs
Embeddings
RecSys
Data Science
Stats
SQL
Python
Evals
Data Lakehouse

Views expressed are my own and do not represent my employer.

Will Scardino

𝗦𝘁𝗼𝗽 𝘄𝗮𝘀𝘁𝗶𝗻𝗴 𝘁𝗶𝗺𝗲 𝗰𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝗔𝗜 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸! 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵 𝘃𝘀. 𝗖𝗿𝗲𝘄𝗔𝗜 🔥 
𝗪𝗵𝗶𝗰𝗵 𝗼𝗻𝗲 𝘀𝗵𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘂𝘀𝗲?

🔗 https://lnkd.in/e-wS8kNb

Here’s the rundown:

👉 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵 𝗶𝘀 𝗮𝗹𝗹 𝗮𝗯𝗼𝘂𝘁 𝗳𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆. 

It’s perfect if you’re already in the Langchain ecosystem, need context engineering, or want to build both Python and browser-based agents. 

The tradeoff is it can be slower (compared to CrewAI) since it checkpoints state, but that also makes it great for human-in-the-loop systems.

👉 𝗖𝗿𝗲𝘄𝗔𝗜 𝗶𝘀 𝗮𝗯𝗼𝘂𝘁 𝘀𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝘀𝗶𝗺𝗽𝗹𝗶𝗰𝗶𝘁𝘆. 

Pure Python agents that are blazing-fast.  

So it's ideal if you just want to spin up multi-agent systems without Langchain dependencies. 

Think of it as plug-and-play AI teams—role-based, autonomous, and efficient.

So the choice comes down to this 👇

If you want flexibility, choose LangGraph.
If you want speed & simplicity, choose CrewAI.

🚀 If you’re serious about enterprise AI agents and becoming an Agentic AI PM, subscribe on Substack (𝗩𝗶𝗲𝘄 𝗡𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿) — 
I’ll show you exactly how to build AI agents with LangGraph in my next blog post.


Thanks for reading ✨𝐀𝐈 𝐏𝐌 𝐁𝐘 𝐃𝐄𝐒𝐈𝐆𝐍.

🔔 Hit the notification bell in my profile so you don't miss an update.
♻️ Repost to help someone level up with AI.

#DoMore
 
Let’s get to work!

AI Product Leader 🔥 Driving $168M+ for ​100M users | Agentic AI @Verizon | Top 6% Voice | Ex-Grubhub, Acxiom, Humana, FEMA

Open video: 🚀 Want to Build AI Agents in 2025? Start Here #ai #chatgpt #artificialintelligence #claude #aiagents on youtube.com

🚀 Want to Build AI Agents in 2025? Start Here #ai #chatgpt #artificialintelligence #claude #aiagents

𝗧𝗵𝗲 𝗔𝗚-𝗨𝗜 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 — 𝗠𝗮𝗸𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝘀 𝗨𝘀𝗲𝗳𝘂𝗹 𝗔𝗴𝗮𝗶𝗻 ✅ 

Remember when Devin was supposed to replace software engineers? The fully autonomous coding agent that would take your prompt and build out your entire codebase while you laid on a beach sipping frozen margaritas?

Meanwhile, Cursor quietly ate everyone’s lunch. Not because it was fully autonomous, but because it worked alongside developers. Users could see what the agent was doing, interrupt when it went off the rails, and collaborate in real-time on the same codebase.

The difference? User interaction.

And that difference just became a protocol.

If you’ve been following the AI SaaS space, you probably heard of:

1. MCP (Model Context Protocol): Connects agents to tools and context
2. A2A (Agent-to-Agent): Enables agents to coordinate with each other
3. ACP (Agentic Commerce Protocol): Enables agents to execute transactions and manage commerce

But there’s a glaring gap 🔥 
How do agents connect to users?

Enter AG-UI (Agent-User Interaction Protocol) - the fourth pillar of the AI protocol landscape that bridges the critical gap between powerful BE agents and the FE, where humans actually do our work.

AG-UI is going to change the way we design and build AI agents..


🫶 𝗔𝗚-𝗨𝗜 𝗶𝘀 𝗮𝗻 𝗢𝗦𝗦 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, 𝗖𝗿𝗲𝘄𝗔𝗜 & 𝗖𝗼𝗽𝗶𝗹𝗼𝘁𝗞𝗶𝘁.

💡 Here’s what it actually does:

✅ Real-Time Streaming
LLMs produce tokens incrementally. Your UI needs them instantly without blocking the full response. AG-UI handles this natively with WebSocket events and SSE (Server-Sent Events).

✅ Tool Orchestration Without Diminishing Context
Modern agents call functions, run code, and hit APIs. They need to show progress, pause for approval, and then resume without losing their CoT.

✅ AG-UI defines ~17 standard event types. Here are the critical ones:

    RUN_STARTED / RUN_FINISHED / RUN_ERROR

    TEXT_MESSAGE_START / TEXT_MESSAGE_CONTENT / TEXT_MESSAGE_END

    TOOL_CALL_START / TOOL_CALL_ARGS / TOOL_CALL_END

    STATE_SNAPSHOT - for bidirectional state synchronization

✅ Shared Mutable State
AG-UI provides bidirectional state synchronization through STATE_SNAPSHOT events. The agent and FE can share state, with the agent emitting state updates that the UI can render.

✅ Human-in-the-Loop
Need to pause execution for user approval? Need the agent to ask clarifying questions? AG-UI has interrupts built right in.

UI automatically shows this to the user, gets their response, and feeds it back to the agent.

With AG-UI, you get all the things → that kept you from shipping agent features in the first place → all standardized = faster time to → deployment 🚀

———
👋 Hey, I'm Will, and I'm an 𝗔𝗜 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗟𝗲𝗮𝗱𝗲𝗿 🔥
♻️ Repost to help someone break into ✨𝗔𝗜.

https://lnkd.in/eYnuctRZ

AI Product Leader 🔥 | Agentic AI @Verizon

Easing into the week? Well here's the 🐐 of all Product Demos~ to help you ease in a little Faster 😂

Happy Monday!

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