Addy Osmani is an Irish Software Engineer and leader currently working as a director at Google Cloud AI, focused on helping developers and businesses succeed with Gemini, Vertex AI, and the Agent Development Kit (ADK). After nearly 14 years leading developer experiences in Chrome, he now bridges Google DeepMind, engineering, product, and developer relations teams. A developer for 25+ years at Google, he is passionate about AI-assisted engineering and developer tools. Follow for motivation, productivity and engineering.

Addy Osmani

Introducing our biggest Google Maps upgrade yet - powered by Gemini!

Today Google Maps is getting its biggest upgrade in over a decade!

By combining our Gemini models with a deep understanding of the world, Maps now unlocks entirely new possibilities for how you navigate and explore. 

Here's what you need to know:

🗣️ Ask Maps A new way to get answers to your complex, real-world questions with a simple conversation. Try asking things like:

"My phone is dying - where can I charge it without having to wait in a long line for coffee?" 🔋

"Is there a public tennis court with lights on that I can play at tonight?" 🎾

"I'm headed to the Grand Canyon, Horseshoe Bend, and Coral Dunes - any recommended stops along the way?" 🏜️

No more sifting through research and reviews - just tap "Ask Maps" and get your questions answered with a customized map. (Starts rolling out now in the U.S. and India on Android and iOS, with desktop coming soon).

🚗 Immersive Navigation (that first demo!)

The Maps driving experience is also evolving with clearer visuals and intuitive guidance. You’ll be able to see the buildings, overpasses, and terrain around you in a vivid 3D view, made possible with help from Gemini models.

You’ll also be able to:

1. See more of your route to prepare for what’s next.
2. Understand trade-offs for alternate routes to pick what works best for you.
3. Arrive easily with helpful details like parking and entrance information.

Really excited about these updates! Go Gemini!

#ai #programming #softwareengineering

Director, Google Cloud AI. Best-selling Author. Speaker. AI, DX, UX. I want to see you win.

You can instantly 10x your AI-generated frontends just by learning what different UI components are called.

The Component Gallery (https://component.gallery) is a comprehensive visual reference for standard UI patterns and their proper names ⚡ 

When delegating tasks to coding agents, the quality of your output is bottlenecked by the specificity of your input. If the only vocabulary you use in your prompts are generic words like "menu" or "button," the model will naturally return generic results.

To get high-fidelity interfaces, you need the right shared language for spec-driven development. Knowing when to ask for a "combobox" instead of a "dropdown" or a "segmented control" instead of a "toggle" gives the AI the exact context it needs to execute your vision. The Component Gallery walks through this really well.

UI Design Brain is also an open-source taxonomy for UI skills and component design. (https://lnkd.in/gYYbhv5q) based on the Component Gallery.

Mastering this terminology is a small investment that massively upgrades your prompt engineering.

#ai #programming #softwareengineering

"WebMCP - MCP Is Coming to the Browser"

The Model Context Protocol just got a proposal to bring it natively to the web.
WebMCP is a new JavaScript API that lets web apps expose their functionality as "tools" that AI agents can invoke directly in the browser. Think of web pages as MCP servers - but running entirely client-side, using your existing frontend code. Available as a Google Chrome Early Preview.

Why this matters:

→ Web developers can declare what their app does in a machine-readable way using APIs they already know 
→ Browser agents can discover and call these tools - no backend MCP server required 
→ Two approaches: 1) a declarative API for standard actions via HTML forms  and 2) an imperative API for complex dynamic interactions via JavaScript 
→ Users and agents share the same UI context, enabling cooperative workflows where you delegate the tedious parts and stay in control of the decisions

The use cases click immediately: an agent that can actually search flights, configure options, and handle bookings through structured data. Customer support tickets that get auto-filled with the right technical details. E-commerce flows where an agent navigates checkout with precision instead of fumbling through DOM elements.

Pietro Schirano built a great demo showing this in action - a DoorDash-style app where the agent adds items to cart and checks out with the right address and promo code, without ever needing to "see" the UI. That's the shift really - agents shouldn't have to screenshot or dump HTML to use your app. Just expose your tools.

This is also potentially huge for accessibility - assistive tech that can understand app capabilities semantically, offering users higher-level actions instead of navigating individual UI elements.

We went from "MCP for desktop tools" to "MCP for the entire web" in months. The pace of this protocol's adoption is remarkable.

If you're building web apps, this is worth watching closely.

🔗 WebMCP Proposal: https://lnkd.in/gxbhzPQ9 
🔗 Chrome Early Preview: https://lnkd.in/gySqDEKS
🔗 Syntax.fm deep dive: https://lnkd.in/gbDfWuFn
🔗 Pietro's WebMCP starter: https://lnkd.in/gMWCksvZ

#ai #programming #softwareengineering

An engineer at Anthropic wrote a spec, pointed Claude at an Asana board, and went home. Claude did the rest.

Claude broke the spec into tickets, spawned agents for each one, and they started building independently. When an agent got confused, it ran git-blame and messaged the right engineer in Slack.

By Monday, the agents had finished the feature.

This is the part that fascinates me most: the agent's learning loop mirrors how a new team members onboards. It reads the codebase, identifies who knows what, and asks the right humans. Slack and email - that's all it needed.

We're approaching a world where developers orchestrate dozens of AI agents in parallel. And when that happens, the differentiator between a good engineer and a great one comes down to one thing:

The quality of your specs.

You can't write a spec that holds up at that scale without genuinely understanding what you're building at a deeper level. Architecture, edge cases, failure modes, integration points. The spec IS the product thinking.

Having agents run over the weekend to ship work will start to become entirely normal. There's zero reason you wouldn't add two extra days of output with a couple of prompts and a machine running in the background.

That said - I'm always a little skeptical of how viable these patterns broadly are but do think this is the direction we're heading in. Verification remains the biggest unsolved challenge. Tests that pass on the pre-patch codebase, UI verification, pathological coding practices leaking into the context window. We need slightly better models and much better evaluation infrastructure for this to become the default. I believe we will get there.

But the trajectory is clear: the next-gen developer who understands fundamentals, can architect well, and knows how to orchestrate agents is going to be a force-multiplier.

#ai #programming #softwareengineering

Anthropic has launched free courses to master AI with certificates for $0! 

You can find the full catalog here: https://lnkd.in/gxXNxesb

Yes, they're worth it - especially if you're a web developer. These free Anthropic Academy courses are short (mostly 1-2 hours each), entirely self-paced with videos and quizzes, and provide official certificates of completion when you're done. There's even Claude on Vertex guidance on there.

For developers, the technical tracks are highly practical. They teach you how to move past basic prompting and start building real AI integrations into your daily workflow:

🔹 Claude Code in Action: Learn how to integrate Claude Code directly into your development workflow, master CLI tools, and handle complex context management.
🔹 Building with the Claude API: A comprehensive, hands-on look at working programmatically with Anthropic models.
🔹 Introduction to Model Context Protocol (MCP): Master MCP’s core primitives (tools, resources, and prompts) to connect Claude with external services using Python.
🔹 Claude 101 & AI Fluency: Strong foundations for collaborating with AI systems efficiently and safely.

Understanding context management, agent skills, and API workflows is quickly becoming a critical engineering baseline. These courses give you a phenomenal foundation for AI-assisted development. Plus, the certificates come directly from a top-tier lab, offering a solid signal of real, applied skills to add to your LinkedIn profile or resume.

Enroll and knock out a couple today. 

For those building in the Google ecosystem, make sure to check out the "Claude with Google Cloud's Vertex AI" It's an excellent, comprehensive guide to working with Anthropic models at enterprise scale!

#ai #programming #softwareengineering

Chrome just became massively more agent-friendly 🔥 Your real, signed-in browser can now be natively accessible to any coding agent (with a toggle)

One toggle in chrome://inspect/#remote-debugging and your real, signed-in browser is now natively accessible to any coding agent. Just use this with Chrome DevTools MCP auto connect. OpenClaw just added support too.

No extensions.
No headless browser.
No screenshots.
No separate logins.

Check this out: https://lnkd.in/gNcDHFnV

Your agent finally sees your web the exact tabs, cookies, dashboards, Linear boards, Notion pages, and internal tools you already have open.

This is the moment the biggest friction in browser agents disappeared. 

Google shipped native DevTools MCP live-session attach (Chrome 146+), and tools like OpenClaw and Browser Use instantly plugged in.

https://lnkd.in/gwnKE6fd

Tested it instantly: told my OpenClaw to check my live Google Analytics traffic dashboard. It opened the tab I already had logged in, read the real numbers, and dropped them straight into a weekly report. Zero extra steps. Note: I give my agents their own accounts (e.g. Google account, specific permissions on their accounts for other sites) as this gives me better security isolation.

The same toggle works for Claude Code, gemini-cli, and any MCP-native agent. 

This closes the "my agent can browse the web… but not my web" gap.

#ai #programming #softwareengineering

Introducing the Google Workspace CLI: https://lnkd.in/gpRfeFvR - built for humans and agents.

Google Drive, Gmail, Calendar, Sheets, Chat and every Workspace API. 

The repo ships many Agent Skills - one for every supported API, plus higher-level helpers for common workflows and 50 curated recipes for Gmail, Drive, Docs, Calendar, and Sheets. 

Great work here by Justin Poehnelt 🙏  

#ai #programming #softwareengineering

Boris created Claude Code. His point here is important -  when AI handles the code generation, the engineer's value shifts to the decisions above the code: 

1. what do we build?
2. why? for whom? 
3. and how it all fits together. 

The bottleneck was always judgment, taste, and systems thinking. AI just made that more obvious. I continue to believe that as engineering and product roles evolve (and even converge) through this time, taste is so important.

For me, the line is roughly:

Agents handle
• code co-authoring
• low-risk code reviews
• tactical planning inside a clearly defined feature

I stay very involved in
• technical / UX design
• feature briefs, high-risk reviews
• app-level intent and constraints

The leverage feels highest when humans stay crisp on "what problem, what constraints, what good looks like" and let agents explore the solution space aggressively underneath that.

#ai #programming #softwareengineering

"I was a 10x engineer. Now I'm useless." here's my take:

AI will encourage software engineers to be more deliberate about what thinking we protect, what code we read and what bottlenecks only we can still unblock.

This may be work with high-dimensional search spaces, where the bottleneck isn't code at all but judgment, taste, domain knowledge, or where hard questions that have to be answered before the code even matters. 

On code, I don't think the choice is between reading all the code and reading none of it. I still read lots of code - just not all of it. The question is developing judgment about which parts actually need your eyes on them. Even if I have multiple agents working together to write code, I always account for some review time and some quality inspection.

A lot of developers have spent years building a professional identity around their ability to figure things out. Mo's video is about what happens when you quietly let something else do the figuring out, and then look up one day and realize the skill isn't there anymore.

Video credit is Mo Bitar (https://lnkd.in/gPdByU9x) who I've enjoyed listening to lately and is worth a follow.

#ai #programming #softwareengineering

Tip: Stop using /init for AGENTS.md to get better performance

My latest deep-dive: https://lnkd.in/gkmZ3HJs ✍ 

As we transition deeper into AI-assisted engineering and background agent orchestration, there's a common ritual: setting up a new project, running an auto-generation tool, and committing a comprehensive AGENTS.md context file. It feels like the responsible thing to do.

But recent 2026 research from ETH Zurich and others reveals a different reality: auto-generated context files can actually reduce task success by 2-3% while inflating costs by over 20%.

Why? Because coding agents can already discover your directory structure, tech stack, and module explanations on their own. Handing them an auto-generated summary just adds noise, burns tokens, and dilutes their attention from the actual task.

So, what actually earns a line in your AGENTS.md?

1. The undiscoverable: Tooling gotchas that change operations
2. Operational landmines: "The legacy/ directory is deprecated but imported by production - do not delete."
3. Non-obvious conventions: Custom middleware patterns that shouldn't be refactored to standard conventions.

If an agent can discover it by reading your code, delete it from the file.

A better mental model: Treat your AGENTS.md as a living list of codebase smells you haven't fixed yet. If an agent keeps reaching for the wrong dependency or putting utilities in the wrong folder, don't just add a prose instruction to the context file. Restructure the code, add a linter rule, or improve the test coverage. Treat it as a diagnostic tool, fix the underlying friction, and then delete the line.

I dive into the data, the "pink elephant" problem of context anchoring, and why monolithic context files need to evolve into dynamic routing layers in my latest post. 

How is your team currently managing context for your background coding agents? Are you relying on static files, or exploring more dynamic context loading? Let me know in the comments.

#ai #programming #softwareengineering

Announcing Gemini 3.1 Pro! Google's smarter model for your most complex tasks just shipped!

Last week, we released a major update to Gemini 3 Deep Think to solve modern challenges across science, research, and engineering. Today, we are releasing the upgraded core intelligence that makes those breakthroughs possible: Gemini 3.1 Pro.

Gemini 3.1 Pro is now available for developers, users and enterprise. I'm sharing some fresh demos showing off just a little of what it can do :)

Building on the Gemini 3 series, 3.1 Pro represents a massive step forward in core reasoning. It is designed for tasks where a simple answer is not enough. The model delivers a 77.1% score on the ARC-AGI-2 benchmark, which effectively doubles the reasoning performance of Gemini 3 Pro.

This is a noticeably smarter, more capable baseline for complex problem-solving. Gemini 3.1 Pro excels at workflows where the model must decide for itself how to build the right solution. 

Whether it is modeling complex systems, orchestrating multi-step logic streams, or acting as a more powerful foundation for creative coding, this model makes tough tasks feel simpler.

We are shipping 3.1 Pro at scale starting today:

For developers: Available in preview via the Gemini API in Google AI Studio, Gemini CLI, Android Studio, and our agentic development platform, Google Antigravity. Note that these are in progress of rolling out.

For consumers: Available via the Gemini app and on NotebookLM for Pro and Ultra subscribers.

For enterprises: Available in Vertex AI and Gemini Enterprise.

While we have made a lot of progress, we are already looking ahead to further improving how our models work in broader, more ambitious agentic workflows. We will continue to refine performance around accurate tool selection, complex instruction following, and extended coding tasks.

Whether you are a developer, a student, or just brainstorming a big idea, we can't wait to see what you build and discover with this new level of intelligence.

#ai #programming #lifeatgoogle

We used Gemini 3.1 Pro to build a realistic city planner app, and the multimodal reasoning on display is incredible!

Some great work from Google DeepMind, Michael Chang and team using our new 3.1 Pro release. I wanted to share a little more about how this works.

You can watch how the model tackles complex terrain, maps out infrastructure, and simulates traffic to generate a high-quality visualization. It's a fantastic look at how we can use AI to reason through large-scale, real-world spatial constraints.

Here is a breakdown of what the model is handling under the hood:

🗺️ Terrain analysis: Gemini writes individual programs to generate topography and discover shorelines. It analyzes the flat areas and water placement to build a foundational map in the app's dashboard. 

🌉 Infrastructure mapping: The model seeds the map with urban hubs based on resource locations, layering in basic wireframes before algorithmic generation takes over. 

🚗 Traffic simulation: To build the roads, the app simulates thousands of trips between these hubs. By analyzing how people would theoretically travel, it generates the optimal road networks around the natural terrain. 

✨ High-quality visualization: The finale generates a polished, photorealistic satellite view of this fictional city. From there, clicking anywhere on the map prompts Gemini to imagine and generate detailed "aerial photography" perspectives of specific neighborhoods.

As noted in the demo, Gemini 3.1 Pro has taken a massive leap forward in caring about user intent - seamlessly combining text prompts, spatial math, and image synthesis. We'll also see if we can open-source some of the prompts involved :)

Gemini 3.1 Pro is now available and rolling out to your favorite developer tools.

#ai #programming #softwareengineering

Announcing the new Google Gemini powered Docs, Sheets, Slides, and Drive! More context, fulled editable AI slides, and new grounding sources!

Available today to G1 Pro and Ultra users!

🚀 Google is fundamentally reimagining how we work across Google Docs, Sheets, Slides, and Drive. 

I'm incredibly excited to see Google Workspace become more contextual, helpful, and collaborative. We've all stared down a blinking cursor or an empty spreadsheet - getting started is often the hardest part. Now, you can simply choose your sources, and Gemini will securely connect the dots and uncover useful insights for you.

Here is a look at the new way of working:

📝 Docs is your new writing partner
Get a customized first draft instantly by asking Gemini to draw from your existing files. You can effortlessly refine sections, strengthen your message, and seamlessly match your unique voice or a specific document format.

📊 Sheets build complex sheets 9x faster

Describe what you need, and Gemini will set up the entire spreadsheet, pulling details directly from your inbox and files. You can even populate missing data instantly by accessing real-time web results - saving hours of manual research. (Plus, Gemini in Sheets is now #1 on the SheetsBench leaderboard!)

🎨 Slides let you go from concept to Presentation-Ready faster

Go from a rough concept to a polished deck with a simple prompt. Gemini acts as your design collaborator to generate beautiful, fully editable slides that align with your theme and pull context from your existing work. (Generating entire decks from a single prompt is coming soon!)

📂 Drive is your active collaborator

When you search in everyday language, Drive now generates a summarized AI Overview right at the top of your results. You can also use "Ask Gemini" to have a multi-turn conversation with your files and folders - all without opening a single document.

These features are rolling out today in beta for Google Workspace Gemini Alpha customers, as well as Google One AI Ultra and AI Pro subscribers.

#googleworkspace #programming #ai

𝐀𝐰𝐚𝐫𝐝-𝐖𝐢𝐧𝐧𝐢𝐧𝐠 𝐃𝐞𝐬𝐢𝐠𝐧 𝐓𝐡𝐨𝐮𝐠𝐡𝐭 𝐋𝐞𝐚𝐝𝐞𝐫 | 𝐇𝐞𝐚𝐝 - 𝐃𝐞𝐬𝐢𝐠𝐧 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠

Vidhya is the 𝐜𝐨-𝐟𝐨𝐮𝐧𝐝𝐞𝐫 𝐨𝐟 𝐂𝐨𝐝𝐞𝐰𝐚𝐯𝐞.𝐜𝐨𝐦, a Design Thinking Led Digital Innovation company headquartered in Bangalore, India. She was named one of the '𝐏𝐨𝐰𝐞𝐫 100 𝐖𝐨𝐦𝐞𝐧 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐨𝐫𝐬 𝐢𝐧 𝐈𝐧𝐝𝐢𝐚' by the Confederation of Indian Industry (CII) and PwC, and is a 𝐅𝐮𝐭𝐮𝐫𝐞50 𝐇𝐨𝐧𝐨𝐮𝐫𝐞𝐞 by the Project Management Institute (PMI). Vidhya is also an educator and 𝐔𝐗 𝐟𝐚𝐜𝐮𝐥𝐭𝐲 at top-tier B-schools in India.

With over 𝐭𝐰𝐨 𝐝𝐞𝐜𝐚𝐝𝐞𝐬 of experience in the IT industry, she has served in various roles—from programmer to analyst, product manager, designer, and entrepreneur. In the last 12 years of her entrepreneurial journey, she has worked with 𝐥𝐞𝐚𝐝𝐢𝐧𝐠 𝐕𝐂 𝐟𝐢𝐫𝐦𝐬 to enable their portfolio companies to go from startup to scaleup. She has solved 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐆𝐨𝐯𝐞𝐫𝐧𝐦𝐞𝐧𝐭 of Karnataka during COVID and 𝐞𝐦𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐨𝐯𝐞𝐫 1000 𝐬𝐭𝐮𝐝𝐞𝐧𝐭𝐬 with design thinking skills.

Championing the idea that "𝐄𝐯𝐞𝐫𝐲𝐨𝐧𝐞 𝐢𝐬 𝐚 𝐜𝐫𝐞𝐚𝐭𝐨𝐫," in her leadership, Codewave became the 𝐨𝐧𝐥𝐲 𝐈𝐓 𝐜𝐨𝐦𝐩𝐚𝐧𝐲 𝐟𝐫𝐨𝐦 𝐈𝐧𝐝𝐢𝐚 in 2024 to win the global ZeroDX Award for its 𝐜𝐮𝐥𝐭𝐮𝐫𝐞 of "Employee as Entrepreneur" and its ethos of 'Zero distance' between customers and employees.

Over the past decade, she has partnered with over 100 businesses globally across 10+ industries to craft digital experiences that are both engaging and delightful—while 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜𝐚𝐥𝐥𝐲 𝐝𝐫𝐢𝐯𝐢𝐧𝐠 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐢𝐦𝐩𝐚𝐜𝐭.

She works with organizations at every stage—whether emerging startups, scaling enterprises, or seasoned market leaders—to navigate complexity, embrace diverse perspectives, and 𝐮𝐧𝐥𝐨𝐜𝐤 10𝐱 𝐠𝐫𝐨𝐰𝐭𝐡.

Vidhya Abhijith

With all the #AI rush, everyone's searching for what's their 𝐩𝐮𝐫𝐩𝐨𝐬𝐞.

Yesterday, I spoke about finding my #Ikigai at a #WomensDay event. 
Most people still treat it like a diagram to solve. 
Here's what I've actually lived.

1) 𝐘𝐨𝐮 𝐝𝐨𝐧'𝐭 𝐟𝐢𝐧𝐝 𝐢𝐭 𝐛𝐲 𝐟𝐢𝐥𝐥𝐢𝐧𝐠 𝐮𝐩 𝐚 𝐕𝐞𝐧𝐧: 
It's that thing you do where: 
– You forget to check your phone. 
– Time dissolves. 
– You feel a small sense of joy, even when nobody's praising.

You keep coming back to do it because that state of flow feels like 𝘤𝘰𝘮𝘪𝘯𝘨 𝘩𝘰𝘮𝘦.

2) 𝐈𝐭 𝐬𝐭𝐚𝐫𝐭𝐬 𝐚𝐬 𝐚 𝐬𝐞𝐞𝐝. 
Small. Private. Almost invisible. 
The more you honour it, the more it grows. 
One day it stops being 'something you enjoy' and becomes a tree that serves others.

3) 𝐈𝐭 𝐚𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞𝐬 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐩𝐞𝐨𝐩𝐥𝐞. 
Building Codewave with Abhijith taught me this. The right partner. The right team. What once felt like 'passion' becomes shared purpose and suddenly the venn makes sense.

That's the thing about #Ikigai. You don't find it by just filling in a framework. 
You find it by paying attention to life and 𝘸𝘩𝘢𝘵 𝘭𝘪𝘨𝘩𝘵𝘴 𝘺𝘰𝘶 𝘶𝘱. 

Joyful. Effortless. Valuable. Rewarding. ❤️

What's that one thing you keep coming back to, even when 𝘯𝘰 𝘰𝘯𝘦'𝘴 𝘢𝘴𝘬𝘪𝘯𝘨 𝘺𝘰𝘶 𝘵𝘰? 

#SelfTransformation #PurposeLed #PersonalDevelopment #LifeJourney #Leadership Codewave.com

Founder @ Codewave | Design - Thought Leader | Scaling - Self Management | CII-PwC Top 100 Women Innovators | PMI Future50

I’ve seen largely two kinds of people in my journey as a #designer.

One says:
“𝘋𝘦𝘴𝘪𝘨𝘯 𝘪𝘴𝘯’𝘵 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘪𝘤. 𝘐𝘵’𝘴 𝘫𝘶𝘴𝘵 𝘢𝘦𝘴𝘵𝘩𝘦𝘵𝘪𝘤.”

The other believes:
“𝘋𝘦𝘴𝘪𝘨𝘯 𝘪𝘴 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘮𝘢𝘥𝘦 𝘥𝘦𝘭𝘪𝘨𝘩𝘵𝘧𝘶𝘭.”

I used to wonder: 
𝘞𝘩𝘺 𝘥𝘰 𝘸𝘦 𝘢𝘴𝘴𝘶𝘮𝘦 𝘥𝘦𝘴𝘪𝘨𝘯 𝘥𝘰𝘦𝘴𝘯'𝘵 𝘮𝘦𝘢𝘯 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴?
𝘞𝘩𝘺 𝘤𝘢𝘯'𝘵 𝘺𝘰𝘶 𝘣𝘦 𝘯𝘪𝘤𝘦 𝘢𝘯𝘥 𝘴𝘵𝘪𝘭𝘭 𝘸𝘪𝘯? 
𝘞𝘩𝘺 𝘤𝘢𝘯’𝘵 𝘺𝘰𝘶 𝘭𝘦𝘵 𝘱𝘦𝘰𝘱𝘭𝘦 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦 𝘺𝘰𝘶𝘳 𝘷𝘢𝘭𝘶𝘦 𝘵𝘩𝘦𝘪𝘳 𝘸𝘢𝘺?

Today, 
#AI has collapsed the walls between #Design, #Strategy & #Technology. 

The era of treating them as separate departments or roles is over. 

With #AI, 𝐄𝐯𝐞𝐫𝐲𝐨𝐧𝐞 𝐢𝐬 𝐚𝐧 #Innovator, 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐧𝐠 𝐢𝐧𝐭𝐞𝐧𝐭, 𝐭𝐚𝐬𝐭𝐞 & 𝐯𝐚𝐥𝐮𝐞 to build uniquely delightful experiences that win. 💥 

#CXO #Leadership #AITransformation #ProductLeadership #CustomerExperience #DesignStrategy #Innovation #FutureOfWork #OutcomesFirst Codewave.com Abhijith HK Shilpa R Kowshik GURJINDER SINGH Karthik Ramesh Bhoomika BM Nitin Naik

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taplio

The Battle

Addy Osmani

Vidhya Abhijith

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Addy Osmani's LinkedIn Performance

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Performance ScoreAddy Osmani's LinkedIn Performance