AI & NLP Enthusiast | Helps Early Founders Define Ideal Customers & Launch Successful GTM initiatives | Advisor | Growth Hacker | Fractional CRO

I build and scale high-performance GTM and enablement functions for technology companies.

As a hands-on leader, my mission is to drive predictable, scalable growth by applying a strategic, operator-first mindset.

Honcho Pickleball: Scaled GTM from 1 → 32 cities, driving 200% revenue growth in 18 months.

Metadata.io: As the first sales hire, created the company's GTM playbook and secured initial enterprise clients.

LivingSocial: Launched Amazon-backed GTM strategies in 10+ cities, training and scaling new sales teams.

I leverage AI automation and RevOps frameworks to build scalable systems that consistently deliver 3x ROI and boost sales efficiency.

If you are looking for a leader who can transform your commercial channel with a proven, results-driven approach, let's talk.

Chris M.

Agent Architect | Senior Software engineer @vivun | Cursor Ambassador

I’m an AI Agent Developer and Cursor Ambassador who has been coding with AI for the past five years, starting from the early days of GitHub Copilot. As one of Cursor’s earliest users, I now run workshops across different domains and speak frequently on AI productivity, helping developers unlock the full potential of AI-powered tools.
My expertise spans the full generative AI pipeline, from fine-tuning models and optimizing prompts to running rigorous evaluations and building scalable agents.
Grounded in a strong background in test architecture, I design AI agents that balance complexity with reliability. I focus on constantly refining and optimizing these systems to push the boundaries of what modern AI software can achieve.

Shrey Shah

10 cool people I met recently and why you should meet them too (AI edition):

The best part of being in AI isn't the tech. It's the people building it.

Here are 10 humans who made me better this year:

1) Ben Lang : Leads communiuty at Cursor. Ben is the reason cursor community grew as big as it is now. I've never met a better community builder. 

2) Sofia Guzowski : Leads community at Tavily. Loved meeting her last year and talking about AI and the future of Tavily!

3) Mike Mikula : One of my best friends and an amazing AI builder. Regularly shares his learnings and insights on AI and building with AI on LinkedIn.

4) Tarak ☁️ : Solving infra for AI. Regularly hosts workshops on infrastructure that actually help you ship.

5) Tori Seidenstein: Building Tadata. Enjoyed our conversation about MCPs and the future of agent architecture!

6) Hemanth HM : Great human and amazing builder. Actually builds agents with bleeding edge tech as soon as it comes out. You never fail to amaze me with your work.

7) Ghadeer Al Ruwaishedi : Building the future of AI in the Middle East. Loved our conversation about the role of AI in the region and where it's heading.

8) Reshma S : One of the best content creators on AI on LinkedIn who actually shares what she builds. Not just talks, builds.

9) Sandipan Bhaumik 🌱: Amazing human and Tech Leader in Data & AI. Every conversation leaves me with something new.

10) Oana F. May : One of the best Product Leaders I've met. Learned more in one session about product thinking than I did in months by reading books/ blogs. Changed how I think about building with AI.

The AI space moves fast. But the people you surround yourself with determine how far you actually go.

If you know any of them, go say hi. If you don't, now you do.

p.s. Thanks Sofia Guzowski for the inspiration to write this post!

This was a lot of fun to do! Going to do many more of these! 

I'm Shrey Shah & I teach AI assisted coding and agents.

If this resonated, hit the ♻️ reshare button so someone else finds their next favorite person in AI

I teach vibe engineering and agents | Senior Software engineer @vivun | Cursor Ambassador | V0 Ambassador

Most people use Claude Code as a basic agent.

They're missing its full potential.

I've been coding with it for over a year, and a lot has changed:

↳ Models have evolved
↳ Context engineering approaches have shifted
↳ New features keep getting added

What helped me get more out of it wasn't one source. It was a mix of official docs, video tutorials, best practices, MCP servers, subagents, SDK examples, and community-curated skills.

I've pulled everything that actually worked into one document.

It includes:

- Getting started guides for beginners
- Deep dives for advanced users
- Tools and extensions to enhance your workflow
- Real-world case studies and experience reports

If you want these resources, link is in the comments

I'm Shrey Shah & I teach AI assisted coding and agents.

If this helped you master Claude Code, click the ♻️ reshare button so someone in your network can too.

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 Shrey Shah led a workshop at JSNation US 2025

Building Knowledge Graphs with LLMs

Cypher Fundamentals

Stable Diffusion: Tips, Tricks, and Techniques

Understanding and Visualizing Data with Python

AI in Connected Products (AIOT)

 AWS Cloud Practitioner - CLF-C01 (LA)

AWS Certified Solutions Architect - Associate SAA-C02

Advanced Testing Practices Using AWS DevOps Tools

Java Design Patterns: Behavioral Part 2

JavaScript: Best Practices for Data

Networking Foundations: Protocols and CLI Tools

Data Science Foundations: Fundamentals

Deep Learning: Getting Started

Learning Kubernetes

Learning Regular Expressions

NLP with Python for Machine Learning Essential Training

Learning GraphQL

Software Testing Foundations: Bug Writing and Management

AWS for DevOps: Monitoring, Metrics, and Logging

Developing CI/CD Solutions with Azure DevOps

GraphQL Essential Training

Leadership: Practical Skills

Learning Splunk

Software Architecture: From Developer to Architect

Software Testing Foundations: Test Planning

Splunk 7.x Fundamentals Part 1

Succeeding in DevOps

Selenium Webdriver with PYTHON from Scratch + Frameworks

Automate the Boring Stuff with Python Programming

Lean Management in 2020: Agile + Kanban 

Spring Boot REST API and Microservices - Spring Cloud

Understanding Docker and using it for Selenium automation

Appium - Selenium for Mobile Automation Testing

Vivun delivers the world’s most advanced AI Sales Agent—automating the critical work required to move complex deals forward. By providing expertise and generating sales-ready outputs that help every rep engage stakeholders, build value, and drive urgency, Vivun empowers sales teams to close more deals, faster.

For more information, visit vivun.com. 

Vivun delivers the world’s most advanced AI Sales Agent—automating the critical work required to move complex deals forward. By providing expertise and generating sales-ready outputs that help every rep engage stakeholders, build value, and drive urgency, Vivun empowers sales teams to close more deals, faster.

Senior AI Software Engineer 

Software engineer | AI

V0 Ambassador

Helping bridge the gap between the community and Cursor team! If you have questions feel free to send me a message!

Cursor Ambassador

● Led development of an end-to-end test automation framework using wdio, Appium, Mocha and Saucelabs for web, mobile and API testing, significantly improving test coverage and reducing regression testing time. This allowed new features to be released faster, resulting in increased customer conversion rate.
● Implemented continuous integration and delivery pipelines using GitHub Actions, enabling teams to release new versions multiple times per day. This drastically improved time-to-market and increased customer satisfaction due to more frequent updates.
● Implemented GitHub actions for automating the entire release process, including PR creation and merging, as well as confluence release documentation, reducing release time.
● Developed backend for one of  core products using Spring Boot, supporting high volume of daily transactions and driving strong revenue growth after launch.
● Created algorithms to auto-generate test cases from historical test-data, reducing manual test creation and maintenance efforts. This allowed the testing team to keep pace with aggressive development timelines, while improving test coverage and quality.
● Integrated test automation framework with Zephyr Scale to provide end-to-end traceability. This improved visibility into overall test coverage and helped identify areas needing more test focus, reducing defects.
● Implemented Splunk dashboards and alerts for real-time application performance monitoring. This enabled pre-emptive identification and resolution of issues, improving uptime and customer satisfaction.
● Provided technical leadership and mentoring on test automation best practices using Mocha, WebDriverIO and JavaScript, improving team productivity and efficiency.
● Played a pivotal role in the recruitment process for SDETs conducting interviews to match job requirements.

Senior Software Development Engineer In Test / JAVA developer

● Conducted thorough research on potential technical and non-technical solutions, testing frameworks, and emerging tools, enhancing business operations efficiency.
● Utilized the inverse pyramid of automation (Unit, Integration/Mid-Level, and Acceptance Tests) for comprehensive feature test coverage, reducing the number of test cases.
● Developed an innovative test automation framework using Cypress, Mocha, Chai, and JavaScript from scratch, improving test automation efficiency.
● Implemented Eslint and SonarQube tools to consistently maintain code quality, decreasing bugs and errors.
● Managed test data creation with various JavaScript libraries, increasing test data accuracy.
Employed Postman, Mocha, Chai, JavaScript for API testing, and JMeter for UI/API performance testing, 
● Crafted MongoDB queries in Roto3T for database validation against the UI, enhancing data accuracy.
● Scheduled test runs, builds, and CI using Azure jobs and pipelines, streamlining the testing process.
● Leveraged Azure DevOps and Visual Studio Team Foundation for agile ALM, fostering efficient communication and collaboration between development and QA teams.

Automation Engineer

● Led comprehensive testing of applications, including Blockchain, Mobile & Web apps, SQL databases, and IoT devices, ensuring product quality and enhancing user experience.
● Developed a data-driven framework for API, Web, and Mobile app testing, improving testing accuracy and speed.
● Engineered an API testing framework using Python and Pytest for IoT devices, increasing testing efficiency.
● Conducted load testing on APIs using Apache JMeter and Artillery, optimizing application performance and reliability.
● Dockerized SoapUI and integrated it within CI/CD on GitLab, enhancing the testing process's speed and accuracy.
● Performed code quality analysis using Sonarlint and SonarQube, reducing errors in the QA framework.

SDET

● Welcomed students and directed them to the relevant office/personnel.
● Carried out clerical duties such as answering phone calls, responding to emails, and preparing documents, including office correspondence, memos, and presentations.
● Coordinated and managed appointments, meetings, and the conference room schedule in order to prevent duplicate bookings.
● Sorted and distributed mail
● Maintained general office files, including job files, vendor files, and other files related to the Basketball department.
● Purchased office supplies, equipment, and furniture.
● Provided excellent customer service.
● Performed other relevant duties when needed.

Administrative Assistant

●	Developed Selenium test cases using the Hybrid framework (Data Driven Framework with POM and TestNG)
●	Validated the scripts to make sure they have been executed correctly and meets the scenario description.  
●	Reviewed the Business Requirements Document and Test Plan to carry out the testing activities. 
●	Developed Test scenarios, Test Cases & Test data and Performed Positive and Negative testing
●	Worked closely with the automation team to create plans for what features can be automated.
●	Attended Sprint Planning and Demo to review & understand uses cases, non-functional requirements & design documents for Test Case Development

QA Automation Engineer

Intern

I teach AI assisted coding and agents | Senior Software engineer @vivun | Cursor Ambassador | V0 Ambassador

Everyone is a staff engineer now.

(It sounds like a promotion. It isn't.)

This has a name: the expectations trap.

And it isn't the first time the industry has run this playbook.

The pattern shows up every decade, dressed a little differently each time:

1) Full-stack engineering (~2010)
- Frontend + backend roles collapsed into one person
- The pitch: be more versatile, more valuable
- What actually happened: scope doubled, compensation stayed flat

2) DevOps (~2015)
- "You build it, you run it" sounded like ownership
- Developers inherited on-call rotations, CI/CD pipelines, Terraform configs, Kubernetes debugging on top of regular feature work
- Scope expanded again, same result on pay

3) AI engineering (~now)
- You're not just writing code anymore
- You're expected to think architecturally, steer agents, review everything they generate, and make strategic decisions about what to build
- The scope has expanded massively
- You can guess what's happening to the paycheck

Here's the part nobody is addressing.

The engineers who will thrive are the ones with deep context. Everyone agrees on that.

But context isn't built by prompting AI.

It's built by implementing, debugging, shipping, dealing with production incidents, and living with the consequences of bad architectural decisions over years.

If junior engineers skip straight to staff-level thinking by handing implementation to AI, they skip the exact work that builds the judgment that makes staff-level thinking valuable.

The output looks impressive. The understanding isn't there.

And if everybody is a staff engineer, nobody is a staff engineer.

That's title inflation. The same cycle the senior engineer role went through a decade ago, now happening in real time to the staff and architect roles.

AI is being commoditized. Prompting faster than your colleagues is not a moat.

Deep context is.

And there are no shortcuts to building it.

The API era is over.

(the next wave of software companies won't sell endpoints)

For 15 years, the playbook was simple: build a product, expose an API, let developers plug in.

The companies that won owned the pipes.

Stripe owned payments. Twilio owned messaging. Sendgrid owned email.

Once you were integrated, you were embedded. The API was the distribution layer.

That model made sense in a world where execution was scarce.

LLMs compress execution into a prompt. So the center of gravity shifts.

An API is a doorway into a function.

Here's how to send an email. Here's how to process a payment. Here's how to fetch this data.

Precise. Mechanical. Bounded.

A skill is a doorway into judgment.

Here's how to audit a landing page like a serious growth operator. Here's how to structure a legal intake so you catch the real risk. Here's how to clean messy directory data so it actually turns into revenue.

You're not encoding a function. You're encoding a way of thinking.

And that changes how companies are built.

In the API era, distribution meant convincing developers to integrate you.
↳ You needed docs, SDKs, developer evangelism
↳ You fought for a place inside someone else's codebase

In the skill era, distribution means becoming part of someone's agent workflow.
↳ A founder opens their coding agent
↳ They type /seo-audit
↳ Your skill runs, frames the output, structures the analysis, guides the decisions
↳ Your expertise lives inside the execution layer itself

You aren't pulling users into your interface. You're embedding your thinking into theirs.

The old playbook:

1) Build SaaS
2) Design UI
3) Onboard users
4) Drive retention
5) Expand seats

The new playbook:

1) Encode a high-leverage methodology
2) Package it as a skill
3) Let agents call it thousands of times per day

One installation means your methodology gets invoked across hundreds of companies automatically. The scaling curve looks less like seats and more like invocations.

What's happening underneath is simple:

→ Software used to be the executor
→ Now software is the orchestrator
→ Next, expertise becomes infrastructure

In the API era, the winners owned the pipes.

In the skill era, the winners own the patterns.

Patterns for closing deals. Patterns for pricing. Patterns for positioning. Patterns for enrichment. Patterns for research.

Many of these new companies will look surprisingly small on the surface. A tight repo. A handful of powerful skill files. Maybe 2-5 people maintaining and improving them.

This is a new class of companies built less around dashboards and more around encoded judgment.

The skill era of the internet is here.

Welcome.

👉 Over to you: What expertise do you think gets packaged as a skill first?

I'm Shrey Shah & I teach AI assisted coding and agents.

Google just released Gemini 3.1 Pro and it's not a small update.

Here's what actually matters:

☑ 77.1% on ARC-AGI-2 (more than double Gemini 3 Pro)
☑ 99.3% on agentic tool use
☑ 85.9% on agentic search
☑ Built specifically for multi-step reasoning and complex workflows

ARC-AGI-2 is the benchmark that tests whether a model can solve logic patterns it has never seen before.

77.1% is not a small number.

What this looks like in the real world:

☑ Generated website-ready animated SVGs from plain text prompts
☑ Built a live ISS tracking dashboard using a public telemetry API
☑ Coded a 3D starling murmuration with hand-tracking and generative audio

These aren't cherry-picked demos. This is baseline capability now.

For anyone building AI agents, the tool use and search scores are what you care about most. 99.3% and 85.9% means your agents just became significantly more reliable overnight.

Rolling out today on Gemini app, AI Studio, Vertex AI, Gemini CLI, NotebookLM, and Android Studio.

Google cooked really hard this time. Claude Opus 4.6 has some serious competition now.

I'm Shrey Shah and I share daily guides on AI.

If you found this helpful, click the ♻️ reshare button to help someone else stay ahead of the curve.

taplio

The Battle

Chris M.

Shrey Shah

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taplio

The Battle

Chris M.

Shrey Shah

Followers

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Engagements

Likes

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);}Shrey Shah's LinkedIn Performance

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