Hey everyone!

After the success of the World Cup Draft Game, The Chase, I bring to you the IPL version cricket strategy game called Powerplay IPL, where you get to build your own IPL dynasty.

The idea is simple - you enter an auction, build an **18-man squad from IPL players across seasons**, manage your purse under a salary cap, pick your playing XI based on match conditions, and try to win the tournament.

You can play in different modes, including:

• All-Time IPL - draft the greatest IPL players ever and play a 10-team tournament
• Historical Season - replace a team in a random IPL season
• Classic Draft - player ratings are visible
• From Memory - ratings are hidden, so you have to rely on your IPL knowledge

Whats matters

1. Set your batting order - This is YOUR call. The engine respects the exact order you set. No auto-sorting. But the position matters for each player and accordingly gives a boost.
2. Team Combination - The team combination and matchups matter based on opposition and pitch.

There’s also a purse/difficulty system, toss calls, team naming, and season progression. The match engine is based on ball-by-ball data of 20000 T20 games.

If you enjoy IPL auctions, fantasy cricket, cricket manager games, or just arguing over the best IPL XI of all time, you might enjoy this.

Play here: https://powerplay-ipl.vercel.app/

Whats already there

• Global Leaderboard
• Shareable result cards
• Post-match analysis
• Career stats tracking

What's next

Still actively building. Would love suggestions from this community. Coming soon wtih these

• A complete IPL version
• A Test version
• T20 World Cup
• Multiplayer draft mode

Would love to hear feedback, bug reports, balance suggestions, or your best squad builds!

Hey everyone!

After the success of the World Cup Draft Game, The Chase, I bring to you the IPL version cricket strategy game called Powerplay IPL, where you get to build your own IPL dynasty.

The idea is simple - you enter an auction, build an **18-man squad from IPL players across seasons**, manage your purse under a salary cap, pick your playing XI based on match conditions, and try to win the tournament.

You can play in different modes, including:

• All-Time IPL - draft the greatest IPL players ever and play a 10-team tournament
• Historical Season - replace a team in a random IPL season
• Classic Draft - player ratings are visible
• From Memory - ratings are hidden, so you have to rely on your IPL knowledge

Whats matters

1. Set your batting order - This is YOUR call. The engine respects the exact order you set. No auto-sorting. But the position matters for each player and accordingly gives a boost.
2. Team Combination - The team combination and matchups matter based on opposition and pitch.

There’s also a purse/difficulty system, toss calls, team naming, and season progression. The match engine is based on ball-by-ball data of 20000 T20 games.

If you enjoy IPL auctions, fantasy cricket, cricket manager games, or just arguing over the best IPL XI of all time, you might enjoy this.

Play here: https://powerplay-ipl.vercel.app/

Whats already there

• Global Leaderboard
• Shareable result cards
• Post-match analysis
• Career stats tracking

What's next

Still actively building. Would love suggestions from this community. Coming soon wtih these

• A complete IPL version
• A Test version
• T20 World Cup
• Multiplayer draft mode

Would love to hear feedback, bug reports, balance suggestions, or your best squad builds!

Hey everyone!

After the success of the World Cup Draft Game, The Chase, I bring to you the IPL version cricket strategy game called Powerplay IPL, where you get to build your own IPL dynasty.

The idea is simple - you enter an auction, build an **18-man squad from IPL players across seasons**, manage your purse under a salary cap, pick your playing XI based on match conditions, and try to win the tournament.

You can play in different modes, including:

• All-Time IPL - draft the greatest IPL players ever and play a 10-team tournament
• Historical Season - replace a team in a random IPL season
• Classic Draft - player ratings are visible
• From Memory - ratings are hidden, so you have to rely on your IPL knowledge

Whats matters

1. Set your batting order - This is YOUR call. The engine respects the exact order you set. No auto-sorting. But the position matters for each player and accordingly gives a boost.
2. Team Combination - The team combination and matchups matter based on opposition and pitch.

There’s also a purse/difficulty system, toss calls, team naming, and season progression. The match engine is based on ball-by-ball data of 20000 T20 games.

If you enjoy IPL auctions, fantasy cricket, cricket manager games, or just arguing over the best IPL XI of all time, you might enjoy this.

Play here: https://powerplay-ipl.vercel.app/

Whats already there

• Global Leaderboard
• Shareable result cards
• Post-match analysis
• Career stats tracking

What's next

Still actively building. Would love suggestions from this community. Coming soon wtih these

• A complete IPL version
• A Test version
• T20 World Cup
• Multiplayer draft mode

Would love to hear feedback, bug reports, balance suggestions, or your best squad builds!

I wanted to share a browser game I just finished building called 380: The Chase. It is a cricket adaptation of the viral 38-0 grid football game.

How it works:

• You roll random World Cup squads.
• You have to draft one player per roll to fill out your ultimate World XI.
• Your goal is to build a high-rated team capable of successfully winning the world cup

The game is completely free, has no ads, and works right in your mobile or desktop browser. I would love to get your feedback on the mechanics, balancing, or UI.

Play here:https://cricket380.vercel.app/

Updates in the pipeline:

• Login and profile to track your stats
• Global leaderboard
• Multiplayer leagues to play with friends
• IPL and Test versions

I wanted to share a browser game I just finished building called 380: The Chase. It is a cricket adaptation of the viral 38-0 grid football game.

How it works:

• You roll random World Cup squads.
• You have to draft one player per roll to fill out your ultimate World XI.
• Your goal is to build a high-rated team capable of successfully winning the world cup

The game is completely free, has no ads, and works right in your mobile or desktop browser. I would love to get your feedback on the mechanics, balancing, or UI.

Play here: Cricket380

I wanted to share a browser game I just finished building called 380: The Chase. It is a cricket adaptation of the viral 38-0 grid football game.

How it works:

• You roll random World Cup squads.
• You have to draft one player per roll to fill out your ultimate World XI.
• Your goal is to build a high-rated team capable of successfully winning the world cup

The game is completely free, has no ads, and works right in your mobile or desktop browser. I would love to get your feedback on the mechanics, balancing, or UI.

Play here:https://cricket380.vercel.app/

’ve been building a free 7-day hands-on course for people who want to move beyond “chat with AI” and actually build agentic AI systems.

It’s called Agentic AI: 7-Day Build Challenge.

The structure is simple: 7 days, 7 builds, zero fluff. Each day has:

• A mental model
• A working build
• Copy-paste prompts
• Supporting files
• A completion checklist
• One intentional failure lab so people learn how to debug agentic workflows

The builds include:

• Day 1: newsletter automation
• Day 2: Firecrawl MCP scraping workflow
• Day 3: first reusable Claude Code skill
• Day 4: Trigger.dev deployment
• Day 5: frontend build with screenshot feedback loop
• Day 6: scheduled automation and monitoring loop
• Day 7: personal executive assistant folder with context, operating rules, and first skill

The core framework is WAT: Workflows, Agent, Tools. The idea is to teach people how to structure repeatable agentic systems, not just collect prompts.

Everything is free and can be accessed here: Build with Agents

I’m also planning the first free live cohort with daily classes (1 hour) for 7 days starting June 15, 2026. The cohort will be for people who want accountability, live walkthroughs, and feedback while building.

I’d love feedback from builders here:

1. Is the 7-day structure clear?
2. What would make you actually complete all 7 days?
3. What should I add before the first cohort?

If the repo is useful, a GitHub star would help me understand whether this is worth continuing and improving.

I’ve been building a free 7-day hands-on course for people who want to move beyond “chat with AI” and actually build agentic AI systems.

It’s called Agentic AI: 7-Day Build Challenge.

The structure is simple: 7 days, 7 builds, zero fluff. Each day has:

• A mental model
• A working build
• Copy-paste prompts
• Supporting files
• A completion checklist
• One intentional failure lab so people learn how to debug agentic workflows

The builds include:

• Day 1: newsletter automation
• Day 2: Firecrawl MCP scraping workflow
• Day 3: first reusable Claude Code skill
• Day 4: Trigger.dev deployment
• Day 5: frontend build with screenshot feedback loop
• Day 6: scheduled automation and monitoring loop
• Day 7: personal executive assistant folder with context, operating rules, and first skill

The core framework is WAT: Workflows, Agent, Tools. The idea is to teach people how to structure repeatable agentic systems, not just collect prompts.

Everything is free and can be accessed here: Build with Agents

I’m also planning the first free live cohort with daily classes (1 hour) for 7 days starting June 15, 2026. The cohort will be for people who want accountability, live walkthroughs, and feedback while building.

I’d love feedback from builders here:

1. Is the 7-day structure clear?
2. What would make you actually complete all 7 days?
3. What should I add before the first cohort?

If the repo is useful, a GitHub star would help me understand whether this is worth continuing and improving.

I wanted to share two completely free resources I have put together to help product managers transition into AI-native workflows and prep for modern AI product roles.

The first is a comprehensive, open-source tutorial that walks you through using Claude Code as a working PM tool. Instead of just giving you a folder of copy-paste prompts, it teaches you how to build actual agents and automated pipelines that run inside your terminal.

The second is a massive, searchable database of 1,200 real AI PM interview questions asked recently at top-tier tech companies.

Here is a quick breakdown of what you will find in both:

Part 1: The AI-Native PM OS (Course & Workspace)

This is a practical build program containing 63 self-paced lessons (about 40 to 50 hours of total content). Everything is built around a fictional B2B SaaS company called Meridian (with pre-built user research, OKRs, and competitive landscapes) so your outputs feel like actual work products rather than classroom exercises.

• Spec & Sync: Write and stress-test PRDs with Claude, then auto-generate Jira epics via MCP.
• Competitive Intelligence: Build a Competitive Intelligence Agent that sweeps the web and summarizes rival threats.
• Feedback Loop: Cluster customer feedback at scale using a Jobs-to-be-Done framework.
• UX Prototyping: Generate clickable HTML prototypes from rough user flows and deploy them to Vercel instantly.
• Exec Updates: Draft stakeholder-aware OKR updates with tailored tone adjustments.

No paid tools are required beyond a Claude subscription to run the terminal client.

Part 2: The AI PM Question Bank

If you are gearing up for a tough interview loop, I synthesized 1,200 interview prompts from AI Product Manager loops at 73 companies, including Meta, OpenAI, Anthropic, Google DeepMind, Stripe, Perplexity, and Mistral.

• Sourced from public reports and real candidate feedback.
• Categorized into 13 specific PM focus areas so you can filter exactly what you are prepping for.
• Searchable and updated for May 2026 interview patterns.

Links to the Project

• Main Site & Course: https://ai-productmanagers.vercel.app/
• Searchable Question Bank: https://ai-productmanagers.vercel.app/question-bank.html
• GitHub Repository: https://github.com/vishalmdi/ai-native-pm-os

If you find this course or the question bank useful, a star on GitHub helps a lot to keep the project growing. I am happy to answer any questions!

Google recently published official guidance on how to optimize pages for AI-powered search features like AI Overviews and AI Mode - https://developers.google.com/search/docs/fundamentals/ai-optimization-guide

Most of the advice floating around GEO / AI search optimization is still pretty hand-wavy, so I wanted something more concrete.

So, I converted Google’s AI search guidance into an open-source Claude Code skill:

https://github.com/vishalmdi/goog-geo

The skill audits any live URL and turns the guidance into a scored report:

• Checks whether Googlebot can crawl the page
• Checks indexability and snippet eligibility
• Detects noindex, nosnippet, max-snippet, canonicals, robots.txt issues
• Uses a live browser to inspect rendered DOM and JSON-LD schema
• Reviews headings, semantic HTML, answer blocks, FAQs, tables, author/date signals
• Checks whether AI crawlers like GPTBot, PerplexityBot, ClaudeBot, and Bingbot are allowed
• Produces a 100-point GEO / AI search readiness score
• Gives a prioritized action plan instead of vague SEO advice

The main idea is simple - Google’s AI search features are not a totally separate SEO system. They still depend on crawlability, indexability, snippet eligibility, helpful content, and structured/extractable pages.

So instead of guessing what “AI optimization” means, this skill audits against the actual signals Google documented. I also added a “what not to do” section because Google explicitly says some popular AI SEO advice is useless or misunderstood, like treating `llms.txt` as a Google AI ranking lever.

Would love feedback from anyone working on SEO, content, SaaS landing pages, docs, or AI search visibility.

If you find it useful, a GitHub star would help:

Repo Link: https://github.com/vishalmdi/goog-geo

I put together a free, open-source GitHub tutorial that walks you through using Claude Code as a working PM tool - not just for generating text, but for building actual workflows you’d use on the job.

It’s called the AI-Native PM OS. The goal is simple: by the end, you have a set of agents and pipelines that handle the repetitive, time-consuming parts of PM work.

What the tutorial covers:

• Writing and stress-testing PRDs with Claude, then auto-generating Jira epics via MCP
• Building a Competitive Intelligence Agent that runs sweeps and summarizes threats
• Clustering customer feedback at scale using a Jobs-to-be-Done framework
• Generating clickable HTML prototypes from rough product flows and deploying to Vercel
• Drafting executive OKR updates with stakeholder-aware tone adjustments

How it’s structured:

Everything is built around a fictional B2B SaaS company called Meridian, with pre-built personas, OKRs, user research, and a competitive landscape. That gives every exercise real context, so the outputs feel like actual work product, not homework.

• 11 modules, roughly 40–50 hours total
• 30-minute, self-paced lessons
• No paid tools required beyond a Claude subscription

If you’ve been curious about Claude Code but didn’t know where to start as a PM, this is designed for exactly that. Each module builds on the last, so you end up with something functional rather than a collection of one-off prompts.

Repo: https://github.com/vishalmdi/ai-native-pm-os

If you find it useful or think you might come back to it later, a star on GitHub helps a lot — and I’m happy to answer questions in the comments.

I put together a free, open-source GitHub tutorial that walks you through using Claude Code as a working PM tool - not just for generating text, but for building actual workflows you’d use on the job.

It’s called the AI-Native PM OS. The goal is simple: by the end, you have a set of agents and pipelines that handle the repetitive, time-consuming parts of PM work.

What the tutorial covers:

• Writing and stress-testing PRDs with Claude, then auto-generating Jira epics via MCP
• Building a Competitive Intelligence Agent that runs sweeps and summarizes threats
• Clustering customer feedback at scale using a Jobs-to-be-Done framework
• Generating clickable HTML prototypes from rough product flows and deploying to Vercel
• Drafting executive OKR updates with stakeholder-aware tone adjustments

How it’s structured:

Everything is built around a fictional B2B SaaS company called Meridian, with pre-built personas, OKRs, user research, and a competitive landscape. That gives every exercise real context, so the outputs feel like actual work product, not homework.

• 11 modules, roughly 40–50 hours total
• 30-minute, self-paced lessons
• No paid tools required beyond a Claude subscription

If you’ve been curious about Claude Code but didn’t know where to start as a PM, this is designed for exactly that. Each module builds on the last, so you end up with something functional rather than a collection of one-off prompts.

Repo: https://github.com/vishalmdi/ai-native-pm-os

If you find it useful or think you might come back to it later, a star on GitHub helps a lot — and I’m happy to answer questions in the comments.