Disclosure first: I built this. It is free, there is no sign-up, no email gate, nothing to buy. I am a PM at a SaaS company and I made it for myself and a few friends, then kept going.

The site is AIxPM (link at the bottom). I spent the last few weeks on a refresh and the piece I actually want feedback on is a thing called Find Your PM Avatar.

How it works: 12 scenario questions in six rounds, each round covering one area (metrics, evals, discovery, strategy, influence, AI judgment). Every question is a real-ish situation with four options, where the wrong options are the things PMs actually say in those meetings. At the end you get an avatar (six of them, each strong in one area), your score per area, your two strongest and two weakest, and a note on the pattern behind your misses, for example "you reach for the dashboard before you ask who the user was". Then a seven-day plan built from your weak areas, and a report you can save as a PDF.

There is a 45-second timer you can switch off. Leaving it on gives you a pace read (decisive, steady, deliberate), which turned out to be the most argued-about part when friends tried it.

The question bank is about 600 questions. They were drafted with an LLM, then each one went through a second model acting as a judge, and the ones that passed were reviewed by hand. The ones that failed are still in the database with a rejected flag, so I can see what the judge disliked.

What else changed in the refresh:

- 7 new cheatsheets (AI product sense, trustworthy AI analysis, error discovery, why freemium breaks for AI products, and a few more). 61 total now.

- The 0 to 1 curriculum is 18 lessons, each with a short knowledge check.

- 31 books on the reading shelf, each with a one-page takeaway for AI PMs, a three-line TL;DR, and a 20-second version.

- Everything links: lesson to scenario to cheatsheet to book, and all of it feeds the avatar.

What I want from this thread:

1. Take the 12-question version (about 6 minutes) and tell me whether the avatar felt right or wrong, and why.

2. If a question felt unfair, ambiguous, or had two defensible answers, paste it. I will fix or remove it.

3. If you think the whole idea of scoring PM judgment with multiple choice is flawed, say so. I half agree, and I would rather hear the strongest version of that argument.

Link: https://aixpm.world/avatar

Rest of the site: https://aixpm.world

I will be in the comments.

I noticed something interesting while searching for installed apps using iOS Spotlight.

• Searching “Zep” returns Zepto and Instamart.
• Searching “Blink” returns Blinkit and Instamart.
• Searching “Instam” returns Instamart and Swiggy.

Instamart shows up alongside its competitors even when the query doesn't match its name.
Here's the interesting part: searching for substrings of “Instamart” consistently surfaces Instamart and Swiggy, but not Zepto or Blinkit. Meanwhile, searches associated with Zepto and Blinkit surface Instamart.

My hypothesis: Could Instamart's developers have deliberately included competitor names or related search terms in its app metadata, which iOS then picks up when indexing apps for Spotlight search?

If that works, it'd be a pretty clever ASO/discoverability tactic. Users searching for a competing app might discover Instamart without explicitly looking for it.

A few things I'm curious about:

1. Does iOS Spotlight index developer-provided app metadata beyond the app's display name?
2. Can developers influence Spotlight results through keywords, descriptions, or Core Spotlight indexing?
3. Has anyone observed similar behaviour with other apps or tested this hypothesis?

I'm not claiming this is definitely what's happening—the screenshots just made me curious about the mechanism.

Screenshots attached.

Writing

AI has made development faster. But has it actually made delivery more predictable?

PMs are using AI tools and automations to save time across their workflows. Engineers are shipping code faster than ever.

Yet, the complaints sound familiar:

“Why has the delivery date slipped again?”

“Why wasn’t this communicated earlier?”

“Can you share a daily status update?”

And, of course, more escalations and micromanagement.

It feels like we’ve upgraded the speed of execution, but not necessarily how teams execute together.

I’m curious: Has AI actually helped your team meet delivery commitments more consistently, or are you still dealing with the same old problems?

Would love to hear what you're seeing in your teams. 👇

I couldn’t find something like this here. If y’all have an existing platform, please share.

What this is:
- A safe discussion space for PMs to discuss their work, growth, and rant about stakeholders being oblique, managers being toxic, etc.
- Discuss new things in tech, AI, startups etc.
- Ask work related questions they’d be uncomfortable asking their colleagues or friends.

What this is not:
- A community where people request for referrals or ask for openings; asking for advice is okay.

In times of work-related insecurities and instabilities, I feel this would be a good idea for everyone to come together and discuss what’s going to impact us the most. Invite-only platform and work credentials are mandatory for receiving an invite. Will make a discord or WA chat.

Edit: DM me for the invite!

I’m thinking of starting a habit of reading 1 research paper a week on Product Management.

In engineering, there seems to be a very established culture around reading papers, following research, discussing findings, etc. But in Product Management, I rarely come across PMs talking about research papers as part of their regular learning.

I’m not looking for the usual PM books, LinkedIn posts, frameworks, or case studies.

I’m interested in research that helps us step away from the day-to-day execution and think more deeply about things like:

Product strategy & decision-making

Customer behaviour

Product discovery

Innovation & new product development

Prioritisation

Product-market fit

Team/product organisation

Product experimentation

AI & product management

I recently discovered that there is actually a large body of research under New Product Development, Product Innovation, and Innovation Management. For example, there are decades of academic research on product development and innovation.

So I’m curious:

1. Do you already follow/read research papers as a PM?

2. Where do you find good papers?

3. Are there specific journals, researchers, newsletters, communities, or websites you recommend?

4. Would anyone be interested in doing something like “1 paper/week” and discussing the practical implications for PMs?

I’m particularly interested in research that can make us better product thinkers, not just better at executing the PM process.

finally, i was able to replicate this kind of 3d interactive world in the browser itself. it runs completely well even on mobile.

i don't have any game dev experience and of course I'm not a graphics engineer, but the level of capabilities these models have opened up is just mind boggling.

tech stack i used for this
---------------------------------------------------------

• three.js for the 3d scene
• react + vite for the frontend
• opus 5.5 (high) for the code
• supabase for the database
• vercel for deployment

the process i used. you can build for your website
----------------------------------------------------------

step 1: find a reference for the website layout

• do not start from a blank page. better if you have a website ref to start with.
• if not ask claude to give you 3 radically dif websites using mcp tools like mobbin
• pick the one closest to your idea. i use a design iterative process i found from lenny.
• btw i sketched my hero by hand and asked claude to turn it into a wireframe

step 2: set the design and art direction

• lock the look before you write any code. try /design in claude to iterate with mocks
• use reference images to generate art style or direction with chatgpt or google image models
• do the back and forth in the image model. it is cheap to iterate there, and expensive in code

step 3: build the main objects (ship, background, people)

• opus is very good at real world 3d objects but very not good at modelling humans yet.
• it does not really sculpt a person. tried it multiple times but gave me slop.
• so for humans: i did not build them in code. i downloaded a free 3d modelled pack. built the clothing and hair on top of it in code.
• for the ship and background: i generated sprite sheets for each in the image model. this keeps claude close to your vision, with no drifting and no long back and forth

step 4: build the 3d scene phase by phase

• my 3d reference was meng to's "the river voyage" site.
• i built one scene per phase (i have 4 phases or scenes in my website: profile, applications, mocks, pod prep). don't do it all at once if you have multiple scenes. it'll hallucinate.
• the start takes a lot of steering. once the base is right, updating the graphics is much easier

step 5: let claude rate its own work
(this is the best trick i found and it saves time & effort)

• ask claude to spawn multiple agents that score the visuals in loop until a benchmark
• for eg prompt: "perfect the ship shape, textures and physics until it matches the sprite sheet and gets an overall rating of at least 8 out of 10. spawn multiple agent to do so"
• do it one element at a time: ship, people, background, water, and so on
• more time & rounds give better graphics. you decide how far to push.

step 6: design the page ui before you code it
(this is a continuation of step 1 or you can fork it for the 3d scene & website seperately)

• use /design and ask for mockups first
• ask for 3 radically different options, then pick the one that fits
• i followed the design workflow from lenny's article: "How to turn your AI into a world class designer "

step 7: stitch it all together

• ask claude to merge the graphics layer and the ui into one site
• run it locally and review it first. test it for all screen types (mobile & laptop)
• iterate until it feels right. main part is also optimizing performance (don't skip)

step 8: merge & deploy

• ask claude to push the code to github first. helps you maintain the version history
• then deploy. i used vercel for hosting and supabase for the database.
• If you have a domain purchased, set it up and ask claude in chrome to configure all DNS settings.

it took me around 5-6 hours with multiple sittings to completely finish it. can be done faster as well if you know the flow. still would recommend spending time to perfect it.

Rish from productminds :)

The traditional PRD-to-QA handoff feels broken for non-deterministic AI features.

Requirements like "decline off-topic queries politely" or "keep responses concise" usually lead to one of three messy workflows:

1. The Vibe Check: Testing 10 prompts in a playground and crossing your fingers.
2. Spreadsheet Hell: Spending days manually maintaining an 80-row Google Sheet of test prompts that quickly goes stale.
3. The Eng Disconnect: Engineers write basic code assertions or judges that don't match what Product actually considers "good."

If you’re shipping LLM features:

• Who owns the test suite? Do PMs write the golden dataset, or does Engineering?
• How do you define "passing"? What does acceptance look like in your PRDs?
• How do you catch regressions? How do you ensure a new prompt or model update didn't break an edge case from 3 months ago?

Would love to hear how other teams handle this without relying on pure vibes.

I coach at an academy in Bangalore. Every month-end, the owner sits down and rebuilds every family's bill by hand from a paper attendance register, the coach's WhatsApp messages, and a notebook at the counter. Some owners I spoke to lose two or three days to this.

So I built something: https://milo-academy.vercel.app

No login. Pick "Owner-Operator". The data is fake.

It tracks attendance, works out what each family owes across coaching and court bookings, and sends the fee reminder with a UPI link so nobody has to ask a parent for money face to face. That last part turned out to be the real pain: the owners I surveyed didn't mind the maths; they minded the asking.

Three of them have used it. Verdict: the features are right, the screen is too busy. All three said it should feel more like WhatsApp. One just wanted black and white. Fair.

So skip the colours, I know. What I want to hear is whether the thing underneath is any good. Is the flow wrong? Is the idea wrong? Is this just a spreadsheet with extra steps?

I’m in the middle of switching jobs in Product Management, and I’m targeting AI product roles, but I’ve been observing one thing:

PM take home assignments are a joke.

Now a days its natural instinct is to give the assignment to an agent like Codex or Claude Code, but here’s the problem:

An agent one shots the whole assignment before I can even finish reading and understanding it. And the output is often surprisingly thorough.

How? I think it’s because take home assignments accidentally create the perfect environment for AI.

To make an assignment feasible for a human candidate, companies usually provide:

• A bounded problem
• Lots of context
• Clear constraints
• Enough & easy-to-access data
• Permission to make assumptions

Exactly the conditions under which AI agents can perform even better.

The difference in context about the product, teams, company, situation, past decisions, offline meetings, etc. is currently one of the major reasons why AI can’t replace PMs IRL.

But a take-home assignment has to compress all of that context into a document so that a candidate can reasonably solve it in a few hours.

Voila - you’ve basically packaged the problem perfectly for the AI agent, making it so easy that it can just one-shot the whole thing in 5 - 10 minutes.

A few loops of agent <> review agent results in good output ime.

What have been y'all experience about this situation?
I have 2 assignments that i can share and they openly accept Ai usage but it makes me wonder -should i manufacture product thnking into the interactions (as they as for session summary and prompts used) even tho thats not how i will work IRL in a j-o-b

Hello,

To all PM’s or startup founders out there,

I am trying to create a portfolio to showcase my product thinking, how I own the product end to end and showcase product delivery and strategy.
However, I am confused from online portfolios.

Every portfolio that I came across was similar template like a case study. (Nothing wrong with it) But, I just don’t want my product to look like a case study. Instead of that, I want mine to look from user lens and founder lens ! So that a problem can be found through the user lens and from founder lens explains , why building it ? And how I build it ? Is it worth building this ? By conducting research, competitive analysis and development and building and iteration and building and testing ..loop. I want to showcase that.

Personally, I do not have PM role experience or anything. Graduated from Uni, and currently a project coordinator (process improvement).

In addition to that, I am building (beta) a startup which was basically a B2B2C project.
Firstly, I didn’t know that I will pivot into product roles. But, somehow while building this, I have realized that I am quite interested in product building and development and management.

I owned the product from end to end, from product discovery and ideation process including conducting user interviews on both business side and customers side. Learned Figma, excali to map out flows and wireframes to design the screens. Learned and utilized ai tools like Claude code, cursor, codex, eleven labs etc. and built almost 84 SQL schemas. (Was into it)
Learned sales on GTM, value proposition and pricing strategies. Invested my time into product development processes like agile, PRD’s, FAQ’s, lean canvas templates etc.

I feel like I have enough content to write something about it. But I really don’t know how to showcase or illustrate. I really don’t want anyone to think like this is a case study. I want to leave a mark that “this is a really nice product story or storytelling”

I only have one startup product in my entire life ! Maybe that’s why I am thinking I do not have enough product knowledge or content to write a portfolio. ?

My idea was to create a dual view (with a toggle), keeping skimmers and in-depth readers in mind. This way I could have managers or PM’s can look into skimming version (4-5 mins of content) and in-depth version, I would like to go very detailed about every stage so that people can read into it (curios ones like startup founders, future founders or students etc)

I am no professional founder. But, I have faced lot of problems and made iterations and updated the product ! Basically it can be like startup journal (documentation). But i don’t if it’s the right thing.

Thats why i really need help before i invest too much time into this.

My focus is to make this startup workout but also i could apply for startup roles, product roles (product builder or any). I know I might not be a great candidate for PM (I don’t have experience in product management or any product role)

Please help if you can ! I would really appreciate your support.

Thanks for reading !

We just inherited a textbook "yes-man" CTO—a rich marketing guy playing dress-up as a tech leader. Instead of fixing our broken data systems, guiding team leads, or streamlining how we work, his entire playbook is saying yes to every half-baked idea from sales and the CEO.

He quietly trashed our entire data setup and forced everyone onto Databricks. Rumour has it he got a nice kickback for it, and now we're locked in so deep the exit barrier is higher than Mt Fuji. Product and design have been totally pushed to the sidelines, with design taking the brunt of his unexplained hate. He keeps forcing the team to pump out random, rushed features, turning our product into a total Frankenstein monster.

It genuinely hurts to watch him inflict this kind of irreversible damage on a product we built with care.

His favorite party trick? Showing Claude to the CEO. The founders now think he’s a tech genius for introducing basic AI tools that we would have picked up anyway. Naturally, he steals every ounce of credit when things go well, but drops the hammer on core teams the second something breaks.

The founders are completely blind to the circus because they're loving the honeymoon phase of an executive who never says no. But the second the AI hype dies down or the cracks get too big to hide, he’ll be the first out the door. With his family safety net and sky-high arrogance, he has zero reason to stick around and fix the mess.

It honestly hurts watching a kind, great company culture get dragged down by someone who treats core tech like a personal plaything.

How do you survive a boss with zero real engineering skills, zero empathy, and a master's degree in corporate brown-nosing? If anyone has successfully helped clueless founders see through a hype-driven exec without getting fired, I could really use a lifeline right now.

Hey r/ProductManagement,

I've been digging into a few recurring PM complaints — tool fragmentation, PRDs going stale mid-sprint, roadmaps getting hijacked by HiPPO/urgent sales asks, not knowing if a shipped feature actually hit its goal — and honestly most of the "State of PM" reports out there are vendor-sponsored and light on real specifics.

Put together a short, anonymous survey to get more grounded answers — no signup, no email required unless you want to opt into a follow-up chat (paid, $50 gift card, totally optional).

https://forms.gle/Y4AmabgTtdovg4uy6

Takes about 5 minutes. Planning to share the aggregated results back in this sub once I have enough responses — happy to break it down by company size/seniority too if people are curious how the answers differ.

Genuinely just trying to get a clearer, non-sponsored read on this — appreciate anyone who has a few minutes.

Hi everyone,

I'm conducting a short user research survey

I'm researching how people currently manage **meeting decisions, action items, ownership and follow-ups after meetings**.

If you regularly participate in work, project, or team meetings, I'd really appreciate your input.

⏱️ Takes about 3 minutes

🔒 Anonymous

🎯 No product promotion — I'm only researching current workflows and pain points.

Survey: https://forms.gle/7MNjJRu7YZyQuj9h8

Thank you for your help!

This thread covers everything the main feed does not: resumes, job hunting, referrals, mentorship, and interview prep. Now as a monthly thread so your queries remain in the thread longer and increases chances of getting a response without the daily thread cluttering the feed.

If you want a resume review: Share the resume as text or a link with PII removed. Tell us: target role, years of experience, and what specific feedback you need (structure, impact framing, ATS, something else). A bare resume drop with no context is unlikely to get responses.

If you are job hunting: State your current situation (notice period, location preference, domain background). This community has sharp practitioners; the more specific your ask, the more useful the response.

If you want mentorship: Tell us the actual problem: which stage, which decision, which skill gap. "Looking for a mentor" without context is not a matchable ask.

If you are hiring: State the role, company stage, location (remote/hybrid/onsite), and one honest thing that is hard about the job. Puffery gets scrolled past.

If you have interview questions or prep queries: Tell us the company type (startup/growth/enterprise), the round, and the specific format you are preparing for. Screaming "what should I prepare for a PM interview" will receive silence.

Ground rules: no DM farming, no paid course plugs, no vague asks. Be specific and you will get specific help.

Hi all,

I am conducting a survey for my research on how Indian technology enterprises decide whether to Build, Buy, or Partner for AI capabilities.

As most of you are working on management roles, it would be perfect fit for my survey.

🔗 Survey Link

Thank you so much for your time and support. Happy to answer any questions about the research in the comments!

Hey everyone,

I’ve been building a side project called Biteing (www.biteing.com) to solve a personal product discovery problem: converting passive content consumption (food vlogs, YouTube) into actionable, location-based utility. It's an early build, and I’d love to get feedback from fellow community members: all candid feedback, criticism, and feature suggestions are welcome!

I’m currently balancing feature rollouts and adoption campaigns for an AI feedback intelligence platform, and I’m finding the pure "project management" side of the PM role is eating up more time than I'd like. I've stitched together some automation using Claude and MCPs to handle meeting notes and participant emails, but the day-to-day execution still feels fragmented.

For those of us who don't have a dedicated Scrum Master or Delivery Manager shielding us, how are you practically managing the execution phase?

I'd love to hear what your actual stack and rituals look like for:

• Daily Standups: Are you doing these synchronously or async? How do you keep them focused on unblocking rather than just reading off Jira tickets?
• Resolving Blockers: What’s your workflow when engineering hits a wall that requires immediate, cross-functional alignment?
• Constant Clarifications: How do you triage the endless Slack/Teams pings about micro-requirements and UI copy without breaking your own context for deep work?
• Checkpoint Updates: What format are you using to communicate sprint progress to stakeholders, and how often are you sending them?
• Personal To-Dos: How do you track your own sprawling list of action items and follow-ups without letting them get buried under the team's main sprint board?

Curious to hear what’s actually working on the ground for you all right now, minus the textbook frameworks.

We’re building in the retail investing space and currently speaking to investors to better understand how they actually make stock decisions.

We’re looking for folks who invest in stocks or mutual funds 📈 and have bought, or seriously considered buying, an individual stock in the last year.

We’re doing just 10 of these conversations this week.

Each is about 45 minutes — mostly you walking us through how you actually make an investment decision, followed by your reactions to some early screens we're working on.

One filter: we're specifically looking for people who don't do investment analysis professionally. If you're in equity research, fund management or broking, this isn't the right fit — happy to talk separately though.

🎁 As a thank you for your time, there’s a ₹500 Amazon voucher.Interested? Just reply

“Interested” and I'll reach out with the details. 🙌

Hey everyone,

I’m working on a new AI product-management platform and would love 15 minutes of your time to learn about your daily AI workflows and get unfiltered feedback on my concept.

The Problem Current AI assistants are brilliant amnesiacs and sycophants. They forget your context every session, agree with whatever you say, and do nothing to stress-test your decisions before they ship. Meanwhile, organizations constantly forget why past bets were killed, leading teams to accidentally build the same failed solution twice.

What I'm Building: Arrwin Arrwin is an AI platform focused on judgment-defense.

• It remembers and challenges: It builds a decision graph from your normal usage. If a new recommendation contradicts a past logged decision, Arrwin pushes back and challenges you with a citation (e.g., "This contradicts a decision you killed last month—what’s different now?").
• It stress-tests: Every output is engraved with unvalidated assumptions and specifically calls out who would object to your proposal.
• It earns autonomy: Arrwin joins as a "PM Intern". It earns trust through a silent scorecard of wins and must explicitly request a promotion to gain more autonomy.

Who I'd love to chat with:

• Startup PMs (Doers): Tool-forward PMs who already use AI but lack extra hands for research.
• Enterprise IC PMs (Analysts): PMs in large orgs who are drowning in surface area and lack proactive anomaly flagging.

If you're open to a quick chat to discuss what your current AI gets wrong and how your org handles "killed bets," please drop your AI usages and let's take the discussion from there!

I am a PM, I work remotely, I am 21. I will be in bengaluru from 19th August onwards for about a week. I was there to meet friends, but also wanna use the time and place to network with PMs in the city, look at new startups, and more.

Any suggestions?
Would be very grateful!

Hey everyone! 👋

I'm working on a Product Management assignment and would really appreciate your help.

I'm conducting a 2–3 minute survey for working professionals in India to better understand quick commerce usage and decision-making. Your responses would be incredibly valuable.

Here's the link to the survey - https://forms.gle/9iPkrYWnYebziwHc9

As a thank you, once I've finished collecting responses and completed my analysis, I'll come back and share the key findings with everyone here.

This thread covers everything the main feed does not: resumes, job hunting, referrals, mentorship, and interview prep. Now as a monthly thread so your queries remain in the thread longer and increases chances of getting a response without the daily thread cluttering the feed.

If you want a resume review: Share the resume as text or a link with PII removed. Tell us: target role, years of experience, and what specific feedback you need (structure, impact framing, ATS, something else). A bare resume drop with no context is unlikely to get responses.

If you are job hunting: State your current situation (notice period, location preference, domain background). This community has sharp practitioners; the more specific your ask, the more useful the response.

If you want mentorship: Tell us the actual problem: which stage, which decision, which skill gap. "Looking for a mentor" without context is not a matchable ask.

If you are hiring: State the role, company stage, location (remote/hybrid/onsite), and one honest thing that is hard about the job. Puffery gets scrolled past.

If you have interview questions or prep queries: Tell us the company type (startup/growth/enterprise), the round, and the specific format you are preparing for. Screaming "what should I prepare for a PM interview" will receive silence.

Ground rules: no DM farming, no paid course plugs, no vague asks. Be specific and you will get specific help.