I like being able to go after particular cards instead of just opening randomly. Anyone doing this?

I used to think I was a fairly hands-on PM.

Spoke to users.

Wrote detailed PRDs.

Made decent wireframes.

Could write basic SQL.

Sat with engineering during grooming.

Knew enough technical words to survive most discussions.

Then I tried building an actual working product with AI and realised how much of my job still ended at “someone else will figure this out”.

The product was simple on paper.

An internal tool where the sales team could upload call notes and get:

• repeated objections
• competitor mentions
• follow-up tasks
• accounts at risk of going cold
• patterns across the whole week

I had already made a PRD for something similar at work.

Around 11 pages.

User stories.

Edge cases.

Success metrics.

Flow diagrams.

Very proper.

During a GrowthX build week, I decided to actually build a rough version instead of writing one more document.

Used Claude for the first backend.

Generated a basic UI.

Connected a transcription API.

Added a database.

Got the happy path working in around two days.

Upload call.

Get summary.

See action items.

I was feeling quite smart.

Then two engineers reviewed it.

First question:

“What happens if the same call is uploaded twice?”

Had not thought about it.

“What if the transcript is 90 minutes?”

No idea.

“How are accounts being matched if the salesperson writes the company name differently?”

Not handled.

“Why are you sending the entire transcript to the model every time someone opens the account?”

Because that was the easiest thing to build.

“What does the confidence score mean?”

Whatever Claude had decided it meant.

That review was uncomfortable because none of these were exotic engineering problems.

They were product decisions hiding inside technical implementation.

In the PRD version, I could write:

“The system should intelligently identify duplicate calls.”

Sounds good.

When building it, I had to decide what duplicate actually means.

Same file?

Same salesperson and timestamp?

Same transcript?

What if a call gets uploaded once through Zoom and once manually?

I could no longer hide behind one elegant sentence.

Same with “surface important objections”.

Important according to whom?

Frequency?

Deal value?

Sales stage?

Whether the customer sounded angry?

Whether the competitor was mentioned?

The prototype forced me to confront how vague a lot of my product thinking was.

AI did make many PM tasks much cheaper for me.

Research summaries are cheaper.

First-draft PRDs are cheaper.

Wireframes are cheaper.

SQL is cheaper.

Basic prototypes are much cheaper.

Writing ten versions of microcopy is basically free.

But cheap does not mean solved.

The more AI handled the output, the more important these became:

• choosing the correct problem
• defining what good output means
• knowing which edge cases matter
• understanding technical trade-offs
• deciding what should not be automated
• getting the workflow adopted
• knowing whether the user will change behaviour
• deciding what happens when the model is wrong

AI helped me build a tool.

It did not tell me whether salespeople would trust it.

It did not tell me whether managers wanted summaries or only wanted missed follow-ups.

It did not tell me whether the company would allow customer calls to leave its system.

It did not tell me whether reps would correct bad output or quietly stop using the product.

Those are still product problems.

I do not think every PM now needs to become a production engineer.

I still cannot review backend architecture properly.

I am not going to pretend I can replace an experienced developer because I got a prototype running.

But I do think the bar has moved.

A PM who can build a rough workflow, put it in front of users and understand where it breaks will have a much better conversation with engineering than a PM who arrives with a 14-page PRD and says “technical feasibility to be assessed”.

The GrowthX experience was useful because nobody cared about how nicely I had framed the problem.

I had to show the screen.

Someone clicked the wrong thing.

The flow broke.

An engineer asked why I had made a decision.

I could not answer.

That taught me more than another session on AI product strategy would have.

My current view:

PM is not becoming less important.

A lot of PM output is becoming less valuable.

The PMs who survive will probably spend less time proving they are organised and more time proving they have judgment.

Curious how this is changing inside Indian companies.

Are PMs in your org expected to prototype now?

And when people say PMs should “become builders”, how far do they actually mean?

Functional prototype?

Basic code understanding?

Production ownership?

Or just better collaboration with engineering?

https://preview.redd.it/nhp62hwdjyeh1.png?width=2280&format=png&auto=webp&s=a140b6f1bf03913ab8e8022fe7286d3fdbc3ccda

https://preview.redd.it/psbnb1wjjyeh1.png?width=1529&format=png&auto=webp&s=b040992938f2a1e885697e8f401361adfe3d9462

Note: This is probably pretty basic. Just sharing.

I tried building a data analysis dashboard with Hy3 last week. I'm still pretty new to using AI for data analysis, but I wanted to share how the dashboard evolved over four iterations.

V1

I started with three simple instructions: assign a role, define the task, and describe the context. It even picked a matching color palette for the dataset (brown for coffee sales). The biggest issue, though, was that everything was crammed onto one page.

V2

I added a sidebar, file upload, and live data updates. The pages looked better, but it still felt like one long report with navigation.

V3

I asked for one page per business question, and multilingual support. With a cleaner layout, I finally started reading the analysis. That's when I realized some conclusions weren't actually supported by the data. One example was the claim that 'the bakery is low attach and price'.

V4

I challenged that bakery thing and gave it a new task: review and verify every insight. It re-ran the calculations on the original dataset, matched the Python analysis, regenerated the missing metrics, corrected all 13 flagged insights, and fixed a startup bug.

That's when I finally felt comfortable sharing it. This was my first time using AI-assisted data analysis for work. And it happened during Hy3's free period, so I could keep iterating without worrying about tokens (lucky enough).

The biggest lesson for me wasn't how to write better prompts. It was realizing that verification is probably more important than generation.
I only questioned one conclusion. Once the verification process started, it found a dozen more issues on its own.

Maybe this is just what working with AI actually looks like. I'd love to hear how people with more experience approach it.

Posting the full numbers because generic “take a PL and clear everything” advice is useless.

Take-home: ₹60k
CIBIL: 650
Total card limit: ₹1.5 lakh
Current outstanding: ₹1.2 lakh
Overall utilisation: 80%
Existing card EMI: ₹4,850, six months remaining
Rent + food + bills + family contribution: around ₹34k

So after essentials and the existing EMI, roughly ₹21k is left.

The problem is that I have been paying more than minimum due, but not enough to properly kill the outstanding. Both cards charge around 3.5% monthly on the revolved balance. One unexpected expense and the utilisation goes back up again.

I am considering three options:

1. Continue paying the cards directly

No new enquiry or processing fee, but interest remains brutal and there is no fixed end date unless I stop using both cards completely.

2. Convert the outstanding into card EMIs / balance transfer

Could be cleaner than revolving, but the offers showing inside the apps are not particularly attractive. Also, part of the balance is already under EMI.

3. Take one ₹1.2 lakh personal loan

For rough calculation only, at 24% for 18 months, EMI comes to around ₹8k, excluding the processing fee.

That is lower than what I am currently trying to throw at the cards, and at least there will be a fixed closure date. But a longer tenure would mean paying much more overall.

I checked Kissht because my profile just meets its stated basic criteria:

• ₹50k minimum monthly income
• CIBIL score of 650 or above
• Loan range of ₹30k–₹5 lakh
• Tenure between 6 and 60 months
• Approved amount transferred directly to the bank

But I understand that being eligible to apply does not mean approval, ₹1.2 lakh sanction or a particular interest rate. Existing utilisation, recent enquiries and banking behaviour will still matter.

My bigger concern is discipline.

If I take a personal loan, clear the cards and then start using the available limits again, I will end up with the PL EMI plus fresh card debt. That would be worse than the current situation.

Would you:

• Take a structured personal loan and lock both cards?
• Convert everything into card EMIs?
• Keep attacking the outstanding without another hard enquiry?
• Reduce the card limits after clearing them?

Also, should I wait for utilisation to fall before applying, or will waiting make no difference at 650?

May have to shift from Delhi in the next 8-12 months and I’m confused about drinking water setup.

Buying a decent RO means 15-20k upfront, installation, filters, service, then uninstalling and reinstalling wherever I move next. New city ka water source/TDS bhi completely different ho sakta hai.

Using cans right now but delivery dependence is irritating.

I checked Rentomojo purifier rental. Starts around ₹419/month and maintenance, repair, installation and filter change are included. For a temporary flat, this feels more sensible than buying.

But what do people who keep shifting actually do?

Buy and carry the purifier?
Rent one?
Continue with cans?
Ask landlord to install?

Delhi/NCR renters, practical advice please.

Finally decide to buy a dash cam. I think 3 channel is worth it. It's not just for accidents, but also for recording what's happening inside the car. At the end of the day, it's there to protect yourself. I've narrowed it down to these two. 70mai T800 and the Viofo A329S. Rn, I’m leaning toward the 70mai because it seems like a better value while offering similar specs. I’ve also done some research on the Viofo A329S, and there are quite a few positive reviews about it. What are you guys using? Would you recommend either of these, or is there another 3 channel dash cam I should consider?

A lot of discussions focus on agent workflows and running multiple agents in parallel. But in practice, many people are still managing this in a very manual way: a handful of terminals, own window, switching between them by hand.

It works for small experiments, but once the workflow becomes more complex, things start to break down. It becomes difficult to track what each agent knows, what has already been done, and how different agents should share information.

That's the reason why we need multi-agent orchestration. I’ve looked into several tools exploring agent-based collaborative workflows:

AutoGen- Developed by Microsoft. Supports agents discussing with one another, invoking tools, and breaking down tasks

Anvita flow- Explores networked patterns that allow different agents to discover each other, leverage specialized capabilities, and collaborate to complete tasks.

Claude Code- Enables Claude to work directly in a coding environment, helping with code understanding, editing, debugging, testing, and project management.

Claude flow- agent orchestration platform for claude. multi-agent swarms and autonomous workflows
CrewAI- Emphasizes role assignment, task workflows, and team-style collaboration.

Saw the latest updates regarding Claude’s continuous improvements in models and tools, and I look forward to seeing how these advancements shape the future of agent-based workflows.

Hi guys, currently 3rd year student here and my side hustle which I juggle lately was mass hiring. This is flexible and you can do it with your free time, all you need to have is a wifi or good data connection.

Requirements

• Good Reading Comprehension
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Apply and Join Here⬇️⬇️⬇️

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I run a mid-sized corporate office and we're undergoing a much needed overhaul of our breakrooms on three floors. I've been asked to find about six new stand-alone water dispensers to deal with the daily demand of our staff of approximately eighty.

I'm looking at a couple of very good appliance manufacturers on Alibaba to see if we can get the units from them direct and save a ton of money from the crazy monthly leasing contracts our local water delivery guys are giving us. Communication with the factory has been good, but the more I dig into the technical details, the more I feel like I'm running into a brick wall with the actual building infrastructure.

Half of our team leaders are asking me to go with direct-plumbed, bottle-less filtration models so that no one has to change out heavy jugs. But our building maintenance guy just told me that it will take him to cut through firewalls to get dedicated water lines split and run to the far corner breakrooms on floors two and three, and it will cost him nearly two grand just in plumbing labor.

Given that plumbing problem, I began to consider the bottom-loading heavy-duty freestanding water dispensers which would circumvent the line-splitting issue altogether. But now I'm worrying about how to store 40 pound water jugs in our small supply closets and if the electric pumps inside the bottom loaders will last long enough to be used in the office every day without burning out in a couple of months.

The suppliers have been very helpful in providing us with pump wattage data and the filter life sheets, but they can't really assess our building's peculiar layout or our actual usage patterns. I can't decide whether to pay for the huge initial plumbing bill for direct lines or the weekly hassle of handling heavy water bottles.

If you've ever had to replace your office drinking water system, what did you consider when making your decision? Am I being too sensitive about the maintenance of a bottle system, or is it really worth paying the extra for direct line hookups from the get-go to avoid hearing people gripe about empty jugs?

Everyone keeps trying to make agents more autonomous. But if agents can not only complete tasks independently, but also communicate and collaborate with each other, how will software itself evolve?

Perhaps in the future, we won’t need to constantly switch between different apps for research, analysis, writing, scheduling, or automation. Instead, specialized agents could work together in the background, combining different capabilities to complete entire workflows based on our goals.

So from the perspective of everyday users, what will this change look like?

Will the way we use software shift from “finding and operating tools” to simply “setting goals and letting agents handle the process”?

These are some thoughts I had after learning about AnvitaFlow, and I’m curious how others see the impact of AI agents on the future of software.

I am not sure if this perspective is correct; It may take a long time to find out.

there's a hermes buildathon on 11 july, build by day demo by evening, there are no talks no panels.

three tracks: virality (make something people share), revenue (real signups or payments same day), ai-as-an-agency (replace something an agency charges for).

curious what this sub would ship. not wrapper stuff. something that makes someone stop scrolling. what would you build?

Since its the summer sale right now, what game bundles should i get to maximize my 30$? I prefer singleplayer games, mostly horror, soulslike, grindy, and has a lot of content.

Games I played and liked was:

Dark Souls Remastered
Nioh 1
Wuthering Waves
Grim Dawn
POE1
Terraria
Minecraft
Hollow Knight
Monster Hunter World

Why is that when I try to hover to some of the items either in crafting guide or recipe browser mod i cant see the tooltip of it or any desc at all of the item im seeing?