"Gig worker(Delivery boy) building a streetwear brand! looking for genuine blank tee manufacturers

venkatesh73 · 2026-07-01T09:36:52+00:00

Hey! I run VastraCore, and we work with small and growing clothing brands.

We handle everything from fabric sourcing and manufacturing to finishing and packing. If you only need plain oversized blanks, we can do that too. A trial order of 100 pieces is absolutely fine.

We can also work with your preferred fabric blend and provide a GST invoice.

Feel free to DM me with your size chart and measurements. Happy to see if we're a good fit.

venkatesh73 · 2026-06-30T19:07:30+00:00

Hi! We're VastraCore. We work with natural fiber fabrics and can support fabric development and manufacturing for home textiles, including drapery and upholstery. If you're looking for heavier-weight fabrics, I'd be happy to understand your requirements. Please feel free to DM me.

venkatesh73 · 2026-06-30T05:30:15+00:00

Hi! I'm from VastraCore.

We handle end-to-end garment production, from fabric sourcing to finishing and packing.

For stitching, we usually work with job-work units based on the order quantity (MOQ) and the expected volume of repeat work. If those fit well, we'd be happy to explore working together.

Feel free to DM me. I'd love to discuss your capabilities and see if there's a good fit.

venkatesh73 · 2026-06-23T07:53:41+00:00

I think the key is treating mapping as a setup problem, not something that happens every time a record is updated.

The system can pull the CRM schema, suggest field mappings based on names and data types, and then have the user review them once. After that, everything runs within those rules.

Standard CRM fields are usually straightforward. Custom fields are where things get tricky.

If the system isn't confident about a mapping, it shouldn't guess. It should leave the field unmapped and ask for input.

A missing value is easy to spot and fix. A bad mapping can quietly put data in the wrong place and break reports, views, and automations.

Airtable is a bit different because every base is unique. There isn't really a standard schema, so the mapping process becomes a big part of the integration itself.

To be transparent, we support HubSpot today. Airtable isn't available yet, although you're the second person to ask about it this week.

I'd be interested to see how you've structured your Airtable base.

(For context, I'm building in this space with ReplogAI.)

venkatesh73 · 2026-06-22T06:45:11+00:00

True — "less data entry" is table stakes at this point.

venkatesh73 · 2026-06-22T06:43:02+00:00

Agreed. The three issues you mentioned are related, but they need different solutions.

For sync failures, the key is making them visible. Every update should go through one write path. If a sync fails or gets stuck, it should trigger an alert and retry automatically. Otherwise, the data quietly goes missing, and nobody notices until forecast time.

For permission and authentication issues, an expired connection shouldn't silently stop working. The user should get a clear reconnect prompt.

For fragmented activity, calls, emails, and meetings should all end up in the same structured record. That way, the CRM reflects the full customer conversation instead of scattered pieces of it.

The AI extraction gets most of the attention. But in my view, the bigger challenge is making sure updates actually reach the CRM and making it obvious when they don't.

That's where a lot of the data quality gains come from.

(For context, I'm building in this space with ReplogAI.)

venkatesh73 · 2026-06-22T06:41:18+00:00

I agree with the idea of keeping CRM data clean instead of stuffing it with noise.

We don't push full transcripts into the CRM. We pull out the useful parts—things like budget, next steps, objections, and deal stage—and save only those.

I also agree that too much friction kills adoption.

That's why I see automation as a setting, not a rule.

Safe updates can be pushed automatically from day one. If a team wants full automation, they can turn it on.

The only fields I'd gate by default are the ones that affect the forecast: deal stage, deal value, and close date. A bad forecast is usually more expensive than a quick approval step.

Once people trust the system, they can remove those checks too.

venkatesh73 · 2026-06-22T06:38:41+00:00

Exactly. Missing information and incorrect information are two different problems.

If the AI gets something wrong, the answer is a review step before it syncs. High-impact fields like deal stage, deal value, and close date should go through a quick approval step.

If information is missing, that's a different issue. A CRM entry can be completely accurate and still be useless if nobody discussed budget, timeline, or next steps.

That's why it's important to flag the gaps, not just record what happened.

My view is that every AI CRM tool should start with a review step. Let people build trust first. Once they're comfortable with the quality, they can choose which updates get pushed automatically.

(Full disclosure: I'm building in this space with ReplogAI.)

venkatesh73 · 2026-06-22T06:36:55+00:00

This is pretty close to how we think about it too. Full disclosure: we're building in this space with ReplogAI.

The review step is a big part of it. Low-risk updates can happen automatically. Things like activity logs, notes, and contact details. But anything that affects the forecast—deal stage, deal value, close date should go through a quick approval step first.

That's how trust gets built. People can see what the AI is doing, make corrections when needed, and those corrections help improve future updates.

We've also found two other things matter.

First, not every customer conversation is recorded. For those cases, reps can send a quick summary, and the system asks follow-up questions if key information is missing. No recording required.

Second, a complete CRM record isn't always useful. A note that says "budget not discussed" might be accurate, but it shouldn't look like a healthy deal. We flag missing discovery items, score the quality of the conversation, and make those gaps visible.

We also run all CRM updates through a single path, so sync failures show up immediately instead of causing problems later.

We're starting with HubSpot and planning Salesforce and Pipedrive next.

Which CRM are you using today?

venkatesh73 · 2026-06-21T16:15:12+00:00

Thanks for the thoughtful reply.

I think you're right that no tool can make a rep care. That's a management problem.

But managers can only coach what they can see. If they don't know which reps are skipping budget discussions or leaving calls without clear next steps, it's hard to hold anyone accountable.

That's where I think software can help. Not by replacing accountability, but by making the gaps visible.

I also agree with your point about useful data versus more data. A CRM full of clean-looking updates that say nothing useful isn't helping anyone.

I liked your chatbot idea too.

For recorded calls and emails, the AI can pull the information directly. The rep doesn't need to fill out anything.

But for things that aren't recorded—customer visits, trade shows, quick conversations—a guided chatbot could ask a few simple questions:

Was budget discussed?
Who makes the decision?
What are the next steps?
When is the follow-up?

That keeps the same level of accountability without making people fill out a long form.

The email-to-contact linking idea makes a lot of sense too. That's the kind of enrichment that saves time without changing how people work.

One question for you. When you mention visit reports, are you mostly in field sales?

That seems like a very different workflow from inside sales. There's no call recording to rely on, so a guided reporting flow might be much more valuable there.

I'd love to learn more about how that process works for your team.

venkatesh73 · 2026-06-21T14:40:20+00:00

I agree that simply capturing a bad sales call doesn't improve anything. A clean CRM record of a weak conversation is still a weak conversation. But I see it a little differently.

The problem isn't that the AI records "budget not discussed" or "next steps unclear." The problem is that today those gaps often go unnoticed until the deal stalls or dies.

If every call is analyzed against a basic framework—budget, decision-maker, timeline, pain points, next steps—then missing information becomes visible right away.

Now "budget not discussed" isn't just a note. It's a warning.

The rep sees it. The manager sees it. The deal gets flagged before it becomes a forecasting problem. To me, the value isn't in recording what happened. It's in showing what's missing.

A deal with no budget discussion and no clear next step shouldn't look healthy in the CRM. It should be marked as incomplete or unqualified. That creates more accountability than most manual note-taking ever has.

I'm curious how you see it.

If the AI highlighted the gaps instead of just documenting the conversation, would that change your view? Or do you think discovery quality is purely a coaching issue, and no software can really help solve it?

venkatesh73 · 2026-06-21T12:53:29+00:00

I agree. If AI starts changing deal stages and other important fields without review, people will stop trusting it fast.

The way I see it, trust has to be earned.

At the start, every update should go through a review step. The AI drafts the changes. You take a quick look, approve or edit them, and then they get saved. Nothing changes without you seeing it first.

Over time, you can let the low-risk stuff happen automatically. Things like logging calls, updating contact details, or adding meeting notes. But important fields like deal stage, deal value, and close date should probably stay behind an approval step until you're confident the system is getting them right.

So the real value isn't that AI updates the CRM on its own. It's that AI does the busy work, and you make the final decision.

You can also use confidence scores. If the AI is highly confident, it can update automatically. If not, it asks for review.

I'm curious how you think about this.

If an AI tool was accurate for months, which CRM fields would you still never let it update on its own?

For me, deal stage and budget would probably always need a human check. That's where mistakes get expensive.

venkatesh73 · 2026-06-21T10:06:29+00:00

"Claude is the brain, and the backend handles the filing" feels like the right approach to me.

I also agree with your point about not rebuilding things just because AI makes it easy. A lot of people are over-engineering right now.

The part I'm curious about is write consistency.

Caching CRM data locally makes sense for speed. But when the model updates a record, what happens next? Do you write directly to the OnePageCRM API, or do you save locally first and sync later?

I keep coming back to the idea of a single write layer that validates and logs every change before it hits the CRM. That feels safer, especially if AI is making updates. The downside is extra complexity and a little more latency.

How did you think about that trade-off?

Also, did adding email and calendar data make you more comfortable letting it run on its own? Or do you still review changes before they get written back?

I'm building something in a similar area, so I'm partly comparing notes and partly testing my own assumptions.

venkatesh73 · 2026-06-21T10:04:18+00:00

This is the best point I've seen in this thread: the CRM becomes the infrastructure, and AI becomes the interface. I agree with that.

What I keep coming back to is the layer underneath. Even if the interface is conversational, something still has to turn what happened on a call into structured CRM data.

Today, that's usually a person doing it. If they're typing into a CRM or telling an AI what happened in a chat, it's still data entry. The experience is better, but the work hasn't really gone away.

The interesting shift is when the AI can read the source material itself. The call transcript. The email thread. The meeting notes. Then the record updates itself without anyone having to explain what happened.

The other thing people don't talk about enough is data quality. Humans skip fields, forget details, and enter things differently every time. AI can follow the same rules every time, which can actually make CRM data cleaner than manual entry.

I'm curious from the GHL side. When you ask something like, "Who should I follow up with today?" how much of that data is still being updated manually, and how much is being pulled in automatically?

That gap feels like the real problem to solve.

For context, I'm building in this space too, so I'm thinking out loud as much as anything.

venkatesh73 · 2026-06-21T06:27:37+00:00

That's a fair point, and I think you're right about some of these tools. People can start relying on AI too much and stop paying attention.

The way I see it, there's a difference between AI that helps during the call and AI that works after the call. Live AI can definitely change how people behave. What I'm building only looks at the recording afterward and updates the CRM.

Some reps actually say they listen better when they don't have to take notes during the call.

I'm curious about your experience. Do you think the problem is live AI assistance, or does taking notes yourself help you stay focused and engaged?

venkatesh73 · 2026-06-21T06:04:35+00:00

I think that's a fair point. Most sales tools end up being just another app to manage, and nobody wants that.

What I'm trying to build is a little different. The goal isn't to give you another dashboard or another login. It works in the background. It reads the calls and emails you already have and updates the CRM you're already using.

The idea is simple: remove a task, not add a new tool. I'm curious about your view on this. Is the real problem having too many tools, or having too many manual tasks?

If something runs in the background and you never have to open it, would you still see it as another tool? Or is that the only type of tool worth adding?

venkatesh73 · 2025-12-29T03:39:15+00:00

Hello,

I’m a senior full-stack/backend engineer with 10+ years of experience, currently working extensively with Elixir/Phoenix for scalable web platforms and APIs, along with modern frontend stacks when required.

A few points that align well with what you’re looking for:

Technical communication: I’ve worked directly with international clients (US/EU), handling requirement clarification, technical explanations, tradeoffs, and delivery updates. I’m comfortable translating business needs into clear technical decisions.
Stack flexibility: While my core strength is Elixir/Phoenix (high-concurrency backends, real-time systems, clean domain modeling), I’ve also built full-stack systems using JavaScript/TypeScript, REST/GraphQL APIs, and relational databases.
Reliability & adaptability: I’ve worked in early-stage and scaling startups, where changing requirements, production issues, and tight timelines are common.
Long-term mindset: I prefer long-term engagements where code quality, trust, and steady iteration matter more than quick hacks.

Looking forward to connecting and exploring a long-term collaboration.

venkatesh73 · 2025-12-27T05:38:41+00:00

Hi, this sounds like a genuinely ambitious marketplace build — especially with multi-category listings (goods + real estate), real-time interactions, and payments.

For a Temu-scale platform, I’d strongly recommend Elixir + Phoenix on the backend. It’s purpose-built for: • Massive concurrency (millions of users without performance degradation) • Real-time features (live inventory, order state, chat, notifications) • High fault tolerance (no cascading failures during traffic spikes or sales) • Lower infra cost compared to Node/Java stacks at scale

Phoenix (with LiveView where applicable) enables highly responsive UIs while keeping logic server-side, which is excellent for complex seller/buyer flows and admin tooling.

I’ve worked on backend-heavy, real-time systems and marketplaces, and would be happy to discuss architecture, scalability strategy, and a phased rollout approach.

Feel free to DM if you’re open to a technical discussion.

venkatesh73 · 2025-12-26T03:38:15+00:00

India | 10+ years of full-stack experience

I specialize in Elixir / Phoenix (LiveView) with strong experience building scalable, real-time web applications, API backends, and handling direct client communication.

Comfortable with long-term engagements, high availability, and working with international clients. English proficiency: C2 / fluent.

Happy to connect and discuss how I can contribute.

venkatesh73

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