u/Flimsy_Bridge7841

Hey everyone, I’m a solo founder building Crestorflow, an AI-native career execution platform.

The problem I’m trying to solve is pretty simple: people can learn almost anything online, but there’s still a huge gap between learning a skill and proving you can actually do the work. Courses and certificates don’t necessarily translate into employability, while companies increasingly care about demonstrated ability and outcomes.

Crestorflow is designed around one continuous loop:

Career goal → AI roadmap → Learn → Build → AI evaluation → Proof of work → Opportunities

Instead of giving everyone the same course, the platform uses AI to create a personalized execution path based on the user's goal.

The AI system I'm building has several agents working together:

Career Agent — understands the user's goal, current skill level, and target role, then creates an execution roadmap.

Learning Agent — finds and organizes relevant resources based on each milestone rather than forcing users through a fixed curriculum.

Project Agent — generates unique, practical projects that require the learner to actually apply what they learned.

Evaluation Agent — evaluates submitted work against predefined rubrics, identifies gaps, and provides feedback.

Proof-of-Work Agent — converts validated projects into structured portfolio artifacts that demonstrate specific capabilities.

Opportunity Agent — eventually uses accumulated proof of work and a trust score to match users with relevant contract/project opportunities or help them form small agencies.

The goal is to make AI the orchestration layer of the entire career journey, rather than simply adding a chatbot to an existing course platform.

I'm currently at the MVP stage and want to build this primarily with open-source models. I've already figured out most of the surrounding tech stack, but I'm stuck on a few things:

Which open-source models would you recommend for the different agents?

Should I use one strong model across the system or specialized models for different tasks?

What's the right architecture for securely running these models in production?

How would you approach deployment and infrastructure if the goal is to get the first 50–100 users without massively overspending?

What would you change about this architecture before I start building?

I'm especially interested in feedback from people who have actually shipped AI-native products or agentic systems, rather than just theoretical recommendations.

Would love some brutally honest feedback on whether this architecture makes sense and where you think the biggest technical/product risks are.

Hey everyone, I’m a solo founder building Crestorflow, an AI-native career execution platform.

The problem I’m trying to solve is pretty simple: people can learn almost anything online, but there’s still a huge gap between learning a skill and proving you can actually do the work. Courses and certificates don’t necessarily translate into employability, while companies increasingly care about demonstrated ability and outcomes.

Crestorflow is designed around one continuous loop:

Career goal → AI roadmap → Learn → Build → AI evaluation → Proof of work → Opportunities

Instead of giving everyone the same course, the platform uses AI to create a personalized execution path based on the user's goal.

The AI system I'm building has several agents working together:

Career Agent — understands the user's goal, current skill level, and target role, then creates an execution roadmap.

Learning Agent — finds and organizes relevant resources based on each milestone rather than forcing users through a fixed curriculum.

Project Agent — generates unique, practical projects that require the learner to actually apply what they learned.

Evaluation Agent — evaluates submitted work against predefined rubrics, identifies gaps, and provides feedback.

Proof-of-Work Agent — converts validated projects into structured portfolio artifacts that demonstrate specific capabilities.

Opportunity Agent — eventually uses accumulated proof of work and a trust score to match users with relevant contract/project opportunities or help them form small agencies.

The goal is to make AI the orchestration layer of the entire career journey, rather than simply adding a chatbot to an existing course platform.

I'm currently at the MVP stage and want to build this primarily with open-source models. I've already figured out most of the surrounding tech stack, but I'm stuck on a few things:

Which open-source models would you recommend for the different agents?

Should I use one strong model across the system or specialized models for different tasks?

What's the right architecture for securely running these models in production?

How would you approach deployment and infrastructure if the goal is to get the first 50–100 users without massively overspending?

What would you change about this architecture before I start building?

I'm especially interested in feedback from people who have actually shipped AI-native products or agentic systems, rather than just theoretical recommendations.

Would love some brutally honest feedback on whether this architecture makes sense and where you think the biggest technical/product risks are.

Hey everyone, I'm Abdul Malik. I'm a 19-year-old college dropout building Crestorflow, a skill-to-opportunity platform that bridges the gap between learning and earning.

The Vision The idea is simple: creators, SaaS founders, and agency builders can sell courses, mentorships, cohorts, and digital products. But here is the catch learners don't just passively consume content. They build real projects, create proof of work, and unlock paid opportunities.

We believe proof of work should matter way more than credentials.

Current Progress I've spent the past year putting in the reps. So far, I have:

• Validated the problem and market demand.
• Built the MVP.
• Networked heavily with founders in the space.
• Documented my building journey publicly to generate early interest.

Who I'm Looking For I'm looking for a technical co-founder who's excited about AI, marketplaces, and the future of work.

Ideally, you:

• Are based in Bangalore (I am looking for someone I can brainstorm and build with in person).
• Love building products from zero to one.
• Are highly comfortable with modern web technologies and AI integrations.
• Want to solve a meaningful problem for creators and learners.
• Are looking for a long-term startup journey, not a weekend side project.

If this resonates with you, I'd love to connect, grab a coffee, share the vision and see if we're a good fit. Feel free to drop a comment below or shoot me a DM!

Hi, I’m a budding entrepreneur currently building my startup in the pre-revenue stage. Along the way, I’ve been exploring different AI products and services. While I’m not a full-time engineer, I can understand code and contribute from a product management perspective.

I wanted to ask a few things:

\\-What’s the best approach to building an MVP using foundation models?

\\- I’m planning to implement AI features using AWS Bedrock, but I don’t have any prior AWS experience. Where should I start?

\\- Could you recommend learning resources or frameworks that would help me become a better product manager and solo founder?

\\- Finally, what would you focus on to reach the first 50–60 active users and demonstrate early traction?

Hi, I’m a budding entrepreneur currently building my startup in the pre-revenue stage. Along the way, I’ve been exploring different AI products and services. While I’m not a full-time engineer, I can understand code and contribute from a product management perspective.

I wanted to ask a few things:

\-What’s the best approach to building an MVP using foundation models?

\- I’m planning to implement AI features using AWS Bedrock, but I don’t have any prior AWS experience. Where should I start?

\- Could you recommend learning resources or frameworks that would help me become a better product manager and solo founder?

\- Finally, what would you focus on to reach the first 50–60 active users and demonstrate early traction?

Hi, I’m a budding entrepreneur currently building my startup in the pre-revenue stage. Along the way, I’ve been exploring different AI products and services. While I’m not a full-time engineer, I can understand code and contribute from a product management perspective.

I wanted to ask a few things:

What’s the best approach to building an MVP using foundation models?

I’m planning to implement AI features using AWS Bedrock, but I don’t have any prior AWS experience. Where should I start?

Could you recommend learning resources or frameworks that would help me become a better product manager and solo founder?

Finally, what would you focus on to reach the first 50–60 active users and demonstrate early traction?

Hi, I’m a budding entrepreneur currently building my startup in the pre-revenue stage. Along the way, I’ve been exploring different AI products and services. While I’m not a full-time engineer, I can understand code and contribute from a product management perspective.

I wanted to ask a few things:

- What’s the best approach to building an MVP using foundation models?

- I’m planning to implement AI features using AWS Bedrock, but I don’t have any prior AWS experience. Where should I start?

- Could you recommend learning resources or frameworks that would help me become a better product manager and solo founder?

- Finally, what would you focus on to reach the first 50–60 active users and demonstrate early traction?

Hi, I’m a budding entrepreneur currently building my startup in the pre-revenue stage. Along the way, I’ve been exploring different AI products and services. While I’m not a full-time engineer, I can understand code and contribute from a product management perspective.

I wanted to ask a few things:

-What’s the best approach to building an MVP using foundation models?

- I’m planning to implement AI features using AWS Bedrock, but I don’t have any prior AWS experience. Where should I start?

- Could you recommend learning resources or frameworks that would help me become a better product manager and solo founder?

- Finally, what would you focus on to reach the first 50–60 active users and demonstrate early traction?

Is AWS a good choice for building my mvp? Or should I stick to supabase and third party vendors?

Hey everyone, I'm Abdul Malik.

A year ago, I made the tough call to drop out of college to build my own startup. Since then, I've just been grinding to attending events, meeting founders, learning and building stuff from scratch.

Honestly, what pushed me to quit was realizing how outdated the system is. I was staring down a 10-year-old syllabus, worst placement cycles and the reality of paying lakhs just for a piece of paper that didn't even guarantee a job. It made zero sense. I always knew I wanted to build a startup, but college actually gave me the push I needed by showing me exactly what I didn't want to do. Sticking around just to write endless assignments, stress over internals, and give vivas felt completely useless to my actual goals.

That frustration led me to build Crestorflow.

It's a skill-to-opportunity platform but with a major twist. The idea is to bring in authentic creators-founders, builders and content creators who have actually done shit and have real expertise in domains like tech, development, marketing, growth, and design. They sell courses, cohorts, and mentorship to pass down real-world knowledge.

But here is the catch: it is not just another course platform, and it is definitely not a standard freelance platform. It is a proof of work marketplace. Learners get access to high-quality, practical content and after completing a course, they immediately build projects. Based entirely on those projects, they get connected with clients. You get hired for what you can actually build, not a meaningless certificate.

I really need some help and feedback from this community.

Is this a legit problem that you guys resonate with? What do you think could make a real difference in this space or are there any killer features that would make this stand out?

If you want to support or just check it out, I'd love for you to sign up for early access here: www.crestorflow.com.

Also, if any of you are currently stuck in that same college rut or facing this exact problem, shoot me a DM. Let's connect and make sure you get your roadmap figured out. Appreciate you all

Hey everyone, I'm Abdul Malik.

A year ago, I made the tough call to drop out of college to build my own startup. Since then, I've just been grinding to attending events, meeting founders, learning and building stuff from scratch.

Honestly, what pushed me to quit was realizing how outdated the system is. I was staring down a 10-year-old syllabus, worst placement cycles and the reality of paying lakhs just for a piece of paper that didn't even guarantee a job. It made zero sense. I always knew I wanted to build a startup, but college actually gave me the push I needed by showing me exactly what I didn't want to do. Sticking around just to write endless assignments, stress over internals, and give vivas felt completely useless to my actual goals.

That frustration led me to build Crestorflow.

It's a skill-to-opportunity platform but with a major twist. The idea is to bring in authentic creators-founders, builders and content creators who have actually done shit and have real expertise in domains like tech, development, marketing, growth, and design. They sell courses, cohorts, and mentorship to pass down real-world knowledge.

But here is the catch: it is not just another course platform, and it is definitely not a standard freelance platform. It is a proof of work marketplace. Learners get access to high-quality, practical content and after completing a course, they immediately build projects. Based entirely on those projects, they get connected with clients. You get hired for what you can actually build, not a meaningless certificate.

I really need some help and feedback from this community.

Is this a legit problem that you guys resonate with? What do you think could make a real difference in this space or are there any killer features that would make this stand out?

If you want to support or just check it out, I'd love for you to sign up for early access here: www.crestorflow.com.

Also, if any of you are currently stuck in that same college rut or facing this exact problem, shoot me a DM. Let's connect and make sure you get your roadmap figured out. Appreciate you all

Hey everyone, I'm Abdul Malik.

A year ago, I made the tough call to drop out of college to build my own startup. Since then, I've just been grinding to attending events, meeting founders, learning and building stuff from scratch.

Honestly, what pushed me to quit was realizing how outdated the system is. I was staring down a 10-year-old syllabus, worst placement cycles and the reality of paying lakhs just for a piece of paper that didn't even guarantee a job. It made zero sense. I always knew I wanted to build a startup, but college actually gave me the push I needed by showing me exactly what I didn't want to do. Sticking around just to write endless assignments, stress over internals, and give vivas felt completely useless to my actual goals.

That frustration led me to build Crestorflow.

It's a skill-to-opportunity platform but with a major twist. The idea is to bring in authentic creators-founders, builders and content creators who have actually done shit and have real expertise in domains like tech, development, marketing, growth, and design. They sell courses, cohorts, and mentorship to pass down real-world knowledge.

But here is the catch: it is not just another course platform, and it is definitely not a standard freelance platform. It is a proof of work marketplace. Learners get access to high-quality, practical content and after completing a course, they immediately build projects. Based entirely on those projects, they get connected with clients. You get hired for what you can actually build, not a meaningless certificate.

I really need some help and feedback from this community.

Is this a legit problem that you guys resonate with? What do you think could make a real difference in this space or are there any killer features that would make this stand out?

If you want to support or just check it out, I'd love for you to sign up for early access here: www.crestorflow.com.

Also, if any of you are currently stuck in that same college rut or facing this exact problem, shoot me a DM. Let's connect and make sure you get your roadmap figured out. Appreciate you all

Hey everyone, I'm Abdul Malik.

A year ago, I made the tough call to drop out of college to build my own startup. Since then, I've just been grinding to attending events, meeting founders, learning and building stuff from scratch.

Honestly, what pushed me to quit was realizing how outdated the system is. I was staring down a 10-year-old syllabus, worst placement cycles and the reality of paying lakhs just for a piece of paper that didn't even guarantee a job. It made zero sense. I always knew I wanted to build a startup, but college actually gave me the push I needed by showing me exactly what I didn't want to do. Sticking around just to write endless assignments, stress over internals, and give vivas felt completely useless to my actual goals.

That frustration led me to build Crestorflow.

It's a skill-to-opportunity platform but with a major twist. The idea is to bring in authentic creators-founders, builders and content creators who have actually done shit and have real expertise in domains like tech, development, marketing, growth, and design. They sell courses, cohorts, and mentorship to pass down real-world knowledge.

But here is the catch: it is not just another course platform, and it is definitely not a standard freelance platform. It is a proof of work marketplace. Learners get access to high-quality, practical content and after completing a course, they immediately build projects. Based entirely on those projects, they get connected with clients. You get hired for what you can actually build, not a meaningless certificate.

I really need some help and feedback from this community.

Is this a legit problem that you guys resonate with? What do you think could make a real difference in this space or are there any killer features that would make this stand out?

If you want to support or just check it out, I'd love for you to sign up for early access here: www.crestorflow.com.

Also, if any of you are currently stuck in that same college rut or facing this exact problem, shoot me a DM. Let's connect and make sure you get your roadmap figured out. Appreciate you all

Hey everyone, I’m Abdul Malik.

A year ago, I made the tough call to drop out of college to build my own startup. Since then, I’ve just been grinding to attending events, meeting founders, learning and building stuff from scratch.

Honestly, what pushed me to quit was realizing how outdated the system is. I was staring down a 10-year-old syllabus, worst placement cycles and the reality of paying lakhs just for a piece of paper that didn’t even guarantee a job. It made zero sense. I always knew I wanted to build a startup, but college actually gave me the push I needed by showing me exactly what I didn't want to do. Sticking around just to write endless assignments, stress over internals, and give vivas felt completely useless to my actual goals.

That frustration led me to build Crestorflow.

It’s a skill-to-opportunity platform but with a major twist. The idea is to bring in authentic creators—founders, builders and content creators who have actually done shit and have real expertise in domains like tech, development, marketing, growth, and design. They sell courses, cohorts, and mentorship to pass down real-world knowledge.

But here is the catch: it is not just another course platform, and it is definitely not a standard freelance platform. It is a proof of work marketplace. Learners get access to high-quality, practical content and after completing a course, they immediately build projects. Based entirely on those projects, they get connected with clients. You get hired for what you can actually build, not a meaningless certificate.

I really need some help and feedback from this community.

Is this a legit problem that you guys resonate with? What do you think could make a real difference in this space or are there any killer features that would make this stand out?

If you want to support or just check it out, I’d love for you to sign up for early access here: www.crestorflow.com.

Also, if any of you are currently stuck in that same college rut or facing this exact problem, shoot me a DM. Let’s connect and make sure you get your roadmap figured out. Appreciate you all!

I’ve been talking to a lot of creators lately, and almost all of them have the same massive bottleneck: they just leave a public @gmail address in their bio.

The result? Their inbox is a chaotic nightmare of fan mail, $50 lowball offers, and crypto scams. Meanwhile, the actual $5k sponsorship or high-value collaboration gets buried and missed.

​

I got tired of seeing people leave money on the table, so I spent the last few weeks building a "Digital Talent Manager" to replace the standard Link-in-Bio. It acts as a ruthless, 24/7 gatekeeper.

​

Here is exactly how I built it and the tech stack behind it.

​

The Concept

Instead of a static Linktree, the bio link opens a dynamic, dark-mode intake interface. It forces the person reaching out to qualify themselves into one of three buckets: Sponsorships, Collaborations, or Consulting.

The Backend Flow (The n8n Engine)

Once they hit submit, the webhook catches the data and routes it based on intent.

​

Path 1: Sponsorships (Catching the Money)

If a brand wants to sponsor a video, the form forces them to state their budget and give a corporate email.

The system extracts their domain and pings the Clearbit API to verify their company size and industry. (This filters out dropshipping/scam brands).

​

Path 2: Collaborations (Protecting Brand Equity)

If another creator wants to collaborate, the form asks for their primary social link.

An Apify node triggers, scrapes their YouTube/Insta, and pulls their exact subscriber count and engagement metrics.

​

Path 3: Consulting (Lead Gen)

Forces them to answer two specific qualification questions about their business revenue to ensure they can actually afford the creator's hourly rate.

​

The AI Triage (Claude 3.5 Sonnet)

All this enriched data gets passed to Claude 3.5 Sonnet. I prompted the AI to act as a strict talent manager.

Low Quality (Trash): If the brand has a $100 budget, or the "collaborator" has 12 subscribers, the AI scores it low. The system automatically sends a polite "Thanks, but not right now" email via Gmail API. The creator never even sees it.

VIP Deals: If a real brand with a $5k+ budget submits, the AI tags it as VIP. It bypasses the inbox entirely and fires a custom Slack or WhatsApp alert straight to the creator’s phone: “🚨 VIP Deal: $5k Sponsorship request from \[Company Name\].”

​

All pipeline data is automatically synced to an Airtable CRM so the creator can see their exact revenue pipeline at a glance.

​

The Tech Stack

Frontend: Framer / Next.js

Orchestration: n8n (Cloud)

AI: Anthropic Claude 3.5 Sonnet

Enrichment: Apify & Clearbit

Database: Airtable

​

I’m currently testing this with a few creators and the amount of inbox hours it saves is insane. It basically entirely automates the boundary-setting process.

I'm thinking about turning this into a productized service. If you're a creator, if you're facing this problem and found this solution helpful, DM LET'S TALK

I’ve been talking to a lot of creators lately, and almost all of them have the same massive bottleneck: they just leave a public @gmail address in their bio.

​

The result? Their inbox is a chaotic nightmare of fan mail, $50 lowball offers, and crypto scams. Meanwhile, the actual $5k sponsorship or high-value collaboration gets buried and missed.

​

​

I got tired of seeing people leave money on the table, so I spent the last few weeks building a "Digital Talent Manager" to replace the standard Link-in-Bio. It acts as a ruthless, 24/7 gatekeeper.

​

Here is exactly how I built it and the tech stack behind it.

​

​

**The Concept**

​

Instead of a static Linktree, the bio link opens a dynamic, dark-mode intake interface. It forces the person reaching out to qualify themselves into one of three buckets: Sponsorships, Collaborations, or Consulting.

​

The Backend Flow (The n8n Engine)

​

Once they hit submit, the webhook catches the data and routes it based on intent.

​

​

Path 1: Sponsorships (Catching the Money)

​

If a brand wants to sponsor a video, the form forces them to state their budget and give a corporate email.

​

The system extracts their domain and pings the Clearbit API to verify their company size and industry. (This filters out dropshipping/scam brands).

​

​

​

Path 2: Collaborations (Protecting Brand Equity)

​

If another creator wants to collaborate, the form asks for their primary social link.

​

An Apify node triggers, scrapes their YouTube/Insta, and pulls their exact subscriber count and engagement metrics.

​

​

​

Path 3: Consulting (Lead Gen)

​

Forces them to answer two specific qualification questions about their business revenue to ensure they can actually afford the creator's hourly rate.

​

​

​

The AI Triage (Claude 3.5 Sonnet)

​

All this enriched data gets passed to Claude 3.5 Sonnet. I prompted the AI to act as a strict talent manager.

​

Low Quality (Trash): If the brand has a $100 budget, or the "collaborator" has 12 subscribers, the AI scores it low. The system automatically sends a polite "Thanks, but not right now" email via Gmail API. The creator never even sees it.

​

VIP Deals: If a real brand with a $5k+ budget submits, the AI tags it as VIP. It bypasses the inbox entirely and fires a custom Slack or WhatsApp alert straight to the creator’s phone: “🚨 VIP Deal: $5k Sponsorship request from \[Company Name\].”

​

​

​

All pipeline data is automatically synced to an Airtable CRM so the creator can see their exact revenue pipeline at a glance.

​

​

​

The Tech Stack

​

Frontend: Framer / Next.js

​

Orchestration: n8n (Cloud)

​

AI: Anthropic Claude 3.5 Sonnet

​

Enrichment: Apify & Clearbit

​

Database: Airtable

​

I’m currently testing this with a few creators and the amount of inbox hours it saves is insane. It basically entirely automates the boundary-setting process.

​

I'm thinking about turning this into a productized service. If you're a creator, if you're facing this problem and found this solution helpful, DM LET'S TALK

I’ve been talking to a lot of creators lately, and almost all of them have the same massive bottleneck: they just leave a public @gmail address in their bio.

​The result? Their inbox is a chaotic nightmare of fan mail, $50 lowball offers, and crypto scams. Meanwhile, the actual $5k sponsorship or high-value collaboration gets buried and missed.

​

​I got tired of seeing people leave money on the table, so I spent the last few weeks building a "Digital Talent Manager" to replace the standard Link-in-Bio. It acts as a ruthless, 24/7 gatekeeper.

​

​Here is exactly how I built it and the tech stack behind it.

​

​The Concept

​Instead of a static Linktree, the bio link opens a dynamic, dark-mode intake interface. It forces the person reaching out to qualify themselves into one of three buckets: Sponsorships, Collaborations, or Consulting.

​The Backend Flow (The n8n Engine)

​Once they hit submit, the webhook catches the data and routes it based on intent.

​

​Path 1: Sponsorships (Catching the Money)

​If a brand wants to sponsor a video, the form forces them to state their budget and give a corporate email.

​The system extracts their domain and pings the Clearbit API to verify their company size and industry. (This filters out dropshipping/scam brands).

​

​Path 2: Collaborations (Protecting Brand Equity)

​If another creator wants to collaborate, the form asks for their primary social link.

​An Apify node triggers, scrapes their YouTube/Insta, and pulls their exact subscriber count and engagement metrics.

​

​Path 3: Consulting (Lead Gen)

​Forces them to answer two specific qualification questions about their business revenue to ensure they can actually afford the creator's hourly rate.

​

​The AI Triage (Claude 3.5 Sonnet)

​All this enriched data gets passed to Claude 3.5 Sonnet. I prompted the AI to act as a strict talent manager.

​Low Quality (Trash): If the brand has a $100 budget, or the "collaborator" has 12 subscribers, the AI scores it low. The system automatically sends a polite "Thanks, but not right now" email via Gmail API. The creator never even sees it.

​VIP Deals: If a real brand with a $5k+ budget submits, the AI tags it as VIP. It bypasses the inbox entirely and fires a custom Slack or WhatsApp alert straight to the creator’s phone: “🚨 VIP Deal: $5k Sponsorship request from [Company Name].”

​

​All pipeline data is automatically synced to an Airtable CRM so the creator can see their exact revenue pipeline at a glance.

​

​The Tech Stack

​Frontend: Framer / Next.js

​Orchestration: n8n (Cloud)

​AI: Anthropic Claude 3.5 Sonnet

​Enrichment: Apify & Clearbit

​Database: Airtable

​

​I’m currently testing this with a few creators and the amount of inbox hours it saves is insane. It basically entirely automates the boundary-setting process.

I'm thinking about turning this into a productized service. If you're a creator, if you're facing this problem and found this solution helpful, DM LET'S TALK

Client Requirements:

- Goal:

Generate qualified leads (digital nomads) and get them booked on demo calls.

- Product:

(Chrome extension, currently in open beta)

- Target Audience:

Digital nomads (remote workers, freelancers, travelers, indie hackers, etc.)

- Lead Sources:

1. Facebook → events, groups, pages, hashtags

2. Instagram → profiles, hashtags, creators

3. Reddit → communities/subreddits related to digital nomads

4. Web → blogs, niche communities, directories

- Data Required per Lead:

- Email address (high priority)

- Username / profile link (platform-specific)

- Optional: website, bio, niche relevance

- Workflow Expectations:

- Scrape / collect leads from multiple platforms

- Enrich data (find emails, extract useful info)

- Filter and qualify leads (remove irrelevant/low-quality)

- Store clean data in a structured format (Sheets/CRM)

- Send personalized outreach (email primarily)

- Automate follow-ups

- Track responses and demo bookings

- Tech Stack Preference:

- n8n for automation

- HubSpot CRM for managing leads + follow-ups

- Key Concern:

Email deliverability

- Avoid landing in spam

- Maintain domain reputation

- Proper email warm-up strategy

- Safe sending limits and practices

Main Questions:

- Best way to reliably source leads from IG/Reddit/Facebook without getting blocked?

- How would you structure enrichment (especially email finding) at scale?

- What’s the safest outreach + warm-up setup for a new domain?

- Any tools/workflows you’d strongly recommend or avoid?

Would appreciate any insights from people who’ve built similar systems.

I used to spend way too much time every week just doing lead gen.

Like literally:

scraping random lists, cleaning them up, trying to find emails, writing the same outreach again and again… and then forgetting to follow up half the time.

It wasn’t even hard work, just repetitive and annoying.

So over the past few weeks I tried building a workflow to handle most of it.

Right now it:

– pulls leads based on niche/location (been testing with a few different ones)

– filters out useless data so I’m not emailing junk

– finds + validates emails (still tweaking this part)

– writes a first line based on their profile so it doesn’t feel copy-paste

– sends emails + does follow-ups automatically

– pushes everything into a CRM so I’m not tracking things in random sheets

It’s not perfect yet (deliverability is something I’m being careful with), but it’s already saving me a lot of time and makes outreach way more consistent.

I’m still refining this and trying it across different use cases

if someone who’s dealing with the same “manual lead gen grind,” I’d be open to sharing what I’ve built or even testing it on your workflow to see if it actually helps.

How are you guys handling the entire outreach part, would love to know.

I’m currently in the middle of a 30-day sprint, splitting my time between coding my startup's MVP and launching a workflow automation freelance business out of Bengaluru.

​Today I finished building what I think is my flagship freelance offering: a fully autonomous outbound lead generation machine using n8n.

​I want to gut-check the architecture with this community and get some raw feedback on how to price it for B2B clients.

​The Problem I'm Solving:

​Most B2B agencies and founders bleed money and time on outbound:

​Software Bloat: They are stringing together expensive stacks (Apollo + Lemlist + Clay + Zapier) that easily run $500+/month.

​Human Error: SDRs miss follow-ups, fail to personalize emails adequately at scale, and waste hours manually updating CRMs.

​Domain Burn: Hitting spam traps because of poor data validation.

​The n8n Solution (The Architecture):

​I built a single workflow that acts as a full-stack sales rep. The only manual input required is a text prompt defining the target (e.g., "SaaS Founders in London").

​Here is the exact flow:

​Global Scrape: Hunts for target data based on the niche/location inputs.

​Enrichment & Validation: Finds the actual decision-maker emails and bounces them against a verification API to protect domain health.

​Filtering & Scoring: Drops the junk leads and scores the valid ones.

​AI Personalization: Passes the enriched data to an LLM node to write a highly contextual, non-robotic cold email.

​Execution & Wait: Sends the first email. Then, an automated delay node holds the prospect for exactly 3 days.

​Contextual Follow-up: If no reply is detected, it generates and sends a follow-up.

​CRM Sync: Pushes every action, score, and status into a live Google Sheet.

​My Questions for You:

​1. How should I price this?

​2. What are the blind spots in this workflow?

For those of you who have built complex outbound engines, what edge cases am I missing?

​Appreciate any ruthless feedback you have.

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