Email0+mailboxes0delivered
0%reply rate
Sequence
- 1Intro
- 2Follow-ups
- Every inbox warmed up and reputation-scored; below the bar it sends less, automatically
- Warm-up ≥90% gates send volume, with daily limits enforced per inbox
Meetings get booked. Most aren't qualified. 9+ years in growth taught me why. Now I build the system that fixes it.
A founder, a marketer and an engineer see three different problems in one funnel. I think in all three, so I find the one that matters. Outbound is one of them, and the system below runs in production.
Book a free teardown
You'll leave knowing what to automate first
Intent signal
Capture
≡
Screen
Profile Enrichment
Person Fit Check
Company Enrich
Company Score
@
Email Enrichment
SMTP
Email Infra
Write Email Copy
SmartLead
LinkedIn Infra
Write LinkedIn Copy
HeyReach
%
Analyze
↻
Learn
◆
Plan
Health Check
Self-healing · always on
- 0+/month
- Qualified meetings
- 0
- Outbound pipelines
- 0%
- Email reply rate
- 0%
- LinkedIn reply rate
- 0%
- LinkedIn acceptance
How this becomes 400+ qualified meetings a month
That's the pipeline above. It's one of five, and each one ends the same way: a real meeting on someone's calendar.
The one that carries most of the volume
Everything below belongs to a single pipeline, one full cycle: Fresh Intent, the loop you just watched play out.
Someone likes a post from a person our buyers follow. Thirteen stages later, they've become a qualified lead sitting in a campaign, with personalized copy written for them.
Before any enrichment or further processing, we run the checks that don't cost anything first: the job title we already have, then fit, then a company score. Only once all three agree does the record move on to enrichment and email lookup.
It runs every day at a scheduled time, working through each stage fully before moving to the next. If something breaks mid-run, we get an instant notification on Discord, so we can fix it right away.
Sourcing, which fans out
Accounts watched0
Posts judged0
Engagers captured0
Qualifying, which collapses
Headline screened0
Profile enriched0
Person fits0
Company enriched0
Company scored0
Email found0
Delivery, which splits by channel
Every message is written off the prospect's most recent LinkedIn post, their company and them, then tailored to the channel it goes out on.
EmailLinkedIn0+accounts0delivered
0%connection accepted
0%reply rate
Sequence
- 1Connection note
- 2Intro
- 3Follow-up 1
- 4Follow-up 2
- 5Follow-up 3
- No warm-up, just safe daily connection and message limits per account
- Each account's profile is matched to the target's geography
- Campaigns are split by region so the sending profile always fits who it's reaching
Four more signals, one outcome
The pipeline above is one of five. A cold list that never got a reply. A second try on a different channel. A company that just raised money. A phone call instead of an inbox. Each one starts differently, but they share the same qualification, the same delivery, and the same outcome: a meeting that actually happens.
Fresh Intent
Old Intent Data
Email to LinkedIn
AI SDR: Funding
Qualify
CRM
Call or no-call
Retell AI
EmailLinkedIn
LinkedInMeeting booked
400+/monthFresh Intent
Old Intent Data
Email to LinkedIn
AI SDR: Funding
Qualify
CRM
Call or no-call
Retell AI
EmailLinkedIn
LinkedInMeeting booked
400+/monthHealth Check: every stage above, watchedAcross all pipelines
Same five pipelines. Here's what they added up to.
- 0
- Campaigns run
- Across email and LinkedIn
- 0
- Pipeline runs recorded
- Every run logged, funnelled and reported on
Read once from production, July 2026. Totals only, nothing live.
What keeps it running
That dashed line around the diagram above is this: every one of these five pipelines reports into the same place, a Discord channel that reads the logs, classifies what broke as Critical, Warning, or Info, and says why, an API failing is a different problem than a bad field mapping. Nothing fixes itself. I decide what's actually worth fixing, open a GitHub issue for it, and that's what ships. The same channel also reads straight from the database for the numbers behind daily, weekly and monthly reports, so I know where a campaign stands against target early enough to act on it.
Read logsClassifyDiscordGitHub
The self-healing loop
Each morning, it reads the last 24 hours, works out what went wrong and why, and posts the findings to Discord. Once I approve a fix, it opens the GitHub issue and ships it.
Email infrastructure
Cold email only works while the mailboxes stay healthy. This keeps an eye on all of them and quietly retires the ones that aren't.
PostgresThe operations console
Live row counts across the whole database, conversion at every stage, and campaign performance by channel. When a number moves the wrong way, I can see exactly which stage caused it.
What it's built from
Orchestration
0cloud tasks, 14 crons
Every stage finishes its own queue before the next starts, so a crash costs time, never correctness.
Data layer
0tables, 2.5M cached lookups
Cache-first lookups keep enrichment spend flat as volume grows: a repeat profile costs nothing.
LLM layer
0typed functions
Every model call returns structured data, not prose, so every result is consistent and easy to act on.
Email waterfall
0finders, then MX verify
Three finders, tried in cost order, first hit wins. Then every address is verified before it reaches a campaign.
Delivery and infra
≥0%warm-up gates send volume
Every mailbox is scored on health; one that drops below the bar sends less, automatically, before it can hurt the domain.
Self-healing
Dailylogs reviewed, every failure classified
Every failure is read from the logs, classified Critical, Warning, or Info, and flagged on Discord with the evidence behind it. Nothing fixes itself. I decide what's worth a GitHub issue and ship the fix myself.
What would this look like on your pipeline?
Most of what's above started as somebody's manual Tuesday. If you can describe the version of that you're living with, I can usually tell you which part is worth automating first.
What I build with
- Build
- TypeScriptNode.jsPythonPostgreSQLREST APIsBashGitHub Actions
- AI systems
- Claude CodeCodexGPTBAMLPrompt engineeringAgentic workflowsCustom plugins & skills
- Orchestration
- Trigger.devn8nRetell AICron schedulingQueue drainingObservability
- GTM infrastructure
- Outbound pipelinesLead enrichmentICP filteringEmail deliverabilityCRM automationHubSpotSmartLeadHeyReach
TypeScript
Node.js
Python
Bash
GitHub Actions
Claude Code
Trigger.devA stalled funnel always has three plausible explanations.
I check all three before I touch anything. The first two usually come back clean, and that is exactly what keeps the third one hidden.
The sequences send on time every single day. The meeting count has not moved in months.
Before I touch anything, I run it through three heads.
Think like a founder
I'd check: are we reaching enough people?
Volume is fine. The list is big enough and the sends go out every day.
Think like a marketer
I'd check: are we aimed at the right people, and is the copy landing?
The ICP is defined right and the reply rate holds. On paper this should be working.
Think like an engineer
I'd check: is the system actually contacting the people we defined?
It is not. The fit check passes anyone close enough, so a big share of every send never matched the ICP at all.
The ICP was right. The filter enforcing it was not.
The targeting was correct. The check deciding who got contacted was not, so a share of every send went to people who never matched it. They replied politely and went nowhere, which is why the reply rate looked fine. The fit check now runs on the real criteria before anyone is contacted, cheapest checks first. Same list, aimed at the people it was always meant for.
Two of those checks came back clean, and that's exactly why the third stayed hidden. It wasn't a mistake on anyone's part: a founder and a marketer both read the dashboards, and the dashboards looked healthy. This only shows up when you look at the records the system actually acted on, and that's the lens I bring to every funnel I build.
9 years in paid media, then I started building.
Up to €1.5M a month at GroupM. Running growth at that scale shows you which decisions actually need a person, and which ones are coordination a system does better.
- 2017 — 20200+ leadsIndia · UAETrackingOptimizeControlAutomate
Cbetter Consultancy
SEO & Media Buying Specialist
The fundamentals, learned end to end: run the ad, track it, improve the page.
Brands
- 2021 — 2024₹0.0Cr / moIndia · 2–3× MoM growthTrackingOptimizeControlAutomate
Social Beat
Lead, Digital Media
The full stack under one roof: paid, commerce, tracking, dashboards, CRO.
Brands
- 2024 — 2025€0.0M / moEurope · APACTrackingOptimizeControlAutomate
WPP · GroupM Nexus Global
Manager, Paid Media
Scale with discipline: hold a consistent ROAS at €1.5M a month, watch everything, never let performance slip.
Brands
- 2025 — now0 pipelinesAI AutomationTrackingOptimizeControlAutomate
Qubit Capital
AI Growth Systems Engineer
9 years of judgment, turned into systems that run themselves. The manual monitoring became self-healing.
Four acquisition pipelines in production. Outbound that runs without a person watching it. 9 years of judgment, encoded as systems
Other things I've built.
Some shipped and in use, some in progress, some scaffolded with the research done and the build not started. Labelled honestly, newest proof first.
Shipped
Running and in useOpen live
Your Flow State
Passion project
Audio-reactive live visuals that run in a browser, built for DJs, VJs and the venues booking them. It listens to whatever is playing and drives the visual off the sound itself, so nobody is cueing clips by hand in the middle of a set.
JavaScript · WebGL · Web Audio · Storybook
Paalthi
Built for a café
Expense and sales tracking for a café, on Supabase and Vercel. No build step, plain HTML and JS, with three small serverless functions for the one thing that needs elevated privileges.
Supabase · Vercel · Vanilla JS
Mhari Ops Console
Client internal tool
Customer feedback capture and an admin dashboard for a jewellery brand, backed by Shopify and running on Vercel serverless. Tracks which review links went out, which got opened, and which turned into an actual rating.
JavaScript · Shopify · Vercel
Outbound Builder
Claude Code plugin
A plugin that packages everything I learned building the Intent Engine into something any Claude Code session can use: 24 implementation docs, 25 code templates, 8 skills and an architecture agent.
TypeScript · Claude Code
CodeHealth Check
Claude Code plugin
The self-healing loop, pulled out of Qubit's codebase and made generic. Collects health signals from any system, scores it 0-100, fingerprints and dedupes issues, discusses them in a chat channel, and on approval opens GitHub issues and runs safety-gated repairs.
TypeScript · PostgreSQL · Discord · GitHub
CodeBuilding
In progress right nowTrade for All
Side product
Export compliance and tariff research for small manufacturers.
Performance Marketing System
In progress
The paid media half of the same idea. 9 years of campaign judgement, encoded as a system that runs accounts rather than reports on them.
Idea
Scaffolded or researched, not builtAll-in-One DJ
Visual prototype
One tool for the whole DJ prep workflow instead of four that don't talk to each other. Currently at the stage of working out how it should look and behave.
The ideology
Time is a gift from the universe.
The present is the only part of it we are ever handed. Music, photographs, training, the systems I build: it is all the same practice, and all of it is me trying to stay inside the moment I am in.
Music
Since I was two years old.
A track is scattered sound until you hear what belongs with what. Learn to hear that once and you never stop hearing it, in a mix or in a funnel that has quietly stopped working.
Abstract photography
Where structure has nowhere to hide.
Take the subject away and only the pattern is left. The same shapes sit in a crack in a wall and in a galaxy. Micro and macro, one story told at two distances.
Calisthenics
No machines. Weight, control, breath.
Closer to meditation than to training. You cannot move well and be somewhere else at the same time. It is where I go to get quiet.
Nothing published. That is rather the point.
Recent frames
Every decision you will ever make gets made in the present. That is the whole thing.
Tell me what you're building.
I take on a small number of consulting projects at a time.
Tell me roughly what your outbound looks like now and where it's costing you time. I'll come back with what I'd change first, whether or not it turns into work.
Book a free teardown
30 minutes. Bring how your outbound runs today, I'll show you which stage is leaking and what I'd fix first, whether or not we end up working together.
WhatsApp
+91 96025 84479FastestEmail
kumar.ankit4479@gmail.comBest for detailLinkedIn
in/ankit4479GitHub
ankit4479- Based
- India, Remote
- Working
- Consulting and freelance
- Studied
- B.Tech, Information Technology JECRC University, Jaipur, 2013-2017Digital Guru Expert (Black Belt) Google