Remote: Yes (experienced with US/EU hours and async workflows)

Willing to relocate: yes, within SEA

Technologies: Python, SQL, n8n automations, PostHog, Google Tag Manager (GTM), Google Analytics 4 (GA4), Shopify Web Pixels, Technical SEO, AEO/GEO indexing schemas, HTML/CSS/Tailwind

Résumé/CV: https://lightyoruichi.com/work (Password: askhn182)

Email: harinder.mke@gmail.com

LinkedIn: https://www.linkedin.com/in/lightyoruichi

GTM/Growth Operator & Fractional CMO. I build data-driven marketing systems and organic acquisition engines, transitioning startups from paid ad dependency to compounding organic channels. I like solving hard marketing problems.

What I've done for:

- CPA firm, I built a technical search and AEO pipeline that replaced a 25,000 USD per month paid ad spend, scaling organic traffic from zero to 210,000 monthly visits and increasing leads by 10x.

- For DTC-ecom brand, I restructured their checkout funnel, cart scripts, and localization layouts, boosting site-wide conversion rate by 250% and generating >1 million USD in annual revenue.

- For a frontier AI lab, I conducted 24 developer ICP interviews to validate commercial use cases and secured 2 enterprise design partners before we built a user interface.

- I designed an organic acquisition loop on Reddit that generated 300 active signups in 30 days with zero budget.

- For another DTC-ecom brand, I managed creator marketing campaigns and a performance marketing budget of 2.5 million USD per month across Southeast Asia.

I write technical content, build webhook-driven attribution pipelines, and set up analytics dashboards (PostHog, GTM) to make marketing performance transparent. I'm basically a one-man marketing team.

Seeking contract, fractional, or full-time roles in growth engineering, technical product marketing, or growth operations.

Comments URL: https://news.ycombinator.com/item?id=48656098

Points: 4

# Comments: 0

  - Wrong ICP, "early stage founders" is not a buyer. They don't have enough email spam problems. Later-stage founders who do already have an EA.

  - You're assuming the pain. People generally don't have problem with email scheduling. And if someone were truly spending 6+ hours a week on it, they would have already delegated.

  - The messaging framing hurts you. The moment Persona is compared to a human EA, you lose on judgment, context, and trust.

  - Narrow to a pathological edge case. One role, one moment, one acute pain.

  - Reframe away from scheduling. Don’t sell logistics or efficiency. Sell control. This is a way more powerful messaging instead.

  - Stop outbound. Insert parasitically into their workflow. Live where the pain already exists. Gmail plugins, CRM edges, investor update workflows. Be an appendage, not a destination.

  - Accept that this may not be a standalone company. It may only survive as a feature inside a larger assistant or email client.

Remote: Yes (full-remote only)

Willing to relocate: No

Technologies: React, Node.js, Python, PHP, SQL | GA4, Mixpanel, PostHog | HubSpot, n8n, Zapier, Clay | Meta/Google Ads, SEMrush, Ahrefs

Résumé/CV: https://dub.sh/2L9ocQb

Email: hari@mimrgrowthlab.com

LinkedIn: https://www.linkedin.com/in/lightyoruichi/

I go deep on SEO/AEO (including technical SEO + LLM optimization), funnel optimization, marketing automation, and analytics infrastructure. I write code to solve problems—landing pages, event tracking, conversion APIs, dashboards, whatever moves the needle.

Looking for: Growth roles at early-stage SaaS (pre-seed to Series A) where I can own the full funnel and build systems from scratch.

long story short: i built a system that scrapes a company’s site, profiles, press, and anything else it can find online, then runs it through a multi-model prompt engine i wrote from scratch (multiple LLMs chained together with custom logic). the workflow is split into three parts: crawl, process, synthesize.

output comes in markdown. all signal, no bs. useful for GTM, growth, competitor analysis, product gaps, strategic blindspots, that kind of thing.

i’ve been stress testing it on real companies. just pushed 2 sample reports to GitHub if you wanna peek:

- Grab (SEA unicorn) - LemmyHomes (early-stage Malaysian proptech)

→ https://github.com/lightyoruichi/numen-output

not selling it as a product (yet). backend still in dev. just doing reports manually for now while testing edge cases/validating if anyone wants this at all lol.

note: it’s not fully automated. i use the system to generate raw analysis, then apply human input to reframe, expand, or clean up weak insights. think of it like pairing with an AI researcher who works fast but lacks nuance/context, you still need a strategist to shape the output. there's tons more feature but at the core this is it.

happy to run one or two more this week if anyone wants a teardown. not free though (token cost’s brutal lol). DM if interested.

http://www.speedtest.net/my-result/3185041626

Kuala Lumpur, Malaysia Download: 1.33Mbps Upload: 0.53Mbps

It's around RM140 = 40++USD per month.

And ironically, Raytheon's scientist was the dude who invented microwave.

Edit: Found this post from Feb 27th. About X-Keyscore, http://www.nowtheendbegins.com/blog/?tag=xkeyscore and the interesting snippet.

What happens next looks like a 21st-century data assembly line. At the NSA’s headquarters in Fort Meade, Maryland, a program called Xkeyscore processes all intercepted electronic signals before sending them to different “production lines” that deal with specific issues. Here, we find another array of code names.

Pinwale is the main NSA database for recorded signals intercepts, the authors report. Within it, there are various keyword compartments, which the NSA calls “selectors.” Metadata (things like the “To” and “From” field on an e-mail) is stored in a database called Marina. It generally stays there for five years. In a database called Maui there is “finished reporting,” the transcripts and analysis of calls. (Metadata never goes here, the authors found.)

As all this is happening, there are dozens of other NSA signals activity lines, called SIGADS, processing data. There’s Anchory, an all-source database for communications intelligence; Homebase, which lets NSA analysts coordinate their searches based on priorities set by the Director of National Intelligence; Airgap, which deals with missions that are a priority for the Department of Defense; Wrangler, an electronic intelligence line; Tinman, which handles air warning and surveillance; and more.

Lest you get confused by this swirl of code names and acronyms, keep this image in mind of the NSA as a data-analysis factory. Based on my own reporting, the agency is collecting so much information every day that without a regimented, factory-like system, analysts would never have the chance to look at it all. Indeed, they don’t analyze much of it. Computers handle a chunk, but a lot of information remains stored for future analysis.

http://makespace.my

http://lightyoruichi.tumblr.com/post/40565014985/quoras-new-...