
director of social @serotonin_hq
BOM/DEL
Joined December 2013
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esha retweeted
I am so proud to have been able to lead anincredible group of Emcees for Devcon VII this year in India! ♥️
- 30 Emcees!
- From > 20 different countries!
- Allocated across 4 days of Devcon!
- Emceeing for 7 different stages!
- For 100s of speaker sessions!
The BIGGEST and most DIVERSE group of Emcees for any single crypto conference in the world!
Coming together to become the GLUE that holds Devcon together 🔥
From technical talks, to intense lightning stages, to hands on workshops where anything could happen!
Theese Emcees conducted themselves with grace and professionalism! Thank you all for trusting me as your Lead and becoming the EMCEES OF DEVCON!
@abena_eth @aledecentral1 @alexanderlee314 @buzea200 @binji_x @0xChiranjeev @chrishobcroft @d_gusakov @DmytroMatviiv @mijovic988 @eshpvt @dutraguss @huvoliveira @JamesNewell @jiminleex @JorkLeonhardt @jgattermayer @kirkthebaird @louviq @MartinBreiten @MissPurrple_ @OfirEliasi @ottokekalainen @pranaytej @robdotrego @zemse_ @solangegueiros @tech_mingler @yq_acc @zaryab_eth @EFDevcon
esha retweeted
GTM larping is wild. Work for a startup that raises $100M, spend the money by hiring 20,000 UGC creators w AI, drive a lot of views, get $0.60 back for every $1 spent, claim victory, then go to another startup and repeat?
Wrapped up my first-ever talk at @EFDevcon today! A summary:
→ We've spent years making protocols censorship resistant. But a permissionless future also needs permissionless distribution and discovery, because something can be impossible to delete and still easy to bury.
→ Between your protocol and your users sit three layers: discovery, distribution and the app itself.
→ The obvious response to censorship is fragmentation. Distribution will probably fragment the way DeFi did, into lots of small pockets that each have their own operator. The cost is community.
→ Build around the gatekeepers. At what points in your distribution and discovery can a centralized power intervene and restrict your users from using your product? Identify those and find decentralized workarounds.
Don’t miss @eshpvt speaking RIGHT NOW at @EFDevcon!
Learn how to avoid a hidden centralization risk that isn’t part of your tech stack: its distribution
Governments and other actors turning off social media, for example
Streaming here youtube.com/watch?v=WIMPzJTf…
esha retweeted
if i send you this pic it means im monitoring the situation as it develops and will be keeping you in the loop as information is gathered
esha retweeted
about to reach new levels of monitoring the situation that the world has never seen before this evening
Will be at @UnchainedSummit on Thursday!
Making complex crypto and fintech products easier to understand is key to connecting innovation with the people who use it.
Esha Datanwala, Director of Social at @serotonin_hq, joins the Unchained Summit India speaker lineup, bringing experience in strategic storytelling and communication across the digital asset ecosystem.
Her work spans stablecoins, yield protocols, consumer payments and emerging technologies, translating complex products into clear narratives that help audiences understand their value.
📍 Courtyard by Marriott, Mumbai | 5–6 November 2026
Get your Unchained Summit India pass for US$ 199. Book now: unchainedsummit.com/india.
#AnEventbyAeternum #UnchainedSummit #EshaDatanwala #Serotonin #Web3
“babe why did you match with me?"
> sends claude’s decision log
I automated Hinge using Claude Code, a spare Android phone, and a few markdown files.
Getting around 20–25 matches/day, and almost 60% of them are people I would've actually swiped right on myself.
I've been experimenting with this setup for a while now.
Here's a detailed breakdown of how I built it, how it works, and a few things I learned about optimizing my own Hinge profile.
1. The setup is pretty basic
- Took a spare Android phone and installed Hinge.
- Connected it to my MacBook using ADB.
- Connected Claude Code to the phone.
- Gave Claude a prompt with my preferences, deal breakers, non-negotiables, locations, etc.
That's pretty much all the hardware you need.
Also, please don't over-engineer this. Be smart about it.
I know some of you are already thinking about replacing the Android phone with a cloud emulator or some complicated setup. I wouldn't recommend it. You're just increasing the chances of getting flagged or banned.
Keep things simple. There's no point building an entire infrastructure around something that was supposed to save you 45 minutes a day lol.
2. Giving Claude enough context about me
I already have a personality.md file that Claude keeps updating whenever I use it.
It has almost everything about me. Places I've travelled, people I've met, experiences I've had, things that went wrong, things I liked, how I generally think, my preferences, etc.
It's obviously not 100% accurate, but it has a pretty decent understanding of who I am.
I also gave it my entire Hinge profile, including all my photos, prompts, and preferences.
So now, when Claude sees someone's profile, it can actually evaluate whether I'd be interested in that person instead of just blindly swiping.
3. How the actual automation works
I keep travelling between three cities in India, so I've set up three scheduled sessions.
Morning: City 1
Afternoon: City 2
Evening: City 3
Each session runs in batches, with fixed intervals and frequent breaks.
Whenever a profile opens:
Claude reads the basic details first.
If there's an obvious deal breaker, it skips immediately.
Otherwise, it goes through all the photos, prompts, and polls.
Cross-references everything with my preferences.
Decides whether to like or skip.
It's not perfect, but the decisions are surprisingly close to what I would've made myself.
4. The interesting part is how it comments on profiles
I spent some time going through Instagram reels and comment sections about Hinge openers and replies.
Collected around 150 comments that seemed to work well and were also somewhat aligned with my personality.
Put them all into a comments.md file.
Now, whenever Claude decides to like someone's profile, it uses those comments as references.
It doesn't just pick one and paste it.
It reads the entire profile and then writes something specific to that person.
For example, if it's commenting on her first prompt, it might reference something mentioned in her third prompt or one of her photos.
So the comment actually has context instead of being a random pickup line that could be sent to 100 different people.
I think this is one of the reasons the setup has been working reasonably well.
5. Everything gets tracked in a Google Sheet
For every profile, Claude logs:
- Profile details
- Whether it liked or skipped
- Why it made that decision
- What comment it sent
- Whether we eventually matched
The sheet also gets updated whenever a match happens.
I occasionally go through the sheet myself to check how accurate the decisions are.
That's where the ~60% number comes from. Around 60% of the matches are people I would've personally swiped right on.
There's still a lot of room for improvement, but that's not a bad hit rate for something running on autopilot.
6. Something else I tried: optimizing my own Hinge profile
This was actually quite interesting.
Since Claude already has my personality.md, I asked it to analyze my current Hinge profile.
Everything from photos and their sequence to prompts, relationship intentions, and the little descriptions you can add below certain fields.
I also asked it to go through research around dating apps, published studies, and insights shared by people who've worked on products like Hinge.
There are so many small things you generally don't think about.
For example, one claim I came across was that having a black-and-white photo among your regular coloured photos can significantly improve engagement.
The reasoning is that it breaks the visual pattern when someone is scrolling, which might get you a couple of extra seconds of attention.
I haven't independently verified the numbers behind that claim, but it was an interesting thing to test.
Another example is how you describe what you're looking for. Most people just select something like "short-term, open to long-term" and leave it there.
But you can add a small description below it, which gives you another opportunity to communicate what you actually want.
Small things, but they add up.
I've been experimenting with different photo sequences, prompts, and descriptions to see what changes the match rate.
It's basically A/B testing a dating profile lol.
7. Where things stand now
The setup has been running for a while.
Getting around 20–25 matches a day, with roughly 60% matching my own preferences.
Earlier, I'd spend at least 45 minutes a day scrolling through Hinge. With this experiment, the manual effort is almost negligible.
One thing I found interesting is how much difference having proper personal context makes.
Without my personality.md and comments.md, Claude would probably just be another bot sending generic pickup lines.
With those files, it can make decisions and write comments that are much closer to how I'd actually do it.
Again, this was just a fun experiment to see how far I could take Claude Code and phone automation, not something I'm actively using as my regular dating approach. There are obvious questions around authenticity and dating-app rules too.
I've documented the entire setup, including the prompts and files.
If anyone wants the setup file, let me know.
Happy to share it.
Thank me later for saving you a few hours every week.
Now go get back to work :)
“Taking things even further, “curation” isn’t a surface act of appreciation or collection, which is how people often referred to the term in previous technology waves. Curation now involves going deeper, further back, and to the lowest levels of the stack: the bare-metal layer, the raw materials in the creation.”


























