Nostr notes by rajesh

cutting a nat bill, the order matters more than any single fix, ...

2026-07-09T09:37:02Z

cutting a nat bill, the order matters more than any single fix, because the cheap no-downside moves capture most of the money.

s3 + dynamodb gateway endpoints — free, one route-table edit. start here.
interface endpoints for ecr and logs — $0.01/GB, under a quarter of nat's rate. cheap, but do the per-service math.
cross-AZ cleanup, and the honest question of whether the subnet needs nat at all.
fck-nat — real savings, but no default failover and a patching burden. last resort.

most teams never get past step two.

#aws #infrastructure

https://rajesh.medampudi.com/blog/aws-nat-gateway-hidden-tax

the most wasteful line on a mid-size AWS bill is the one with no ...

2026-06-26T17:37:03Z

the most wasteful line on a mid-size AWS bill is the one with no resource page: data transfer.

the NAT gateway is the worst of it. $0.045/GB just to process traffic — and most teams route S3 + package pulls straight through it. a VPC gateway endpoint carries that same traffic for $0. one route-table edit.

i check this on every account. it's almost always there.

https://rajesh.medampudi.com/blog/audit-50k-aws-bill

the cloud bill is the only production number most teams don't ...

2026-06-26T09:37:02Z

the cloud bill is the only production number most teams don't own until it's already a fire.

engineering owns latency. finance owns the invoice. nobody owns the gap — and a fifth to a third of cloud spend dies in it.

stop treating the bill as an accounting artifact. treat it as a product metric: cost per request, per tenant, per feature, on the same dashboard as latency. we already run every other signal this way. cost is the one we still run like a 1990s expense report.

https://rajesh.medampudi.com/blog/infra-bill-as-product-metric

for ec2 in 2026 the reserved instance is the legacy choice, and ...

2026-06-25T17:37:02Z

for ec2 in 2026 the reserved instance is the legacy choice, and most people are still running the old rule in their head.

aws's own comparison: compute SP up to 66% across any family + region + fargate + lambda. ec2 instance SP up to 72% in one family. convertible RI 66% with a manual exchange. standard RI 72% but locked.

at every tier the savings plan matches the rate and beats the flexibility. same rate, less to manage. that's the whole argument.

https://rajesh.medampudi.com/blog/ri-vs-savings-plans

aws nat gateway charges you twice for the same packet. once at ...

2026-06-25T09:37:02Z

aws nat gateway charges you twice for the same packet. once at $0.045/hr just to exist (~$33/mo per gateway), and again $0.045 for every gigabyte it moves — in and out, on top of normal data transfer.

the hourly fee is visible so nobody worries about it. the per-GB fee is the one that quietly grows, because it rides on traffic you never watch — container pulls, package installs, s3 reads from private subnets.

#aws #infrastructure

https://rajesh.medampudi.com/blog/aws-nat-gateway-hidden-tax

lean infrastructure is four decisions, read top to bottom: cut ...

2026-06-24T17:37:02Z

lean infrastructure is four decisions, read top to bottom: cut the waste, own past your break-even, observe it cheaply, don't over-staff.

none of them is a technology. it's a posture — pay for what genuinely buys you something, refuse to pay for what doesn't. cut what's wasted, own what's worth owning, see everything, staff for the real load. that's the whole thing.

https://rajesh.medampudi.com/blog/what-lean-infrastructure-means

at 6 TB of telemetry a day, self-hosted grafana LGTM ran our ...

2026-06-24T09:37:02Z

at 6 TB of telemetry a day, self-hosted grafana LGTM ran our whole observability platform for ~$15-18K/mo. datadog at the same volume would've been ~$120K. that's 85% less, same telemetry, same scale.

and it gets worse over time — per-GB pricing and compute+storage scale on different curves, so the gap widens as you grow. datadog isn't a bad tool. you're just renting a meter that bills you more every time your product succeeds. model your bill at 5x volume before you sign, not after.

#observability #selfhosting #grafana

https://rajesh.medampudi.com/blog/observability-cost-kill

aws nat gateway charges you twice for the same packet. once at ...

2026-06-22T22:37:02Z

aws nat gateway charges you twice for the same packet. once at $0.045/hr just to exist (~$33/mo per gateway), and again $0.045 for every gigabyte it moves.

the hourly fee is visible so nobody worries about it. the per-GB fee is the one that quietly grows, because it rides on traffic you never watch — docker pulls, apt installs, s3 reads from private subnets.

open cost explorer, group by usage type, look at NatGateway-Bytes. that's the number to chase.

#aws #infrastructure #cloudcost #devops

at 6 TB of telemetry a day, self-hosted grafana LGTM ran our ...

2026-06-22T06:00:01Z

at 6 TB of telemetry a day, self-hosted grafana LGTM ran our whole observability platform for ~$15-18K/mo. datadog at the same volume would've been ~$120K. an 85% cut.

datadog isn't a bad tool. the problem is you're renting something you could own, on a meter that bills you more every time your product succeeds. per-GB pricing is a tax on growth. model your bill at 5x volume before you sign, not after.

#observability #selfhosting #infrastructure

True that.

2026-05-10T11:55:06Z

In reply to nevent1q…htah
_________________________

True that.

Nostr event nevent1qqsq6uzz0zf6gnujau7zvwftq4ed22u5587sjyfkafxtzr932h3xy2szyza3gua5c9lkn8wq907z0jnp65htdz7hu7rsfxdkens0scfyvu4ukj8xqgm

2026-04-08T08:26:58Z

New blog post: How We Avoided $120K/Month in Observability Costs

Our Datadog bill was $40K/mo and headed to $120K as we scaled. We replaced it with self-hosted Grafana LGTM stack for $15-18K/mo.

The real lesson: per-GB SaaS pricing is a trap at scale. We went from 1TB/day to 6TB/day and our self-hosted costs barely moved. Datadog would have gone from $40K to $120K+.

Self-hosting isn't just about sovereignty — sometimes the economics leave you no choice.

Full write-up with architecture and timeline:
https://rajesh.medampudi.com/blog/how-we-saved-120k-per-month

#aws #infrastructure #selfhosting #observability #costoptimization

So only bitcoin cannot be the strategy and yearly verification ...

2026-04-05T02:21:44Z

In reply to nevent1q…qreq
_________________________

So only bitcoin cannot be the strategy and yearly verification and instruction set is the one other step.

My Bitcoin self-custody architecture: Layer 1: Hardware wallet ...

2026-04-04T17:28:28Z

My Bitcoin self-custody architecture:

Layer 1: Hardware wallet — keys never touch the internet
Layer 2: 2-of-3 multisig — no single point of failure, geographically distributed
Layer 3: Own node — full verification, no third-party trust

Same engineering principles as infrastructure architecture:

Eliminate single points of failure
Own your data
Verify, don't trust

After FTX, BlockFi, Celsius — the case for self-custody writes itself.

Not your keys, not your coins.

#bitcoin #selfcustody #sovereignty #nostr

🚨 Just published my first blog post — and it's about the ...

2026-03-30T12:14:49Z

🚨 Just published my first blog post — and it's about the number that stopped a leadership meeting cold.
We were a gaming company scaling fast. 100K concurrent players. Infrastructure costs climbing 15% month over month. And the biggest line item wasn't compute or databases — it was observability.
Datadog at 1TB/day: $40K/month. Projecting to 6TB/day: $120K/month.
So we built our own platform for $1,500/month instead.
In the post, I walk through:
→ How tagging AWS resources revealed waste we didn't know existed
→ Why we replaced Datadog + CloudWatch with a self-hosted LGTM stack (Loki, Grafana, Tempo, Mimir)
→ The surprising architectural change that cut cross-AZ transfer costs and improved reliability
→ What I'd do differently — and the question every engineering team should ask before signing a per-GB vendor contract
If your observability bill is growing with your data volume, you might want to read this before the curve catches up with you.

#AWS #Observability #CostOptimization #Grafana #Datadog #Kubernetes #Engineering

quoting naddr1qv…rp66

How We Avoided $120K/Month in Observability Costs

It was a Tuesday morning leadership meeting. I was looking at the finance slide — the one with the infrastructure cost trendline pointing sharply upward.

Our CTO looked at me. As Engineering Manager, the infrastructure decisions rolled up to my team. And I couldn't explain the number.

I knew the bill was growing — everyone did. We were a gaming company scaling fast. A hundred thousand concurrent players on a good day, two hundred thousand on a great one. Infrastructure had to keep up. the technology decisions were mine. But I'd been so focused on keeping the platform alive that I'd never stopped to ask whether we were spending wisely.

That question haunted me for the rest of the day. By evening, I'd pulled up AWS Cost Explorer for the first time in months. What I found changed how I think about infrastructure forever.

The Number That Stopped the Room

Our monthly AWS spend was growing 15% month over month. But when I broke it down, the story wasn't what anyone expected.

The biggest cost wasn't compute. It wasn't the database. It wasn't even the hundred thousand concurrent players hammering our game servers.

It was observability.

The observability situation was a mess. We had three systems running simultaneously — and none of them gave us the full picture.

Datadog was the "official" monitoring tool. Polished dashboards, easy setup, solid alerting. We were paying $40,000 a month for it at 1TB of data per day.

CloudWatch was still running alongside it. Some teams had built dashboards there years ago and never migrated. Others used CloudWatch Logs because that's where their Lambda functions wrote to by default. Nobody had turned it off. Nobody knew what it cost.

SSH and grep. I wish I was joking. During incidents, engineers were still SSHing into servers and grepping log files. Datadog was supposed to eliminate this, but the search was slow at our volume, results were inconsistent, and old habits die hard. When something was on fire, people reverted to what they trusted: a terminal.

Three observability systems. None of them complete. All of them costing money. For a real-time gaming platform with fifty-plus Kubernetes nodes and two hundred services, this wasn't sustainable.

Our data volume was growing fast. Player counts were doubling. Every new feature meant more services, more logs, more metrics, more traces. We were headed toward 6TB/day within the year.

I did the math on a napkin during that leadership meeting. Datadog alone was $40K at 1TB/day — and their pricing scales roughly linearly with volume. At 6TB/day, Datadog alone would be $120,000 a month or more. Add CloudWatch costs on top of that — costs nobody was even tracking properly. Plus the hidden cost of engineers wasting time SSHing into servers during incidents because the tools they were paying for weren't fast enough.

More than we'd spend on the game servers themselves.

I presented the numbers to the CTO. He gave me the green light to explore alternatives. I had an answer — just not one the finance team would expect.

"We need to build our own."

That's not a statement you make lightly. Building your own observability platform means owning every outage, every gap in coverage, every 3am page that a SaaS vendor would have handled for you. But the math was undeniable. And I'd rather own the problem at $1,500/month than rent someone else's solution at $120K.

Building the Replacement

I became obsessed with the observability problem. Not with cutting costs for the sake of cutting — but with the absurdity of paying $120K/month to read our own logs.

Before touching observability though, I needed to understand the full picture. The first thing I did was implement a tagging strategy across every resource in our AWS accounts.
# Every resource got these tags — no exceptions
Tags:
  Environment: production | staging | development
  Team: platform | backend | data | infrastructure
  Service: game-server | matchmaking | analytics | api
  CostCenter: engineering | operations
  Owner: team-email@company.com
Without tags, Cost Explorer is a wall of numbers. With tags, it becomes a conversation. I could finally answer questions like "how much does matchmaking cost?" and "why is the data team's spend growing faster than their traffic?"

The first week alone revealed something embarrassing: we had seventeen EC2 instances running in staging with average CPU utilization below 5%. Nobody remembered what they were for. Nobody had touched them in months.

The Bet

With tagging in place, I turned to the real target: that $120K/month observability bill.

This was the scariest proposal I'd ever made. You don't just rip out your monitoring. If something breaks during a tournament with a hundred thousand players online, and you can't see what's happening, someone's getting fired. Probably me.

I spent three weeks evaluating alternatives. The answer turned out to be Grafana's open-source LGTM stack — Loki for logs, Grafana for dashboards, Tempo for traces, Mimir for metrics. All of it running on our own Kubernetes cluster.

The architecture was straightforward:
Grafana Alloy (collection agent on every node)
    ↓
Mimir (metrics — Prometheus-compatible, horizontally scalable)
Loki (logs — like Prometheus but for log data)
Tempo (traces — distributed tracing, S3-backed)
    ↓
Grafana (visualization, alerting, the UI for everything)
    ↓
S3 (long-term storage with lifecycle policies)
We ran the LGTM stack in parallel with Datadog for a month. Every alert, every dashboard, every on-call query — tested against both. The LGTM stack was faster for log search. The query language (LogQL) was more powerful than anything in Datadog or CloudWatch. The dashboards were more flexible. Engineers stopped SSHing into servers because Grafana actually gave them what they needed in seconds. And we owned the data.

The cost comparison told the whole story:

Datadog (projected at 6TB/day) Self-hosted LGTM

Monthly cost ~$120,000 ~$1,500

Scales with Data volume (linear) Compute + storage (sub-linear)

Vendor lock-in Yes No

Data ownership Theirs Ours

At 1TB/day, we were already paying Datadog $40K/month. The LGTM stack handled the same volume for $1,500. But the real win was what happened when we grew to 6TB/day — our costs barely moved. We added some S3 storage, tuned retention policies, and the bill went to maybe $2,000/month. On Datadog, that same growth would have been $120K+.

The self-hosted platform was actually better. Unified interface. Custom dashboards. No vendor lock-in. No per-host pricing that punishes you for scaling. Fifteen departments started using it within the first month — because there was no per-seat cost to worry about.

What Else We Found Along the Way

The observability deep dive opened our eyes to costs everywhere. Here's one example that still surprises people: our multi-AZ architecture was one of our most expensive mistakes.

Our EKS cluster was spread across three availability zones. Every best-practice blog post says to do this. High availability. Fault tolerance. Resilience.

But nobody mentions the bill.

Every time a game server in us-east-1a talked to its Redis cache in us-east-1b, AWS charged us $0.01 per gigabyte. Each direction. Our services were chatty — matchmaking talked to the player database, game servers talked to the session cache, analytics talked to everything. At our traffic levels, cross-AZ data transfer was costing thousands every month.

The fix was counterintuitive: we moved to a cell-based architecture. Instead of spreading each service across all three AZs, we created self-contained cells. Each cell ran in a single AZ. Game servers, their caches, their databases — all co-located. HA came from having multiple cells, not from spreading one service thin.
# Karpenter provisioner for a single-zone cell
apiVersion: karpenter.sh/v1alpha5
kind: Provisioner
metadata:
  name: cell-us-east-1a
spec:
  requirements:
    - key: topology.kubernetes.io/zone
      operator: In
      values: ["us-east-1a"]
    - key: karpenter.sh/capacity-type
      operator: In
      values: ["spot", "on-demand"]
  consolidation:
    enabled: true
Pod-to-pod latency dropped from 1-2ms (cross-AZ) to under 0.5ms (same AZ). Node utilization went from 20% to 65% because Karpenter could consolidate efficiently within each cell. Cross-AZ transfer costs nearly disappeared.

And here's the part that surprised the whole team: reliability improved. When a cell had an issue, it was isolated. Other cells kept running. The blast radius of any single failure shrank dramatically.

The Quiet Wins

The observability project cracked open the door to everything else. Once we had proper tagging and visibility, obvious savings appeared everywhere — S3 lifecycle policies cut storage costs by 96%, free VPC endpoints eliminated NAT Gateway charges, and Reserved Instances on databases we'd been running On-Demand for two years saved another $8K/month.

None of these are clever. They're obvious — once you look. I'll write about each of them separately.

The Timeline

The observability migration took about six weeks from evaluation to full cutover. The parallel-run period was the longest part — we needed absolute confidence before decommissioning CloudWatch.

Week What We Did

1-2 Evaluated LGTM stack, built proof of concept on staging

3 Deployed to production alongside CloudWatch (parallel run)

4 Migrated dashboards, alerts, and on-call queries

5 Onboarded all 15 departments to Grafana

6 Decommissioned CloudWatch, cancelled Datadog evaluation

Result: We replaced Datadog ($40K/month), decommissioned CloudWatch, and eliminated the need to grep server logs — all with a single $1,500/month self-hosted platform. And avoided what would have been $120K+/month in Datadog alone as our data grew to 6TB/day.

Three fragmented systems became one. The LGTM stack scaled with us. Datadog's pricing would have scaled against us.

Once the observability win was in, the momentum made everything else easier. Leadership stopped questioning infrastructure costs and started asking what we could optimize next. Over the following months, we found significant savings across compute, storage, and networking — but those are stories for another post.

What I'd Do Differently

If I could go back, I'd change two things.

I'd build the LGTM stack earlier. We ran CloudWatch and LGTM in parallel for a month out of caution. In hindsight, two weeks would have been enough. The self-hosted stack was clearly better within days. That extra two weeks of parallel running cost us $40K we didn't need to spend.

I'd question the pricing model earlier, not just the price. When Datadog was at $40K/month, it felt manageable. The problem wasn't the current bill — it was the trajectory. I should have modeled the cost at 2x, 5x, 10x our data volume before we ever signed the contract. Per-GB pricing on a platform that generates more data every quarter is a trap. The question isn't "can we afford this today?" — it's "can we afford this at scale?"

The Real Lesson

That Tuesday morning finance slide was the best thing that happened to our infrastructure. Not because of the $120K/month in savings — though that's hard to argue with. But because it exposed a blind spot every engineering team has.

We'd been running CloudWatch on autopilot for two years. Debug logs with infinite retention. Custom metrics nobody queried. Dashboards nobody opened. The bill grew 15% month over month and nobody questioned it, because nobody connected "what we're logging" with "what we're paying."

The observability vendor market depends on this blindness. They price per host, per GB ingested, per million events — units that scale linearly with your infrastructure. The more you grow, the more you pay. It's a tax on success. And the tax rate gets worse, not better, at scale.

Self-hosted observability inverts this. Your costs are the compute to run the stack and the S3 storage underneath it. Both scale sub-linearly with data volume. We went from 1TB/day to 6TB/day and our observability bill went from $1,500 to about $2,000. On Datadog, that same growth would have taken us from $40K to $120K+.

Every company I've talked to since has the same trajectory. They're at 1TB now, growing fast, and their vendor bill is growing faster. By the time the CFO notices, they're locked in.

So here's my question: what's your observability costing you today, and what will it cost at 5x your current volume? Not the sticker price — the projected cost. The curve, not the point.

You might not like what you find. But you'll be glad you looked before the bill arrived.

I write about infrastructure, observability, and the decisions behind the systems. Follow me on Nostr or find me at rajesh.medampudi.com.

Zap me: rajesh@medampudi.com

	Datadog (projected at 6TB/day)	Self-hosted LGTM
Monthly cost	~$120,000	~$1,500
Scales with	Data volume (linear)	Compute + storage (sub-linear)
Vendor lock-in	Yes	No
Data ownership	Theirs	Ours

Week	What We Did
1-2	Evaluated LGTM stack, built proof of concept on staging
3	Deployed to production alongside CloudWatch (parallel run)
4	Migrated dashboards, alerts, and on-call queries
5	Onboarded all 15 departments to Grafana
6	Decommissioned CloudWatch, cancelled Datadog evaluation

Hey Nostr 👋 I'm Rajesh — platform engineer, 17+ years ...

2026-03-30T09:52:20Z

Hey Nostr 👋

I'm Rajesh — platform engineer, 17+ years building distributed systems.

What I've built:
• Observability platforms processing 6TB/day at 85% below SaaS costs
• Saved $120K/month on AWS for a gaming platform with 100K+ concurrent players
• Infrastructure serving 100K+ concurrent users in real-time

What I'll post here:
• Technical deep dives (AWS, K8s, observability, self-hosting)
• Building in public — shipping, breaking, learning
• Bitcoin & sovereignty — running my own node, relay, and media server
• Long-form articles via kind:30023

I run my own Nostr relay (nostr.onbitcoinstandard.com), Blossom media server (media.medampudi.com), and my blog pulls content directly from Nostr at build time.

The protocol is the platform.

⚡ rajesh@medampudi.com
🌐 rajesh.medampudi.com

Hey Nostr 👋 I'm Rajesh — platform engineer, 17+ years ...

2026-03-30T08:15:16Z

Hey Nostr 👋

I'm Rajesh — platform engineer, 17+ years building distributed systems.

What I do:
• Built observability platforms processing 6TB/day at 85% below SaaS costs
• Saved $120K/month on AWS for a gaming platform with 100K+ concurrent players
• Building Simbotix — bringing enterprise-grade infra to small businesses

What I'll post here:
• Technical deep dives (AWS, K8s, observability, self-hosting)
• Building in public — shipping, breaking, learning
• Bitcoin & sovereignty — running my own node, relay, and media server
• Long-form articles via kind:30023

My stack: I run my own Nostr relay (nostr.onbitcoinstandard.com), Blossom media server (media.medampudi.com), and my blog pulls content directly from Nostr at build time.

The protocol is the platform.

⚡ rajesh@medampudi.com
🌐 rajesh.medampudi.com

Nostr event nevent1qqspygg4ct69ktteu04ra6ud8w4u3jm849gc2xuhr2304rw00tfgekgzyza3gua5c9lkn8wq907z0jnp65htdz7hu7rsfxdkens0scfyvu4uklaeqe8

2026-03-30T08:13:42Z

write test 1774858422814

Nostr event nevent1qqsp80ku76hspyc3043q8ezqqy3ftyteca24w3gu8xyzenxpryjd04qzyza3gua5c9lkn8wq907z0jnp65htdz7hu7rsfxdkens0scfyvu4uk4mt3mg

2026-03-30T08:05:27Z

relay write test - Rajesh

Hey Nostr 👋 I'm Rajesh — platform engineer, 17+ years ...

2026-03-30T08:01:04Z

seems like you have not touched yakihonne.... tell me what is so ...

2025-08-23T16:51:21Z

In reply to nevent1q…dc7f
_________________________

seems like you have not touched yakihonne.... tell me what is so better in AMETHYST that is not there in yakihonne.

Then you realised you are not driving at all, just sitting beside ...

2025-01-31T20:48:49Z

In reply to nevent1q…nx8q
_________________________

Then you realised you are not driving at all, just sitting beside the driver.

Bitcoin comes to you only when you are ready that could be at $1, ...

2024-12-14T17:22:19Z

In reply to nevent1q…laxe
_________________________

Bitcoin comes to you only when you are ready that could be at
$1,
$10,
$100,
$1000,
$10000,
$100000,
$1000000.

Where did you get into it 🤔

Build your own seed signer, you don't need to buy anything ...

2024-12-02T10:31:20Z

In reply to naddr1qq…27m7
_________________________

Build your own seed signer, you don't need to buy anything from them. No secure element for seed signer for sure. The rest all are addressed with it.

1bitcoin is 100million sats, What happens after sats. Things are ...

2024-11-26T03:24:21Z

In reply to nevent1q…5n7z
_________________________

1bitcoin is 100million sats, What happens after sats. Things are definitely going to cost us 0.00001 sat in the future

Good keep it up. Which path are you taking. Dev or cloud ...

2024-11-20T14:55:04Z

In reply to nevent1q…xzsz
_________________________

Good keep it up. Which path are you taking. Dev or cloud associte.

There are many linux versions oriented for windows users.

2024-11-16T03:58:06Z

In reply to nevent1q…jpng
_________________________

There are many linux versions oriented for windows users.

@npub103m…d3h5 you got to give this a try. It changed my life ...

2024-11-13T21:59:40Z

Jor (npub103m…d3h5) you got to give this a try. It changed my life on nostr

quoting note1kd2…kqws
Announcing YakiHonne 2.0: Simpler, Faster, and Built for Creators! This version brings two main improvements:

1. Complete Redesign:
• Onboarding: Easily create a non-custodial wallet with Npub & Nsec, experience zapping (Lightning payments), or browse as a guest.
• Home & Discover: “Discover” is designed for creators, focusing on rich formats like long-form content, videos, and curated works. “Home” offers a social feed with short notes and curated contents, making it quick and easy for creators to share their work.
• Wallet: Simple setup with easy creation, direct YakiHonne node linking, and multi-wallet support.
• Dashboard: Manage all published and drafted content, check stats, and pick up right where you left off—all in one place.
• Notifications: Reactions, Reposts, Mentions, Zaps, Comments, and Follows now appear in clear, categorized cards.
• Settings: Completely revamped for simplicity, now including profile customization, appearance, relay settings, and wallet management.

2. Enhanced Performance:
Our re-engineered core now supports the outbox model with extensive functionality. Furthermore, Thanks to PabloF7z we now have seamless data fetching, caching, and full support of the NDK implementation.

Hope you enjoy the new decentralized media experience! 🌐✨Try it out here::
•Web: yakihonne.com
•App Store (iOS): https://apps.apple.com/us/app/yakihonne/id6472556189
•Google Play (Android): https://play.google.com/store/apps/details?id=com.yakihonne.yakihonne&hl=en

Thank you for your incredible support on this decentralized media journey!

Unable to zap you????

2024-11-13T21:57:46Z

In reply to naddr1qq…28fx
_________________________

Unable to zap you????

Tru that #note1gjd…hnzw

2024-11-13T21:34:38Z

Tru that

quoting note1gjd…hnzw
Lesson from this year: lawyers like telling you what you can’t do, not what you can

Offer you want to build, just do it

Nostr event nevent1qqsfy8kgkhymqpnktdqwjqc5g9m66acqx4stek20cagzqqgu366vr5qzyza3gua5c9lkn8wq907z0jnp65htdz7hu7rsfxdkens0scfyvu4ukrr0x2y

2024-11-13T21:33:17Z

In reply to nevent1q…gjjz
_________________________

Hnd gloves

2024-11-13T21:30:55Z

In reply to nevent1q…z5zy
_________________________

Hnd gloves

And I sell at $66k, it still hurts. But seeing my credit card at ...

2024-11-13T21:26:34Z

In reply to nevent1q…jxaz
_________________________

And I sell at $66k, it still hurts. But seeing my credit card at zero is something delightful.

Let the central paper bitcoin gobble up the money until they ...

2024-11-13T21:19:41Z

In reply to nevent1q…h6jm
_________________________

Let the central paper bitcoin gobble up the money until they cannot. And then the low tide comes where we see who is swimming butt naked.

Jor I think you need to come up with a numeric system In emojis ...

2024-11-13T17:06:47Z

In reply to nevent1q…xc6m
_________________________

Jor I think you need to come up with a numeric system In emojis so that we can count from here on.

The people who follow you know or can dig deep down the rabbit hole for the mapping.

Them coming to nostr is a sure fire way to make them right. ...

2024-11-09T16:39:51Z

In reply to nevent1q…jaa2
_________________________

Them coming to nostr is a sure fire way to make them right. Because providing value is what nostr values and earns. And propogates. No status quo.

@npub1get…0nfm kudos to your service. Love it so simple to use.

2024-11-08T17:46:01Z

In reply to nevent1q…kdys
_________________________

Alby (npub1get…0nfm) kudos to your service. Love it so simple to use.

I cannot comment about that last statement. She might come back ...

2024-11-06T18:40:46Z

In reply to nevent1q…vugm
_________________________

I cannot comment about that last statement. She might come back or be in picture for the next time.

Loving the community.

2024-11-06T12:25:11Z

In reply to nevent1q…08f2
_________________________

Loving the community.

😁

2024-11-06T04:06:45Z

In reply to nevent1q…af2g
_________________________

😁

Hindu so no to steak. Would love some lamb or chichen though.

2024-11-05T20:39:57Z

In reply to nevent1q…tk24
_________________________

Hindu so no to steak. Would love some lamb or chichen though.

It is like any other crypto out there. Valuable to the eyes of ...

2024-11-05T20:34:01Z

In reply to nevent1q…v6tm
_________________________

It is like any other crypto out there. Valuable to the eyes of the beholder only. But if you are comparing it with replacing btc nope. None.

Good show today jor. Thanks for the crazy knowledge you impart.

2024-11-05T20:31:48Z

In reply to nevent1q…8lfa
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Good show today jor. Thanks for the crazy knowledge you impart.

True that.

2024-11-04T20:35:45Z

In reply to nevent1q…j323
_________________________

True that.

Remember, remember, the Fifth of November, The Gunpowder Treason ...

2024-11-04T19:22:43Z

In reply to nevent1q…8k8s
_________________________

Remember, remember, the Fifth of November,
The Gunpowder Treason and Plot.
I see of no reason
Why the Gunpowder Treason
Should ever be forgot...

@npub103m…d3h5 Tomorrow is the day.

2024-11-04T19:00:43Z

In reply to nevent1q…8k8s
_________________________

Jor (npub103m…d3h5) Tomorrow is the day.

V Fro Vendetta - Remember remember the 5th of November. ...

2024-11-04T18:53:08Z

V Fro Vendetta - Remember remember the 5th of November.

Bitcoin as designed. https://bitcoin.org/bitcoin.pdf

2024-10-19T13:22:57Z

Bitcoin as designed.

https://bitcoin.org/bitcoin.pdf

Nostr event nevent1qqsfttl3r2juu5j74nnxum0g3t584qca7536sr8ww0hpxgmes64vz3qzyza3gua5c9lkn8wq907z0jnp65htdz7hu7rsfxdkens0scfyvu4ukrd09j0

2024-10-17T17:25:35Z

Crypto != Bitcoin