The introduction of numbers as cordinates is an act of violence
India
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Deepak Kumar retweeted
The evergreen resource - An Introduction to Distributed Systems by Kyle Kingsbury
github.com/aphyr/distsys-cla…
For an impromptu discussion, the Google File System (GFS) came into the picture. And from there, I remembered this MIT course 6.824 Distributed Systems, where there is a lecture on it.
Many folks have covered GFS in depth, but this course also provides an in-depth view of Distributed Systems in general. Recommend this if you are interested in this domain.
nil.csail.mit.edu/6.824/2021…
(Note: the site is HTTP though)
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Deepak Kumar retweeted
🐘 Introducing Postgres Internals in 3D.
🌟 pgrun.dev/pi
Stop reading boring diagrams. Start exploring PostgreSQL.
An interactive 3D map to understand how Postgres actually works.
100% free. Built for developers.
x.com/alxshp/status/21100494…
Introducing PGSync 🐘
Real-time PostgreSQL replication. FREE. OSS
Built in Rust. 🦀
Postgres 16 / 17 / 18.
No extensions. No triggers. No complex setup.
→ snapshot
→ replicate
→ stream changes
→ track WAL
→ recover from crashes
→ resume automatically
→ keep databases in sync
~15 MB RAM during streaming.
Built for developers. Built for AI agents.
Open source.
x.com/alxshp/status/21078790…
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Deepak Kumar retweeted
banger read on infra and workflows side from stripe's blog
stripe.dev/blog/run-recurrin…
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Deepak Kumar retweeted
The 194th issue of the Polymathic Engineer is out.
This week, we discuss how to build a cache:
- The API contract
- Memory alone is not enough
- Building an LRU cache
- When fresher data isn’t better: the LFU cache
- Implementation
Read it here:
newsletter.francofernando.co…
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What?
Dear Prime Minister Ambani,
Please accept my humble apologies for not realizing that you are the real boss of India.
Naturally, you would prefer to maintain your monopolistic exploitation of the great people of India, but would you nonetheless consider allowing Starlink to compete?
There are many areas of India, as there are in all countries, with no Internet access, which denies children the opportunity for education and for small businesses the opportunity to sell their goods to a global market. Starlink would change their lives for the better.
Thank you 🙏
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Wow. This is interesting
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Deepak Kumar retweeted
went through this blog as i was curious how Talim used Postgres exactly
and man very good articulation Talim @talimbuilds
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Deepak Kumar retweeted
The project is real and open source.
Repo: github.com/GLinnik21/plx-nat…
Site: plxnative.com/
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Need zachxbt skills. And make agent out of it.
bro zachxbt is actually insane
this man went undercover as a money laundering client
spent $350K of his OWN money to gain the trust of a chinese launderer who was moving bybit hack funds for north korea
the guy started sharing everything. screenshots. wallet addresses. bridge transactions. in real time
zach was matching every single transaction on-chain as the guy was sending them
traced $12M+ across bitcoin, ethereum, solana, and tron
got tether to freeze $442K from the evidence alone
and the funniest part? in between discussing how to launder funds for north korea this guy was casually talking about playing mahjong and his weight loss plan 😭
bro thought he was talking to a client. he was talking to the most dangerous investigator in crypto
and zach funded this entire operation himself. $350K out of pocket. no guarantee he'd ever see it back
this is not the FBI. this is one guy with a laptop and a blockchain explorer
different breed
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Deepak Kumar retweeted
Very underrated tip from @karpathy.
Just tried ASD-STE100 rule for model responses, and I found it to be surprisingly good at making explanations clearer. It can be bit too strict, so I agree that "80% of the way to ASD-STE100" feels like a better default.
A prompt you can try with your agent:
"Use ASD-STE100 as a guide for your responses. Write short sentences, use active voice, and keep terminology consistent. Relax the vocabulary rules when they make explanations awkward. Preserve technical precision and uncertainty."
@0xpili_ also made a nice skill for it:
github.com/0xpili/simplified…
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.
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Deepak Kumar retweeted
Found the best resource to learn Harness Engineering. 😭
walkinglabs.github.io/learn-…
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Deepak Kumar retweeted
Wow: @petermattis has quite the history in shipping: co-created GIMP, built Gmail’s original backend, shipped Google’s Colossus, and is the cofounder and CTO at Cockroach Labs. We talked distributed DBs:
Timestamps:
00:00 Intro
02:42 Peter’s path into tech
04:00 Building GIMP
09:30 Working on Gmail at Google
14:51 Google’s infra: google3, build files, Bazel, and Colossus
21:30 Distributed storage bottlenecks
23:59 Latency, throughput, and availability
30:04 Contributing to libraries
41:52 Google Spanner
46:10 CockroachDB
52:00 Manual vs. automatic sharding
55:28 Consistency models and strong consistency
1:00:03 Raft consensus
1:06:15 How AI brought Peter back to coding
1:19:12 Peter’s tools and agentic workflows
1:23:08 How AI can improve quality
1:26:39 Code reviews: are they done?
1:29:17 100x engineers
1:35:33 Peter’s advice for leveling up your engineering skills
Brought to you by:
• @turbopuffer – the team are completely redesigning their storage architecture from first principles. And they’re documenting all of it! Follow along,: turbopuffer.com/v3
• @linear – most of us work with agents in a “single-player” setting. Linear’s take is agent work should be teamwork, and they built it so: linear.app/pragmatic
• @WorkOS – fresh from the WorkOS oven: Airlock, the authorization layer for AI agents. It evaluates every request against the agent’s intent and your rules and either allows it, denies it, or routes it to a human for approval. workos.com/airlock
Three fascinating parts from this convo:
1. Peter was recruited to Google because of... GIMP!
The very first version of the famous Google logo was made in GIMP, the free, open-source raster graphics and image editing software created by Peter and his college roommate Spencer Kimball.
In 2001, Sergey reached out to Peter, invited him to an interview and then made an offer. While Peter said no back then (thanks to the commute), he joined a year later, in 2002.
2. Peter twice “beat” standard library data structures in performance terms.
At Google, one of his colleagues noticed that std::map showed up in memory profiles. Peter looked closer and figured out that the std::map implementation is a red-black tree, meaning every node has two pointers. Peter built a B-tree with nearly the same semantics which was both faster, due to spatial locality, and smaller because it used fewer pointers. They used this data structure inside Google.
Peter also did something similar with Go’s map: it was performant, but he built a Swiss Table implementation that was faster. That implementation later made it into the Go library, with the Go team helping to finish it!
3. If you squint hard, everything in distributed databases and storage systems starts looking like a B-tree.
These B-trees are a recurring theme in this podcast episode: the backend of Gmail, the std::map replacement, CockroachDB’s range index, etc. There’s even a paper on this phenomenon, The Ubiquitous B-Tree
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Deepak Kumar retweeted
Rust has one serialization library that is Serde. Over the years I collected a bucket list of all the things that I do not enjoy about it. Finally did something about it and finished Deser. Here is a small summary of the why, what and how: lucumr.pocoo.org/2026/9/29/d…
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Deepak Kumar retweeted
study.devatlas.site
wtf this is free??? 💀 Your one-stop place to revise tech for interviews.
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