I’m going to try to avoid falling into the trap of making a bad pun about the season…damnit! ;-)
Welcome to the September edition of Interesting Links in the Data and AI World. It’s a bumper edition (aren’t they always), with lots and lots about Kafka and related technologies in particular this month. Oh, and AI. Obvs.
AI, from my little corner of the internet (and my echo-chamber), seems to be calming down. Obviously, in one sense it’s actually going f**king crazy (hacks! AGI! Jev!!). But amongst folk like you and I working with computers, the conversation seems to have thankfully passed the "gnghgngh it’s just auto-complete" phase to "cool bro, which model you using?". It’s less about magic incantations of prompts ("Make no mistakes! Pretend you’re a senior engineer!"), and more about considered use of the coding agents and how to get the best out of them without pissing off our co-workers and open source project maintainers.
| November sees the return of Confluent’s conference about data streaming, Current, to San Francisco. Admission is free, and you can register here. |
The Confluent Developer Blog continues to publish some great material - check out these recent posts:
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Lorenzo Nicora — Absolutely Everything You Always Wanted to Know About Watermarks in Apache Flink Part 1 & Part 2.
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Gustavo de Morais — Flink SQL Evolution: Handling Custom CDC with FROM_CHANGELOG and TO_CHANGELOG.
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David Anderson — How I Review Flink SQL Solutions.
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David Anderson — Deduplicating Streams with Flink SQL.
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Geoff Williams — Streaming IoT sensor data from MQTT to Kafka.
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Kafka and Event Streaming 🔗
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🔥 Rogerio Santos — Why your Kafka topic ignores retention.ms (and how to fix it).
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Federico Valeri — Data liberation: Apache Kafka’s native cluster mirroring.
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André Terroir — Can Kafka Support Elastic Partitioning?
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Nicoleta Lazar — Auto-Magically Quitting MSK Part 1 & Part 2.
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Kaan Karakaya — How We Built Automated Capacity Testing for Kafka Consumers.
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Kshitij Nawandar — Five Years of Kafka at Razorpay’s UPI Switch.
Kafka’s architecture and future direction 🔗
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🔥 Two posts on a similar theme, from Anton Borisov — What Still Belongs in a Kafka Broker?, and Michał Matłoka — Diskless Kafka: What Happens When Brokers Stop Owning the Data?
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Michał also wrote another interesting piece: Log-first or Table-first? Apache Kafka, Fluss, & Streaming Tables.
Tools 🔗
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🔥 Khaos is an Apache 2.0 licensed tool from Aleksandar Skrbic for load testing Kafka and simulating different failures.
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Monedula’s Kafka Simulator has been updated with more fun and toys to try.
Kafka (not Kafka) 🔗
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Hot on the heels of Apache Fluss last month, Apache Iggy is now also a Top-Level Project.
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Michał Matłoka — Apache Kafka vs Apache Iggy: A Technical Comparison.
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🔥 Apache Fluss v1.0 has been released.
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blob-stream has just been released, and bills itself as a Kafka-like streaming system for high-throughput workloads that prioritizes total cost of ownership over ultra-low latency. You can read more in the launch blog post.
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Yusuf Birader, Brian Shih — Move Fast And Don’t Break Things: Automatic Apache Kafka® Migrations to WarpStream With Orbit.
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Tansu (a stateless Kafka-compatible broker with pluggable storage) has been renamed to Nisshi.
Stream Processing 🔗
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It wouldn’t really be an edition of Interesting Links without a post from Katya Gorshkova and her excellent series on Flink :) This month she’s looking at Running Flink SQL Batch as a Kubernetes Job.
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OSSIP is a very handy utility from Tom Cooper, gathering and organising Open Source Software Improvement Proposals. It covers Flink, Kafka, and several other related projects. Tom’s added a Mastodon and Bluesky feed of updates too which is nice.
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🔥 Nikita Savinov has written a very nice TUI for Flink.
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A new paper from Tyler Akidau et al. — The Dataflow Model Revisited.
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Maheep Myneni — Why and How Lyft Moved to the Apache Flink Operator.
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Sudarshan Shubakar — Event-time windowing with Flink on a Kafka stream — Learnings in a lab.
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Eduardo Donzeli — Apache Flink 2.3 vs 2.2: What Actually Improved for Production Streaming?
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Scuttlebutt, speculation, and sacrilege as the masses on
r/apachekafkadiscuss Why didn’t ksqlDB turn out to be successful?.
Analytics 🔗
August’s big news in the data industry was the acquisition of DuckLabs by AWS:
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Announcement: DuckLabs to Join AWS, Projects to Remain Open Source.
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Hannes Mühleisen has done several podcasts, including with Joe Reis and Kris Jenkins.
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🔥 Analysis from Rachel Stephens (RedMonk), Andy Warfield (AWS), Lindsay Clark (El Reg), Michael Driscoll (Rill Data).
Elsewhere:
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A nice set of tips and tricks from Hoyt Emerson on their DuckDB + AI Workflow.
Data Platforms & Architectures 🔗
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🔥 Five vendors in the streaming data space (including Confluent, for whom I work) have formed a working group and defined the Streamhouse, pitching it as a shared data architecture for the age of AI.
There are some related articles too:
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George Zefko — Query the Stream: An Introduction to the Streamhouse Pattern.
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Stéphane Derosiaux — Streamhouse: What It Is, What It Isn’t, and What’s Missing.
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Yali Sassoon considers whether agents will be the driving force behind moving business applications to cloud data platforms. See Streamhouse above too :)
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Details of how Walmart implement data contracts in their architecture.
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ByteByteGo — How American Express Processes Payments at Scale.
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Jeffrey T. Pollock — Zero Magic in Zero Copy.
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A paper from the Databricks Lakebase team (Nikita Shamgunov, Matei Zaharia, et al.) — Lakebase: Serverless Postgres over Open Lake Storage.
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Some interesting articles this month looking at how companies can build their data architectures so that analytics agents can make accurate use of the data:
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🔥 Pramod Sadalage, Prem Chandrasekaran — Making Your Data Ready for Agentic AI.
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Fabiane Nardon on InfoQ — Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models.
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Veronika Durgin discusses why the semantic layer is so important in the age of agents.
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Ian Macomber — The Shape and Feel of the Post-AI Data Stack.
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Timothy Wong — The Semantic Layer and Data Modeling Dilemma in AI Analytics.
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Eric Broda and Juha Korpela — Semantics for the Emerging Enterprise Agent Ecosystem.
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Maxime Rosina — (Re)Building an AI-Ready data universe at BlaBlaCar.
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Booking.com’s Kostiantyn Okhrimenko has details of their self-serve analytics platform including a semantic layer and AI agents for natural language querying of data.
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If you’re not sure how analytics agents are being used beyond the breathless pitch of vendors' marketing, this list from Matthieu Blandineau is a useful starting point: A curated list of articles from data teams building analytics agents.
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Ian Baldwin and colleagues at DoorDash — Inside Vera, DoorDash’s Data Agent.
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Kai Lentit has a very funny video: Interview with Big Data engineer in 2026. The amusing quotations from it are too many to list but I particularly liked this one:
Eventual consistency was too hard, so we went with immediately inaccurate
Data Engineering and Pipelines 🔗
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A nice write-up from Mark Rittman of the recent dbt Summit, covering What’s New and What’s Coming from dbt Labs, Fivetran and the Agentic Data Stack.
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Srikanth Mamidala from Twilio has an interesting article on InfoQ looking at Computing Time in Queue for Apache Hudi Data Lake Pipelines at Petabyte Scale.
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Read this thread from
r/dataengineeringand either weep as you see a mirror held up, or rejoice that you’ve not experienced some of the madness within: What is the most WTF thing you’ve seen at a company? -
Tim Castillo has written previously about implementing the medallion architecture up to Silver, but in this post addresses why he’s not published one for Gold — he doesn’t fully believe in it.
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Matt Martin shows off building a real-time data pipeline using Flink to de-duplicate events and then write them to DuckLake with Python: Streaming Events to DuckLake.
CDC 🔗
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🔥 Frane Jelavic has a nice real-world account of when things don’t go smoothly with Debezium: Debezium and PostgreSQL in Production: Surviving Database Failover.
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Andreas Andreakis writes about his new paper Generalized DBLog: A Verified Contract for Interleaving Copied Rows with a Change Log in his blog post A Verified Theoretical Basis for Incremental Snapshots in Debezium and Flink CDC.
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Sarthak Tripathy from Jimdo describes how they cut their CDC bill from $3,000 to $150 a month (spoiler: moving from AWS DMS to Maxwell).
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ClickHouse’s Sai Srirampur writes about their new WalShadow engine, claiming Sub-second Postgres replication to ClickHouse from physical WAL.
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Prathit Malik — How INTEGER and INT Produced Different Schemas in Debezium.
Open Table Formats (OTF), Catalogs, Lakehouses etc. 🔗
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🔥 Stefan Dienst has published a very nice hands-on exploration of Iceberg.
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Parquet write support has landed in Hardwood with the release of 1.1.0.Beta, along with performance improvements and more.
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Neelesh Salian from Apple presented recently about What’s New in Apache Iceberg 1.12 (the release is being voted on as I type, and should drop any day soon).
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Chris Douglas has two fascinating blog posts 1 2 about efficiencies to be had in Iceberg from the use of Compaction Maps. He also presented on the subject at a recent meetup, the recording of which is here.
RDBMS 🔗
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🔥 Is AI coming for our DBA jobs? Perhaps.
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Vadim Tkachenko — Evaluating LLM models for DBA tasks.
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Rohan Bansal — Training a 4B model to produce 81% faster query plans than Postgres.
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🔥 Lorin Hochstein has a nice guts 'n all analysis of database problems at GitHub.
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Elizabeth Garrett Christensen interviews Tom Lane about 30 Years of Postgres Architecture.
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A couple of good posts from Radim Marek this month: Read your own writes, off the primary and The unbearable lightness of one more index.
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Gülçin Yıldırım Jelínek — Read your writes: WAIT FOR in PostgreSQL 19.
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Milan Jovanović — How to Design the Right SQL Index.
General Data Stuff 🔗
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Jack Vanlightly has been, in his own words, "For fun and no-profit, […] collecting and specifying (in TLA+) WAL-on-S3 designs and anything remotely log-like, as long as S3 is the only source of truth". You can find the growing collection on GitHub here.
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Almog Gavra — how to think about latency in distributed data systems.
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🔥 Rick Houlihan from Oracle looks at the difference between Converged Database vs. Multi-Model Database.
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Booking.com’s Başak Tuğçe Eskili — How we selected the next vector database.
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Jon Lee and team at OpenAI have written about Rapidly scaling online storage to serve over 1 billion ChatGPT users.
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🔥 I enjoyed this podcast from Gergely Orosz in which he interviews Casey Muratori about Why performant code matters (but gets widely ignored).
Casey Muratori has a blog here, as well as a cool talk titled The Root of the Root of All Evil all about the background to the well-known expression premature optimization is the root of all evil.
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Justin Cormack has written an open-source S3 clone, argmin. He writes about to what extent he used AI, and links out to a couple of talks that he’s given about it too.
AI 🔗
The OpenAI / Hugging Face incident 🔗
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Whilst AI is moving so fast that this may even seem old hat now that all the labs are rushing to claim many other hacks including the Australian government (?!)—but agents from OpenAI deciding to get themselves internet access and do a bunch more including hacking into Hugging Face really did blow my mind. If you only heard the initial accounts of this (accessing H.F. just to get the result for a test), it’s actually a lot more than that. Communicating with each other, taking steps for a perceived 'common good' of the agent swarm, and so on. |
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Ryan Greenblatt, Ajeya Cotra, and Hjalmar Wijk published a Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident.
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Dwarkesh Patel — The Rise and Fall of Agent Civilizations.
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🔥 Dwarkesh Patel has an excellent interview with Ajeya Cotra (one of the researchers on the above investigation), and she has also published her own blog post The Hugging Face attack surprised me.
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One of the other researchers, Ryan Greenblatt, did a podcast episode with Sam Harris: A Coin Toss for the Future.
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Researchers from OpenAI, Eric Wallace and Michael Dalton, gave a talk in August at Black Hat USA 2026 about the hack and the subsequent investigation: Unraveling an autonomous, multi-agent system.
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Max Read takes a more measured approach to the episode and cautions against anthropomorphising agents: AI is all sci-fi stories all the way down.
The whole incident brought the issue of AI safety and regulation back to the fore, with varying opinions and analysis:
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Casey Newton — The AI safety vibe shift.
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🔥 Ezra Klein speaks to Matt Sheehan about the state of AI, regulation—and the "But China!" argument that always surfaces when the R word is raised. There’s a video and transcript (if you don’t have an NYT subscription, you can access the page via Freedium).
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Ed Zitron — AI Is Already In Dangerous Hands.
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🔥 Rob Bowley — The AI threat is real, it just isn’t the one in the headlines.
General 🔗
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🔥 If you only listen to one podcast episode this month, make it this one from Joe Reis: Nobody Knows…
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If all you do all day long is feed tokens into the LLM and crank the handle, it’s sometimes good to get a little perspective and counter-opinion, and Cory Doctorow brings it in spades (always!) with this piece: The Claude Delusion.
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Stephen O’Grady — How to Think About Open Weight Models.
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Charity Majors published a great set of blogs about AI Norms & Values at Honeycomb:
AI and how we communicate 🔗
A series of solid posts on why you shouldn’t use LLMs to write your words for you:
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🔥 Charity Majors — Confessions of an Unrepentant Slop Snob.
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🔥 Michael Lopp — Robots Have No Voice.
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Colin Breck — I Don’t Want to Read What You Didn’t Write.
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Zach Holman — As Someone Who Has Written This Blog Post,
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Murat Demirbas — The Safest Job from AI may be Writing.
No-one is saying don’t use LLMs (well, some are, but those folk are gonna be in trouble), just use them for the right thing. Thomas & Erin Ptacek have a nice article laying out How To Write With An LLM.
AI in Software Engineering 🔗
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🔥 Oh dear, I’ve got Charity Majors featured at least three times over here, haven’t I? Well that’s because she has great ideas and communicates so damned well. Here she is talking to Gergely Orosz: Stop being skeptical about AI for development.
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🔥 Stephen O’Grady — Agents: The new, New Kingmakers.
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Kate Holterhoff — Shopify returns to native, and what that says about rewrites in the agentic era.
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I like this idea from Cory Doctorow about how AI coding agents now enable one to "scratch an itch". He goes on to relate it to FOSS and the benefits that open software in general provides.
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If you’re wanting to learn more about agents then check this out - the course materials for CMU’s AI Agents course are available, including lecture slides, recordings, and assignments.
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Simon Willison — Jev introduces a new shape of LLM—System One, aka Decision Models.
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This is a fun project (and good write-up) from Ian Macomber: How I Built an Automated Cycling Ride Recap with GoPro, Garmin, and Gemini.
And finally… 🔗
Nothing to do with data, but stuff that I’ve found interesting or has made me smile.
Nerd 🔗
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A couple of interesting posts from the teams at Cloudflare, about optimising 1.1.1.1’s DNS cache and optimising the memory footprint of a service.
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🔥 Very cool use of technology for 🐦 bird-watchers, with an Automatic Bird Identification System with Security Cameras, as well as an E-ink bird frame that shows an image of the bird currently detected.
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Jim Nielsen — Don’t Let Anyone Take Away Your Big Box of Cables.
Communicate 🔗
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Simon Späti interviewed Benn Stancil who shares some great insights on how he goes about writing.
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Gwen Shapira shares words of wisdom on the importance of clarity in blog writing.
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🔥 Michael Heap — I believe you. I don’t need the details. Tell me what we’re changing.
Misc 🔗
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🎧 Francis Fukuyama: ‘The old United States is not coming back’.
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I love that sites like this still exist on the internet. Ian Fieggen has an entire website devoted to… how to tie your shoelaces properly 🪢.
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Some 🔥 from Elena Verna, in which she tells us Congrats, your sales problems in PLG are completely unoriginal.
Cool visualisations 🔗
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Newton’s Orchard — Explore and experiment with space systems and gravity.
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🔥 Parcelscope — How the LA skyline changed 1880–2026.
Remember 🔗
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