corpus.blog
56,966 blogs · [ { "id": "01a08cf3-43be-72eb-8e56-bbe0ca7d8e8b", "title": "How human-agent synergy can sharpen critical thinking", "url": "https://thedataquarry.com/blog/how-human-agent-synergy-can-sharpen-critical-thinking", "published_at": "2026-09-10T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80665b323a", "title": "Hyperdimensional Computing (3): From representation to online learning", "url": "https://thedataquarry.com/blog/hyperdimensional-computing-3", "published_at": "2026-08-15T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8066dfd5a0", "title": "Hyperdimensional Computing (2): Building an encoder", "url": "https://thedataquarry.com/blog/hyperdimensional-computing-2", "published_at": "2026-08-12T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8067bfe83e", "title": "Hyperdimensional Computing (1): The algebra of hypervectors", "url": "https://thedataquarry.com/blog/hyperdimensional-computing-1", "published_at": "2026-08-08T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80688388e9", "title": "How a Taiwanese Oolong changed the way I look at tea", "url": "https://thedataquarry.com/blog/how-a-taiwanese-oolong-changed-the-way-i-look-at-tea", "published_at": "2026-08-01T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806941cf5b", "title": "Incremental multimodal data pipelines with CocoIndex and LanceDB", "url": "https://thedataquarry.com/blog/incremental-multimodal-data-pipelines-with-cocoindex-and-lancedb", "published_at": "2026-07-04T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806989345c", "title": "5 reasons I love CocoIndex, and why you should try it", "url": "https://thedataquarry.com/blog/5-reasons-i-love-cocoindex-and-why-you-should-try-it", "published_at": "2026-06-19T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8069c77231", "title": "Towards multimodal knowledge graphs with lance-graph", "url": "https://thedataquarry.com/blog/towards-multimodal-kg-with-lance-graph", "published_at": "2026-04-30T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806a2c8af6", "title": "How I 5x my writing throughput with AI", "url": "https://thedataquarry.com/blog/how-i-5x-my-writing-throughput-with-ai", "published_at": "2026-04-12T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806b2a833d", "title": "From Kuzu to Ladybug: The embedded graph ecosystem powers onward", "url": "https://thedataquarry.com/blog/from-kuzu-to-ladybug", "published_at": "2026-04-11T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806bc51112", "title": "DataFusion and the Rise of Deconstructed Data Systems", "url": "https://thedataquarry.com/blog/datafusion-and-the-rise-of-deconstructed-data-systems", "published_at": "2026-04-10T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806c5b26d9", "title": "How Lance enables the Multimodal Lakehouse", "url": "https://thedataquarry.com/blog/how-lance-enables-the-multimodal-lakehouse", "published_at": "2026-03-27T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806d23adc5", "title": "A framework for technical writing in the age of LLMs", "url": "https://thedataquarry.com/blog/a-framework-for-reading-and-writing", "published_at": "2025-12-25T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806d2c3fa4", "title": "Why I'm excited to work at LanceDB", "url": "https://thedataquarry.com/blog/i-joined-lancedb", "published_at": "2025-10-20T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806ddab633", "title": "Learning DSPy (3): Working with optimizers", "url": "https://thedataquarry.com/blog/learning-dspy-3-working-with-optimizers", "published_at": "2025-10-13T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806e1d1e2d", "title": "Learning DSPy (2): Understanding the internals", "url": "https://thedataquarry.com/blog/learning-dspy-2-understanding-the-internals", "published_at": "2025-09-01T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806ec79dbd", "title": "Learning DSPy (1): The power of good abstractions", "url": "https://thedataquarry.com/blog/learning-dspy-1-the-power-of-good-abstractions", "published_at": "2025-08-26T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806f68f64f", "title": "Using LLMs to enrich datasets: A case study with BAML", "url": "https://thedataquarry.com/blog/using-llms-to-enrich-datasets", "published_at": "2025-03-23T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806f87999d", "title": "I've moved this blog to Astro, and I like it here", "url": "https://thedataquarry.com/blog/blog-is-now-in-astro", "published_at": "2025-02-26T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a806ff28818", "title": "BAML is like building blocks for AI engineers", "url": "https://thedataquarry.com/blog/baml-is-building-blocks-for-ai-engineers", "published_at": "2025-02-10T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80702fc09e", "title": "Why I'm excited about BAML and the future of agentic workflows", "url": "https://thedataquarry.com/blog/baml-and-future-agentic-workflows", "published_at": "2025-01-29T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80705b7210", "title": "uv: Towards a unified vision for Python tooling", "url": "https://thedataquarry.com/blog/towards-a-unified-python-toolchain", "published_at": "2024-12-26T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8070bad52d", "title": "Speeding up data analysis with Rayon and Rust", "url": "https://thedataquarry.com/blog/intro-to-rayon", "published_at": "2024-02-10T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8070ca479c", "title": "What I've learned about open source software, visualized in graphs", "url": "https://thedataquarry.com/blog/open-source-via-graph-viz", "published_at": "2023-12-06T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a807112ec2a", "title": "Why Pydantic just keeps getting better", "url": "https://thedataquarry.com/blog/intermediate-pydantic", "published_at": "2023-12-02T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80719635ec", "title": "Why I chose Zola to build this site", "url": "https://thedataquarry.com/blog/static-site-zola", "published_at": "2023-11-29T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8073171e70", "title": "Embedded databases (3): LanceDB and the modular data stack", "url": "https://thedataquarry.com/blog/embedded-db-3", "published_at": "2023-11-20T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80738243c3", "title": "Embedded databases (2): Kùzu, an extremely fast embedded graph database", "url": "https://thedataquarry.com/blog/embedded-db-2", "published_at": "2023-09-09T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8073918d93", "title": "Embedded databases (1): The harmony of DuckDB, Kùzu and LanceDB", "url": "https://thedataquarry.com/blog/embedded-db-1", "published_at": "2023-08-27T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80742c6e3e", "title": "Vector databases (4): Analyzing the trade-offs", "url": "https://thedataquarry.com/blog/vector-db-4", "published_at": "2023-08-19T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8074dfd81f", "title": "Blazing fast async data loading in Meilisearch", "url": "https://thedataquarry.com/blog/meilisearch-async", "published_at": "2023-07-28T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80753c38f7", "title": "Vector databases (3): Not all indexes are created equal", "url": "https://thedataquarry.com/blog/vector-db-3", "published_at": "2023-07-24T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a807632164b", "title": "Vector databases (2): Understanding their internals", "url": "https://thedataquarry.com/blog/vector-db-2", "published_at": "2023-07-09T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80725c1a9d", "title": "Obtain a 5x speedup for free by upgrading to Pydantic v2", "url": "https://thedataquarry.com/blog/why-pydantic-v2-matters", "published_at": "2023-07-01T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a80772cda84", "title": "Vector databases (1): What makes each one different?", "url": "https://thedataquarry.com/blog/vector-db-1", "published_at": "2023-06-28T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a807774c001", "title": "How Rust 🦀 is supercharging Python from the ground up", "url": "https://thedataquarry.com/blog/rust-is-supercharging-python", "published_at": "2023-06-15T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8077c99740", "title": "Neo4j for Pythonistas (2)", "url": "https://thedataquarry.com/blog/neo4j-python-2", "published_at": "2023-06-04T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a807823fd64", "title": "Neo4j for Pythonistas (1)", "url": "https://thedataquarry.com/blog/neo4j-python-1", "published_at": "2023-05-22T00:00:00+00:00" }, { "id": "01a087ec-85b5-72bd-b78b-3a8078f767c2", "title": "Hello, world!", "url": "https://thedataquarry.com/blog/hello-world", "published_at": "2023-04-29T00:00:00+00:00" } ] posts 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2026

How human-agent synergy can sharpen critical thinkingoriginal ↗
10 Sept 2026
Hyperdimensional Computing (3): From representation to online learningoriginal ↗
15 Aug 2026
Hyperdimensional Computing (2): Building an encoderoriginal ↗
12 Aug 2026
Hyperdimensional Computing (1): The algebra of hypervectorsoriginal ↗
8 Aug 2026
How a Taiwanese Oolong changed the way I look at teaoriginal ↗
1 Aug 2026
Incremental multimodal data pipelines with CocoIndex and LanceDBoriginal ↗
4 Jul 2026
5 reasons I love CocoIndex, and why you should try itoriginal ↗
19 Jun 2026
Towards multimodal knowledge graphs with lance-graphoriginal ↗
30 Apr 2026
How I 5x my writing throughput with AIoriginal ↗
12 Apr 2026
From Kuzu to Ladybug: The embedded graph ecosystem powers onwardoriginal ↗
11 Apr 2026
DataFusion and the Rise of Deconstructed Data Systemsoriginal ↗
10 Apr 2026
How Lance enables the Multimodal Lakehouseoriginal ↗
27 Mar 2026

2025

A framework for technical writing in the age of LLMsoriginal ↗
25 Dec 2025
Why I'm excited to work at LanceDBoriginal ↗
20 Oct 2025
Learning DSPy (3): Working with optimizersoriginal ↗
13 Oct 2025
Learning DSPy (2): Understanding the internalsoriginal ↗
1 Sept 2025
Learning DSPy (1): The power of good abstractionsoriginal ↗
26 Aug 2025
Using LLMs to enrich datasets: A case study with BAMLoriginal ↗
23 Mar 2025
I've moved this blog to Astro, and I like it hereoriginal ↗
26 Feb 2025
BAML is like building blocks for AI engineersoriginal ↗
10 Feb 2025
Why I'm excited about BAML and the future of agentic workflowsoriginal ↗
29 Jan 2025

2024

uv: Towards a unified vision for Python toolingoriginal ↗
26 Dec 2024
Speeding up data analysis with Rayon and Rustoriginal ↗
10 Feb 2024

2023

What I've learned about open source software, visualized in graphsoriginal ↗
6 Dec 2023
Why Pydantic just keeps getting betteroriginal ↗
2 Dec 2023
Why I chose Zola to build this siteoriginal ↗
29 Nov 2023
Embedded databases (3): LanceDB and the modular data stackoriginal ↗
20 Nov 2023
Embedded databases (2): Kùzu, an extremely fast embedded graph databaseoriginal ↗
9 Sept 2023
Embedded databases (1): The harmony of DuckDB, Kùzu and LanceDBoriginal ↗
27 Aug 2023
Vector databases (4): Analyzing the trade-offsoriginal ↗
19 Aug 2023
Blazing fast async data loading in Meilisearchoriginal ↗
28 Jul 2023
Vector databases (3): Not all indexes are created equaloriginal ↗
24 Jul 2023
Vector databases (2): Understanding their internalsoriginal ↗
9 Jul 2023
Obtain a 5x speedup for free by upgrading to Pydantic v2original ↗
1 Jul 2023
Vector databases (1): What makes each one different?original ↗
28 Jun 2023
How Rust 🦀 is supercharging Python from the ground uporiginal ↗
15 Jun 2023
Neo4j for Pythonistas (2)original ↗
4 Jun 2023
Neo4j for Pythonistas (1)original ↗
22 May 2023
Hello, world!original ↗
29 Apr 2023