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ath_ray

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投稿

Building the systems that build the software

blog.nilenso.com
3 ポイント·投稿者 ath_ray·26 日前·0 コメント

Why I Attack (2024)

nicholas.carlini.com
1 ポイント·投稿者 ath_ray·5 か月前·0 コメント

Codex CLI vs. Claude Code on Autonomy

blog.nilenso.com
1 ポイント·投稿者 ath_ray·5 か月前·0 コメント

Weird System Prompt Artefacts

blog.nilenso.com
1 ポイント·投稿者 ath_ray·5 か月前·0 コメント

A Sigmoid Dialogue (2014) [pdf]

aleph.se
1 ポイント·投稿者 ath_ray·5 か月前·0 コメント

A Call for New Aesthetics

newaesthetics.art
5 ポイント·投稿者 ath_ray·7 か月前·0 コメント

How to game the METR Plot

shash42.substack.com
2 ポイント·投稿者 ath_ray·7 か月前·0 コメント

Pedagogy Recommendations

parentheticallyspeaking.org
1 ポイント·投稿者 ath_ray·7 か月前·0 コメント

Frontier of the Year 2025

renaissancephilanthropy.org
1 ポイント·投稿者 ath_ray·7 か月前·0 コメント

Minimum Viable Benchmark

blog.nilenso.com
1 ポイント·投稿者 ath_ray·7 か月前·0 コメント

Paper AI Tigers

gleech.org
4 ポイント·投稿者 ath_ray·7 か月前·0 コメント

Variation Is King, Not the Average

xmrit.com
2 ポイント·投稿者 ath_ray·8 か月前·0 コメント

Show HN: A tool to properly observe your LLM's context window

blog.nilenso.com
8 ポイント·投稿者 ath_ray·8 か月前·0 コメント

Age (2022)

anilv.com
3 ポイント·投稿者 ath_ray·9 か月前·0 コメント

Building Repo Bench

repoprompt.com
1 ポイント·投稿者 ath_ray·9 か月前·0 コメント

A Software Analogy

atharvaraykar.com
1 ポイント·投稿者 ath_ray·9 か月前·0 コメント

Data on AI Models

epoch.ai
2 ポイント·投稿者 ath_ray·10 か月前·0 コメント

Agentic Development Disrupted Our Business Model

rangle.io
1 ポイント·投稿者 ath_ray·10 か月前·0 コメント

コメント

ath_ray
·7 か月前·議論
FYI, this was sent as an experiment by a non-profit that assigns fairly open ended tasks to computer-using AI models every day: https://theaidigest.org/village

The goal for this day was "Do random acts of kindness". Claude seems to have chosen Rob Pike and sent this email by itself. It's a little unclear to me how much the humans were in the loop.

Sharing (but absolutely not endorsing) this because there seems to be a lot of misunderstanding of what this is.
ath_ray
·10 か月前·議論
Yeah I agree. There's a lot more needed than just the User Story, one way I'm thinking about it is that the "core" is deliverable business value, and the "shells" are context required for fine-grained details. There will likely need to be a step to verify against the acceptance criteria.

I hope to back up this hypothesis with actual data and experiments!
ath_ray
·10 か月前·議論
I enjoyed the emphasis on optimising the context window itself. I think that's the most important bit.

An abstraction for this that seems promising to me for its completeness and size is a User Story paired with a research plan(?).

This works well for many kinds of applications and emphasizes shipping concrete business value for every unit of work.

I wrote about some of it here: https://blog.nilenso.com/blog/2025/09/15/ai-unit-of-work/

I also think a lot of coding benchmarks and perhaps even RL environments are not accounting for the messy back and forth of real world software development, which is why there's always a gap between the promise and reality.
ath_ray
·10 か月前·議論
"Unit of work" here is the unit for software delivery, and it can be decoupled from how any individual developer plans and executes whatever software they are delivering.

Product requirements are a hypothesis for creating business value, and the only way to test that hypothesis is to actually demonstrate a slice of that value in a way that's legible to all stakeholders involved.

This post is a nice articulation of this: https://blog.nilenso.com/blog/2025/09/17/the-common-sense-un...