This is the same as having it in unstructured documents. Which means the auditing is still required funny enough.

So yes, this could be done. I'd love to see what run in the CI/CD for a change. When someone works on the wrong thing, or breaks compliance IRL, how do you backport it into this? "Alice is a software engineer, and created this SaaS account with her email when the company was founded. The admin email can not be changed and she has admin even though another role should control that"

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> Last Friday we announced install.md and it didn't see much adoption.

With thrash like this why would anyone adopt this for something serious?

It's just an .md file, so the overhead is low. The lack on conviction in your design does not inspire confidence though.

My personal prediction is that the US foundational model makers will OSS something close to N-1 for the next 1-3 iterations. The CAPEX for the foundational model creation is too high to justify OSS for the current generation. Unless the US Gov steps up and starts subsidizing power, or Stargate does 10x what it is planned right now.

N-1 model value depreciates insanely fast. Making an OSS release of them and allowing specialized use cases and novel developments allows potential value to be captured and integrated into future model designs. It's medium risk, as you may lose market share. But also high potential value, as the shared discoveries could substantially increase the velocity of next-gen development.

There will be a plethora of small OSS models. Iteration on the OSS releases is going to be biased towards local development, creating more capable and specialized models that work on smaller and smaller devices. In an agentic future, every different agent in a domain may have its own model. Distilled and customized for its use case without significant cost.

Everyone is racing to AGI/SGI. The models along the way are to capture market share and use data for training and evaluations. Once someone hits AGI/SGI, the consumer market is nice to have, but the real value is in novel developments in science, engineering, and every other aspect of the world.

[0] https://www.anthropic.com/research/persona-vectors > We demonstrate these applications on two open-source models, Qwen 2.5-7B-Instruct and Llama-3.1-8B-Instruct.

Future frameworks will be designed for AI and enablement. There will be a reversal in convention-over-configuration. Explicit referencing and configuration allow models to make fewer assumptions with less training.

All current models are trained on good and bad examples of existing frameworks. This is why asking an LLM to “code like John Carmack” produces better code.. Future frameworks can quickly build out example documentation and provide it within the framework for AI tools to reference directly.

Authors from several countries were already suspicious, such as Iran. Anyone from Russia and China or unknown places are all potential risks now.

Combined with recent inclusive ideologies, it’s gonna cause hard conversations. There will be a furthering in segmenting the Internet. Why fight contributing to an open source project when you could fork it and contribute with your allies?

For true enemies, there’s no risk to licensing or copyright issues. You can merge changes from the original, no problem. China even falls into this as there’s a limited ability for US companies to litigate within the country.

People think the Network State is hot, but at the end of the day, the Internet still has borders.

Kubernetes was the chasm. Owning the computing platform is the core of utilizing Vault and integrating it.

The primary issue was that there was never a "One Click" way to create an environment using Vagarent, Packer, Nomad, Vault, Waypoint, and Boundry for a local developer-to-prod setup. Because of this, everyone built bespoke, and each component was independently debated and selected. They could have standardized a pipeline and allowed new companies to get off the ground quickly. Existing companies could still pick and choose their pieces. On both, you sell support contracts.

I hope they do well at IBM. Their cloud services' strategy is creating a holistic platform. So, there is still a chance Hashi products will get the integration they deserve.

Mixing the infra and application logic is the obvious path forward, though. Just as most applications don't need more than Rails and a single Postgres, most apps don't need customized infra. Simplifying the 80% unlocks cycles for more creative work. Suppose you are successful enough to have to define custom infra at some point. That's good for you. That's a great problem to have.

AI is going to standardize architectures going forward. Providing a simple set of tools in the same code as the logic makes the planner easier for Copilots and reduces the context windows. Terraform and application code have implicit dependencies. Colocating them lets you define explicit dependencies that are more understandable.

Comments URL: https://news.ycombinator.com/item?id=38193315

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Comments URL: https://news.ycombinator.com/item?id=38130614

Points: 1

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Today's ecosystem requires advanced knowledge of system design and still coding abilities.

To democratize model generation we need a more iterative and understandable way of defining intented execution. The problem is this devolves into just coding the damn thing pretty quickly.

The arguments against my point always assume perfect memory of everything this model is consumed. This is the plagiarism position. In reality, some patterns are more common than others and generate a code that looks nearly identical. I can’t speak for the reasons for this, as I’m not familiar with all of the methods. However, I don’t assume that is the current working state or intent of Codex.

The copilot service backed by an army of actual humans wouldn’t be a story at all. Nor would anyone be angry, if an individual offered coding skills as a service, and had gone through the exercise of learning great amount to open source software to do so.

No open source license was written with this in mind. Because previously learning was something only humans could do and no one had issue with sharing that knowledge. Until licenses take machine learning use into account I see no problems with Copilot.

Source cannot be open if you restrict any viewing of it.

I always found imaginating Square's point of view a fun challenge. Seeing a world, I otherwise recognize the same way gives it a whole new dimension.

[1] https://en.wikipedia.org/wiki/Flatland

The goal isn't to always have to do the repetitive reviews. It's to mentor people up so they do them for you eventually.

When you life those juniors up enough for them to mentor the next iteration you start the flywheel. You get to mentor and review people's work who do things at a higher level, and they get to learn to mentor juniors who were in their position. Everyone, even you, get to move up.

Comments URL: https://news.ycombinator.com/item?id=29231725

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Could you have selected some workspaces with lower traffic to migrate first? That would have decreased the load on the primary, potentially speeding up the replication, which is a flywheel to enable more customers to migrate to shards.