ryancoleman

GOAT (Generative Offensive Agent Tester, arXiv:2410.01606): an attacker LLM holds an in-context toolbox of 7 jailbreak techniques and reasons in an Observation/Thought/Strategy/Reply structure each turn, sending only the Reply to the target. Now available in an evals SDK for any agent harness SDK.

Achille and Soatto (Amazon/AWS) model AI reasoning agents as compute-capable stochastic dynamical systems and ask: can chain-of-thought reasoning solve any computable task? They show the key resource is inference time and that training data can exponentially reduce the time needed.

Found via https://www.amazon.science/blog/intelligence-isnt-about-para...

That's basically how it works! (with human authored functions that validate the result, automatically providing feedback to the LLM if needed)

The initial version on GitHub does not implement caching or memorization but it's possible and where the project will likely head. (FYI I'm on the Strands Agents team).

They're handy for situations where it would be impractical to anticipate the way your input might vary. Like say you want to accept invoices or receipts in a variety of file formats where the data structure varies but you can rely on the LLM to parse and organize. AI Functions lets you describe how that logic should be generated on-demand for the input received, with post-conditions (another Python function the dev write) which define what successful outcomes look like. Morgan wrote about the receipt parser scenario here: https://dev.to/morganwilliscloud/the-python-function-that-im... (FYI I'm on the Strands Agents team)

https://www.lambci.org ?

I'm excited to see what sorts of CloudFormation templates people have lying around or which previously shared templates people find interesting.

To continue the show and tell part of Show HN, here are a few examples that caught my eye.

This example architecture that meets the Australian Cyber Security Centre’s Information Security Manual for the Protected classification level. It includes patterns you can borrow for three types of private subnets, AWS KMS-based encryption, and AWS WAF firewall protection. https://www.stackery.io/registry/?repo=https://github.com/aw...

Maybe you want to go back in time to 2019 when our problems involved how to construct serverless data lakes. If so, AWS Samples has you covered with this example which helps you think about both data ingestion and storage across several services. https://www.stackery.io/registry/?repo=https://github.com/aw...

I've seen a lot of shares of the serverlessland patterns library, including this deceptively simple pattern aka the "fan out" for managing data from kinesis streams. https://www.stackery.io/registry/?repo=https://github.com/aw...

Someone shared the DataDog template for deploying their integration, which you should scope the IAM Role to your resources before you deploy it, but it’s wonderful to see vendors providing CloudFormation templates for their stuff. https://www.stackery.io/registry/?repo=https://github.com/Da...

I see lots of shares from the consultancy Widdix. They focus on modular patterns that incorporate production-ready configurations, like this one for running container services in ECS. https://www.stackery.io/registry/?repo=https://github.com/wi...

Finally, if you’re feeling nostalgic for winter, this example from Symphonia is a lab for benchmarking Lambda cold starts for Java runtimes so that you can better understand how they behave and plan configurations accordingly. https://www.stackery.io/registry/?repo=https://github.com/sy...

I continue to be surprised by the so-called "S3 Bucket Negligence Award" which feels like the intersection of IAM and S3 configuration ugliness that result in so many public horror stories like: - https://www.upguard.com/breaches/attunity-data-leak - https://www.lastweekinaws.com/newsletter/reinforce-meant-lea...

For example, this Ghost + Gatsby tutorial. https://www.stackery.io/registry/?repo=https://github.com/st...

Developer experience for serverless is such a pain point, spot on. AWS SAM has tackled some of the IaC modeling problem (on top of CloudFormation which is a mature choice) and they've had a crack at the local iteration (invoke Lambda function or API Gateway locally with connectivity to cloud services).

It's a little incomplete, missing some of the AWS IAM automation that makes local development smooth, environment management for testing and promoting changes, and some sort of visualization to make architecture easier to design as a team.

I work for a platform company called Stackery which aims to provide an end-to-end workflow and DX for serverless & CloudFormation. Thanks for comments like these that help identify pain points that need attention.

I really like Ghost https://ghost.org/

It's more for prose than ecommerce but it's really pleasant to use and great for headless through its GraphQL interface.

I recently wrote a tutorial on how to use it with Gatsby & AWS serverless infrastructure so that everything is self-hosted but without the overhead of operating servers. https://docs.stackery.io/docs/tutorials/jamstack-ghostgatsby...