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Infrastructure as Code is solved. There's no longer any excuse for a service not to have it. Here's a walkthrough of Alchemy's automated flywheel that generated 100% coverage for both AWS and Cloudflare. 1000s of Resources and Bindings, zero slop.
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in the next version of Porffor, the basics of Effect v4 works
Effect v4 is here. One ecosystem. Zero dependencies. The next chapter of Effect and the foundation for building reliable software and AI agents in TypeScript.
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We all know that the @foldkit, @alchemy_run, @EffectTS_, and @Cloudflare stack is GOATed but what name should we give it? Reply with your own suggestions
20% FACE
71% CAFE
9% Something Else
258 votes • Final results
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Was thrilled to speak about @alchemy_run at the Effect 4.0 release last night. Great event and huge milestone for the @EffectTS_ team.
Effect v4 is here. One ecosystem. Zero dependencies. The next chapter of Effect and the foundation for building reliable software and AI agents in TypeScript.
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Introducing @yielded/auth, a new effect (v4)-based auth library. It's infinitely customizable, it can manage your db schemas, or you can bring your own, or you can use whatever sql adapter you want or even reimplement any func. github.com/yielded-dev/auth
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Effect runs in production at companies of all sizes, including large enterprises that bet their products on it. 43.9M weekly npm downloads, with projects like @alchemy_run and @foldkit building on Effect for cloud infrastructure and frontend development.
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Effect v4 is here. One ecosystem. Zero dependencies. The next chapter of Effect and the foundation for building reliable software and AI agents in TypeScript.
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the people have spoken Alchemy is 🔥
Replying to @stolinski
Any frontend framework. But use Alchemy
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Replying to @stolinski
i haven’t done a ton of frontend work this year, but alchemy + your deployment platform of choice + Effects Http api platform - @RhysSullivan might have stronger opinions esp around frontend stuff
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If you haven’t tried @alchemy_run yet you’re ngmi
i am once again telling you how good @alchemy_run is i sent off a prompt telling my agent to improve performance and to use Alchemy to measure the impact, and woke up to a reviewable stack of PRs with performance improvements the verification loop is so good
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sam retweeted
i am once again telling you how good @alchemy_run is i sent off a prompt telling my agent to improve performance and to use Alchemy to measure the impact, and woke up to a reviewable stack of PRs with performance improvements the verification loop is so good
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sam retweeted
I don't hate this? smaller than everything else too elm: 350 loc react19: 350 loc solid2: 268 loc foldkit: 381 loc experiment: 160 loc keep in mind this experiment and foldkit are the only ones that have to pay the effect verbosity tax; and this is still more than half the size of react 19
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sam retweeted
alchemy home lab IaC with durable effect layers 🧙‍♂️
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There's a reason Cognition bought Dioxus. If AI is writing all the code and can get the job done equally well in ANY language, then obviously the most performant language wins. Adding threads and structs to JS does not fix this.
JavaScript was never designed for the server. If that doesn't change soon, JavaScript on the server will be replaced by Rust. The fix needs to happen in the engine. Sound types. Ahead-of-time compilation. Threads with shared objects.
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"Factories as code" - is he talking about @alchemy_run? 😏
Software factories should be built on an infrastructure stack that is open, composable and defined in code: Open == works with any model, agent and hosting configuration Composable == you can adopt part or all of the stack, and use the pieces however you want Defined in code == factory state is versioned, testable, and revertible Let’s break this down layer by layer: Factories-as-code Define your agent infrastructure in a version-controlled file like factory.yaml: agent configuration, runners, repository access, external integrations (Slack, Jira), webhooks (Grafana, Sentry) and automation triggers (crons, taskboard changes, PR updates, etc). The format matters less than having a code-based approach that allows versioned changes to the factory definition. Versioning enables benchmarking, A/B testing and rollbacks. It’s Terraform for factories. Data and context One level up sits the Context Layer. It includes internal MCPs and CLIs, agent memories (blob storage, skill files), conversation logs, access logs, and agent rules / skills. If you use a third-party context layer, you should be able to store all its data on your infrastructure. No outside provider should train on this data. ZDR is a must. Compute Next is the Compute Layer, where your agents run. Centralized runs need remote dev environments, likely defined in Docker or k8s. They should be pausable and resumable, with state portable across machines. You should also be able to connect computer use models to test the apps agents build in your remote dev environments. This is useful for reproduction, verification and prototyping. Inference The Inference Layer should support any model and agent so you can evolve and test your factory configuration to optimize quality, cost and speed. It should support frontier and open-weight models plus multiple agent harnesses. Improvement An important part of any factory is the Improvement Infrastructure, which ensures software gets built at higher quality and lower cost over time. Start by tracking DORA metrics like cost-per-PR and qualitative metrics like code quality and efficiency using LLM-as-a-judge. Once you have these metrics, close the loop: Self-improvement: agents automatically find failure points and suggest skill improvements. Benchmarking: test suites with varied configs measure how the model and harness combinations perform on real work. Orchestration Your factory needs a control plane to launch agents, manage crons, drive work to subagents, and provide live sessions for human steering. Access Work enters and leaves through UIs, a direct MCP, and third-party surfaces like code forges and knowledge work tools. All access points should use unified APIs for launching work, monitoring progress, updating the factory definition, and more. This benefits humans and agents. - As we move to automated development, think of software factories as an Infrastructure Stack. If you are exploring this approach, we would love to chat.
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Your infrastructure and runtime code are coupled whether you like it or not. No shade if you want to keep them separate, but the best way to actually manage this coupling is with Context.Service and Layers. Not by drawing a hard line between infra and runtime code.
Is there any thought towards alchemy usage that doesn’t couple infra and runtime code? Personally I prefer the separation, and so far mostly am able to get that by having the alchemy runtime stuff just thinly wrap my entry points But I see things like the stripe provider or better auth where it seems I have to buy into both the infra and runtime completely. Not that it’s bad, just curious if there’s any thought towards the experience for those who don’t do so
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Michael is much better at this me. Hyped for the makeover.
benchmarking @alchemy_run for the new website has made me realize how much overhead github actions have. alchemy does deploy, test, destory in ~25 seconds and there is like 0 shot thats under a minute on github. new website teaser 👀
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than* 🤦‍♂️
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Rhys is cooking with @alchemy_run. If you need a reason to try alchemy, it's the speed of verification loops. Agents can TDD whole services that work well and have sensible code structure thanks to Alchemy's Effectful Runtime abstraction.
I literally did this exact scenario twice today
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sam retweeted
Replying to @samgoodwin89
choosing alchemy as a core foundation on @op0ai is probably a top 3 decision long-term. so far, the dx and velocity has gone thru the roof. like i wont go over the top and say alchemy in and of itself, adopted, will give you superpowers but it lowk will - or in my case with opzero, made it easier to build extremely durable tooling around the stack that WILL move you way faster. and this applies to effect in general imo.
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What I like about @alchemy_run v2 is it looks like it's taking us towards application-defined infrastructure. Which is a step beyond infrastructure-as-code (Pulumi etc, sst, Alchemy v1) and framework-defined infrastructure (Next wrt Vercel).
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