# WeWeb AI - My few thoughts. and suggestions for AWS Bedrock
**URL:** https://community.weweb.io/t/weweb-ai-my-few-thoughts-and-suggestions-for-aws-bedrock/19044
**Category:** Ask us anything
**Tags:** weweb
**Created:** [July 1, 2025, 9:19pm UTC](https://community.weweb.io/t/weweb-ai-my-few-thoughts-and-suggestions-for-aws-bedrock/19044 "2025-07-01T21:19:50Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@Zacharyb](https://community.weweb.io/u/Zacharyb)
#### Post date: [July 1, 2025, 9:19pm UTC](https://community.weweb.io/t/weweb-ai-my-few-thoughts-and-suggestions-for-aws-bedrock/19044/1 "2025-07-01T21:19:50Z")
Hello ! , just a few thoughts (with english correction so it’s readable ahah)
First off, it’s great to see WeWeb is on AWS Bedrock. That’s a solid strategic move that simplifies the tech stack. For what it’s worth, Claude is also a very capable model for coding, so we’re in a good position.
With that foundation, here’s a quick list of expert recommendations to elevate the implementation:
- **Enhance user-side transparency:** Give users clear visibility into which model is being used, how it’s being used, and a simple way to track their credit costs.
- **Activate Guardrails:** Implementing AWS Guardrails should be standard practice to enforce responsible AI policies from the start.
- **Leverage cost-effective models:** The current prompt routing (no Sonnet 4) is a smart trade-off. For most tasks, Sonnet 3.5 and Haiku are the cost-effective workhorses.
- **Orchestrate complex tasks:** Implement a routing layer to manage multi-step workflows. This would allow for flexibly integrating the best model for the job, whether it’s Sonnet 4 for heavy lifting or specialized embedding and rerank models.
- **Implement caching & long-term memory:** Leverage the native AWS toolset to build a robust caching layer and long-term memory, which is crucial for reducing latency and managing costs.
- **Establish clear AI governance:** This is key for getting explicit user agreement on data usage. It not only builds trust but also allows WeWeb to unlock the full potential of its AI features.
- **Build a knowledge base:** Setting up a dedicated knowledge base with a solid Retrieval-Augmented Generation (RAG) pipeline is a game-changer for agent accuracy.
- **Optimize AI spend:** The current AI cost is unsustainable. Aggressively optimizing this spend has to be a critical focus.
…and that’s all I’ve got, starting to be sleepy
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### Author:  [@Agustin\_Carozo](https://community.weweb.io/u/Agustin_Carozo)
#### Post date: [July 2, 2025, 2:16pm UTC](https://community.weweb.io/t/weweb-ai-my-few-thoughts-and-suggestions-for-aws-bedrock/19044/2 "2025-07-02T14:16:57Z")
Hi Zach, thank you for your feedback!
Would you mind creating a feedback ticket so our dev team can sit down to analyse it?
Thanks 🙏
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