TheAnkurTyagi

code reviews take way longer now because you gotta actually read through everything instead of trusting the dev knew what they were writing. Its like the AI is great at the happy path but completely misses edge cases or makes weird assumptions about state...

The real kicker is when someone copies AI generated code without understanding it and then 3 months later nobody can figure out why production keeps having these random issues. debugging AI slop is its own special hell

A very nice explanation with visual interactions of how database works internally. author is a great teacher.

hmmm even at big Fortune 100 size companies there's a lot of vibe coded slop that works well for MVP but will absolutely fall apart under stress and within prod environments once they scale to more users. I've seen this first hand. It doesn't really reveal itself until later when it's much more difficult to fix.

Love the product clean, actionable PR reviews. Can’t wait to see what you ship next.

AI subscriptions I currently pay for: ChatGPT, $20/mo, Claude Code, $20/mo, Cursor, $20/mo, CodeRabbit, $30/mo

We have a soft cap at $500/mo for everyone right now and most devs don’t get close.

I compare them here https://www.devtoolsacademy.com/blog/cursor-vs-windsurf/

Very nice animations.

nice also you can use project-specific structure and markdown files to ensure the AI organizes content correctly for your use case. we are using it on 800k lines of golang and it works well. https://getstream.io/blog/cursor-ai-large-projects/

thanks for the feedback... I'll update the post but check with your founder (Paul).

I messaged Paul on Twitter on Sunday before even sharing the post to get feedback if any as I don't want any confusion like you had last time on Reddit.

and I genuinely like both databases and other awesome developer tools.

pls show some fighting spirit.

PS- I'm no longer working with Neon.

happy to show the bank statement :)

how it's different from https://www.findmicrosaasideas.com/

why not? both offer database as a service and under the hood using Postgres.

fun fact - this blog is also powered by neon

Here’s a quick rundown of the tech stack:

Framework: nextjs Styling: tailwindcss Database: prisma paired with neondatabase MDX Support: I love writing with Markdown Auth: ClerkDev—an absolute game-changer. Animations & Icons: Framer Motion and Heroicons. UI Components: Radix UI

github - https://github.com/tyaga001/devtoolsacademy

yes please add issues here as it's an open-source project I started and would love some contributions from the community to keep it going. I'm hungry for ideas and write about cool dev tools https://github.com/tyaga001/devtoolsacademy

I’m a big fan of Neon postgres. It’s pretty much unbeatable value for the price. The documentation is good and multi-tech stack friendly and I created a repo in which I added all the awesome links about Neon Postgres - https://github.com/tyaga001/awesome-neon and wrote a tutorial https://www.freecodecamp.org/news/build-an-invoice-saas-app-...

What key features make Tau a compelling self-hosted PaaS alternative?

How does CopilotKit compare to other frameworks or tools for building AI assistants?

sounds like a great project. How do you handle performance with large message sizes?

IMO, think of it like switching from a bicycle to a car. The bicycle might be faster in certain conditions, but the car offers more features and flexibility for different terrains. Similarly, Neon’s database branching feature is like adding all-terrain capability.

easy to slam others but I don't see what's bizarre about the article. It highlights a successful customer story where Neon (https://neon.tech) played a significant role in improving their db management with its db branching feature. Yes, caching and pooling helped, but Neon made their testing and development much faster and efficient and it's not easy to write such detailed articles. why not any constructive feedback which can help them?

fair point about the slower response times But Neon's not just any Postgres. They've got that whole serverless angle, which can be a game-changer for scaling and costs. Maybe the team's still figuring out how to optimize for that setup? Plus, with Neon, they probably ditched that whole SQLite-in-git headache.

ohh wow but why switch away from PlanetScale though? and I think Supabase also serve a dedicated Postgres DB (that is powering the BaaS) and we can use Supabase just for database hosting as well.

yay i heard from someone in my network but I don't think they are serverless Postgres as IMHO "Postgres is all you need, even for vectors" checkout this post I found in a discord https://anyblockers.com/posts/postgres-is-all-you-need-even-...

nice to know but when you say "challenging real-world tasks" any use cases?

are you automating the end to end RAG pipeline?

This is great. we used Qdrant vector DB for an end to end automation for our AI RAG app at https://github.com/rnadigital/agentcloud, but very excited to see you are making a successor. any ETA when it would be ready to use and any quickstart guide? Maybe I can help in writing a blog as well.

Hello everyone,

Introducing AgentCloud, an open-source project focused on building agents and chatbots.

What is Agent Cloud?

Agent Cloud enables companies to host their own AI App platform. (imagine a self hosted GPT builder platform with extra goodies!)

There are two types of apps companies can build and deploy to their employees:

1- Conversational Chat Apps 2- Process Apps

Key features of Agent Cloud:

RAG Pipeline: Seamlessly embed 260+ datasources for comprehensive data access.

Conversational Apps: Build your own GPTs with ease.

Multi-Agent Process Automation: Streamline workflows with CrewAI.

Tools: Empowering you with the tools you need to succeed.

Teams & User Permissions: Collaborate effectively and securely.

Easy Setup: Get started in no time with Docker and our install.sh script.

But that's not all! Under the hood, Agent Cloud utilizes an impressive open-source stack:

- Airtbyte for ELT pipeline - RabbitMQ for message bus - Qdrant for vector database

Here is a our docs (https://docs.agentcloud.dev/documentation/get-started/introd...) and GitHub (https://github.com/rnadigital/agentcloud)

We've written another comparison blog post recently.

Agent Cloud vs CrewAI - https://www.agentcloud.dev/blog/agent-cloud-vs-crewai-a-comp...

As always, we would love to hear your feedback!

Talk to your data we're building Agent Cloud which is an open source platform enabling companies to build and deploy private LLM chat apps (like chat GPT), that can enable teams to securely talk to their data.

Agent Cloud is like having your own GPT builder with a bunch extra goodies. The GUI features

1) RAG pipeline which can natively embed 260+ datasources

2) Create Conversational apps (like GPTs)

3) Create Multi Agent process automation apps (crewai)

4) Tools

5) Teams+user permissions. Get started fast with Docker and our install.sh

and it's open source https://github.com/rnadigital/agentcloud

Takeaways and Things I’ve learned from Dmytro:

- Embrace Building in Public: Dmytro's transparency in sharing his development process and challenges has not only helped him solve problems but also attracted a community of supporters and customers. This approach can be a powerful tool for growth and engagement.

- Leverage Your Strengths: Dmytro capitalized on his expertise in API engineering, recognizing that his skills were better suited to backend development rather than UI/UX. Understanding and playing to your strengths can lead to more successful and manageable projects.

- Simple Tools Can Be Effective: Despite the vast array of sophisticated tools available, Dmytro uses a straightforward set of tools like Google Sheets and Pirsch Analytics. This simplicity allows him to focus on what truly matters—building and improving his product.

- The Importance of SEO and Product Positioning: Focusing on SEO and refining the product's positioning were crucial in attracting the right customers and scaling the business. These strategies can significantly impact a startup's visibility and growth.

- Customer Satisfaction Over Complexity: Ensuring that your service or product meets customer needs is more important than the complexity or breadth of the tools you use. Customer satisfaction is key to retention and word-of-mouth referrals.

- Focus Is Key: Dmytro advises focusing on one product, one ideal customer profile, and one marketing channel, especially in the early stages. Spreading yourself too thin can dilute your efforts and hinder growth.

- Community Support Is Invaluable: The support from the build-in-public community and platforms like Indie Hackers has been instrumental in Dmytro's journey, highlighting the importance of community engagement and support networks for entrepreneurs.

- Plan for Growth: Dmytro's goal to reach $10K MRR by the end of 2024, by focusing on SEO and reducing churn, shows the importance of setting clear targets and planning for the future.

Each story is unique and full of challenges, triumphs, and insights, offering a rare glimpse into the personal and professional lives of people who write the software that shapes our world.

Thanks, Just one last question from my side- For the self-hosted version of Revert, can you provide more insights into the level of technical expertise required to set it up within an organization's infrastructure?

And Additionally, what kind of support and assistance does the Revert team provide to facilitate this setup? If a client needs it.

Looks promising, I've 2 questions.

1- How does Revert ensure the security and privacy of data while facilitating integrations through its unified API, especially when dealing with various third-party applications and services?

2- The platform mentions a 'Unified Data Model' and 'Standardised data formats and schemas.' Could you elaborate on how these aspects help in simplifying the integration process across different CRMs and what measures are in place to handle discrepancies or inconsistencies in data formats between various integrations?