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Merry Christmas Jonathan Ross (Groq s Founder)! $20B will buy a lot of holiday cheer!

Today, Groq announced that it has entered into a non-exclusive licensing agreement with Nvidia for Groq s inference technology. The agreement reflects a shared focus on expanding access to high-performance, low cost inference.

As part of this agreement, Jonathan Ross, Groq s Founder, Sunny Madra, Groq s President, and other members of the Groq team will join Nvidia to help advance and scale the licensed technology.

Groq will continue to operate as an independent company with Simon Edwards stepping into the role of Chief Executive Officer.

GroqCloud will continue to operate without interruption.

Source.

Hi, I am launching my first product on PH soon - next couple of hours soon :-) I am so excited about this holiday launch special and hope to gain some great feedback from lovely PH community in holiday spirit too!

Lattice enables smart AI systems decisions. When building AI systems there are so many decisions to take. What model to use, which vendor to use for GPUs, which framework works best with my use case, how does pricing compare across different permutations, and so on. Then there are sensitive business requirements which are usually under NDA and cannot be shared with vendors with ease. Lattice enables startup and enterprise AI labs to self-serve this research and take high quality decisions within the privacy and comfort of own laptop or private cloud.

Hello lovely people! Hope you are enjoying the holiday season. Launching during holidays is so much fun, in between awesome food, supportive friends and family! I have ticked all the boxes, ran 1,000+ tests on the product, recorded the walkthrough video, wrote the product features blog guiding uses step by step. Now on to doing some social posts, though I don't have huge following, still no harm sharing on other channels :-)
I will continue to share my builder and launch journey here. What worked, what did not, what could be better. So please watch this space. Hope this journey helps and inspires others - in case Lattice makes it to top 10 for a brief moment :-)
Of course feel free to share any last minute tips. I will do my best to follow.

Hi PH friends! I am the builder launching Lattice today...

Just like me, I am sure you and your customers are constantly challenged to keep pace with changing AI infra, model, tooling landscape, while having to make high quality (and costly) decisions, fast!

I am building https://www.navam.io/ sharing practitioner guidance on how to build like the best AI startups including seven fully functioning projects, ready to fork, easily customize, and ship in days!
Welcome your feedback and guidance on:
1. Which AI projects you would like to see me make next?
2. How can I make these AI projects more reusable and extensible for you?
3. What specific AI practitioner guidance you are seeking?

I m seeing a noticeable shift in job descriptions lately.

There s a growing demand for Product Engineers (or Product Builders) people who can take a feature from spec all the way to shipping.

Sure, a lot of this momentum comes from software engineers using AI to speed up their workflow

but I m convinced PMs and Product Designers are going to step into these roles too.
Strong product sense, design intuition, and prioritization are becoming just as important as deep engineering knowledge.

I am building Navam Sentinel in public as a reference AI project source available at official GitHub repo. The problem I am addressing is multi-agent regression testing for quality, capabilities, efficiency, and other criteria which matters. I want to do so with least cognitive load on the end user who is a busy developer, engineer, scientist in an AI lab. The project is a reference in two ways, 1) how to build a multi-agent AI system solving for AI-ops automation using visual primitives, 2) how to context engineer AI code generation for a complex multi-platform desktop AI app across tens of thousands of lines of code, hundreds of tests, multiple releases per day.

Hello everyone, recently I am refactoring old AI codes in hot spots. I used both Claude Code and Codex to quickly implement the feature at that time. It works but when I look into the logic today, it introduces too much unnecessary complexity (a lot of helper/manager/try-except). Although I have manipulated CLAUDE.md (emphasizing KISS principle, introduce Linus https://gist.github.com/iiiyu/4c... ), the code agent still try to add entropy on the whole project. I can understand the code LLM is trained to program defensely, but if I do not review carefully and really understand the logic, the project quickly becomes hard to maintain. Now every week I will leave 1 day to write codes without AI to clean the whole project for longer future.
Do you have similar experiences or solutions to share?

Hey folks Ryan here

I ve been chatting with a bunch of vibe-coding builders lately, and everyone keeps saying the same thing:

Prompts get you UI fast but the moment things get real, everything starts to fall apart.

I ve noticed that my workflow has changed completely over the last year. I rarely start a new project with a blank file anymore. Instead, I pick a template, reuse snippets, or let an AI helper suggest the structure and then I just vibe my way through the build.

It s faster, but sometimes I miss the old blank screen energy, when every line felt handcrafted.

I m curious how others here approach it:

Do you still prefer to build from scratch?

Hey PH family.

Been part of this community for years now, and if there's one place to talk with builders, this is it.

AI dev tools are evolving crazy fast , every few weeks there s a new must-try for vibe coders.

Some people are building full products with @ChatGPT by OpenAI and @Replit , others swear by @Cursor and @Claude by Anthropic , and a few are mixing @Lovable + @v0 by Vercel + @bolt.new to ship apps in record time.

I ve been refining my own vibe stack lately, trying to find that sweet spot between speed, control, and creativity.
It made me wonder ,what does your setup look like right now?

I am building Navam.io in the open source. My mission is to offer indie hackers, bootstrapped startup founders with working white label AI products which they can easily fork, vibe code to make their own, and rapidly ship.

I have open sourced four products so far, representing 177K+ lines of code, 100% vibe coded themselves. These are products my customers can easily install from GitHub or PyPi, evaluate themselves how they work, read entire code base, docs, prompts, release histories, before they decide to purchase a commercial license at a reasonable one time fee. They can then read our growing blog with 40+ long form articles documenting Navam's vibe coding journey to follow along and become super productive themselves.

Each white label product represents 6+ months of trial-and-error, architecture decisions, and production refinement all the hard lessons learned building real multi-agent and AI systems. Now founders can fork the working code, skip the debugging hell, ship in days. Would love to hear feedback from the PH community. What else can we build and share? What pain points can we help solve? Any guidance and tips for a successful PH launch for Navam would be most welcome as well!

Hey, I m Navam, living in San Francisco, building in open source, production-ready multi-agent AI white label products for indie founders and small teams. I would love to enable my customers to just Fork. Vibe. Ship.
What got me here? I have been coding for years, across stacks and frameworks. I am a lazy engineer, follow DRY (Don't Repeat Yourself) to its limits, so I love automating my developer tooling. I also enjoy exploring latest frameworks, tools, and models, whatever gets me closer to that 10X engineer promise, faster, easier, at lowest cost!
Enjoying the PH community already, hope to learn some new tricks and share some of my own as well to benefit others.

Had a fascinating discovery call yesterday. Founder showed me their SaaS - built entirely with Cursor in one weekend. Stripe payments, auth, admin panel. Actually works great, they're at $11k MRR.

Then they opened the codebase.

The @v0 by Vercel team recently dug into industry trends to publish the first State of Vibe Coding report.

My key takeaways:

1. Everyone can build: 63% of vibe coding users are non-developers, generating UIs (44%), full-stack apps (20%), and personal software (11%).

2. Adoption is everywhere, with significant adoption rates in APAC (40.7%), Europe (18.1%), North America (13.9%), and LATAM (13.8%).

3. 92% of US developers use AI coding tools every day

4. 30% of new code at @Google is generated by AI

5. 25% of @Y Combinator startups rely on AI-generated code

6. Rapid expansion has a cost. Vibe coding apps keep hitting vulnerabilities: exposing secrets, access misconfigurations, hardcoded credentials.

7. The future: going mainstream or hitting its sweet spot in working MVPs, the vibe coding trend is here to stay, and it's happening now.