Scaler | Backend Engineer | Distributed Systems • APIs • Scalability
Joined December 2025
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Devdeep retweeted
bro asked claude for an office and got a whole GTA side quest 💀
I asked Claude to build an office for the @tavus PALs...
I was not expecting it to build THAT kind of office
Devdeep retweeted
We’re now a family of 350 people on here!
Thank you to everyone who followed, engaged, and supported D3 Bytes. Every single one of you means a lot!
If you’re into tech, backend engineering, databases, or system design, let’s connect and grow together.
350 today. Bigger things ahead.
Devdeep retweeted
Starting a Backend Series from today
57 episodes.
From "what is a server" to shipping a production API.
Node, Express, auth, databases, caching, Docker, CI/CD, all with demos you can code along.
Every episode opens with "what breaks without this." Follow so you don't miss Ep 1.
Everything we'll cover is in the thread 👇
Devdeep retweeted
3D generation is entering its Agent-Ready era. Hyper3D is leading the shift.
I created a production-ready 3D camera using Hyper3D Rodin Agentic Mode.
Instead of manually deciding the workflow, Agentic Mode analyzed the reference, selected the best generation approach, and handled the heavy lifting automatically.
Workflow:
🔹 Upload reference
🔹 Agentic Mode chooses the optimal modeling path
🔹 Generate the 3D camera
🔹 Refine and iterate with natural language
* Parameter Controls -- adjust dimensions and add custom controls for specific parts.
* Animation Presets -- describe a movement or gesture and generate an animation with natural language.
* Enhanced Materials -- modify the material of specific parts while keeping the rest of the model intact.
🔹 Export production-ready results
In this demo, I show the complete process from a camera reference to a fully realized 3D model and the final refined result.
Try Agentic Mode on hyper3d.ai
#Hyper3D #DeemosTech #Rodin #AI3D #agentready #3DModeling #Agent #agenticmode
Devdeep retweeted
The use cases here are only the beginning.
AI that can actually understand how we communicate could unlock so many positive applications.
But as these systems become more capable, safety and responsible deployment become even more important.
There’s so much potential here. We just have to make sure we build it the right way.
Yesterday we previewed Griffin, a Human Interaction Model capable of seeing, hearing, sounding, and looking like a human does. There have been a lot of questions, so I wanted to take a moment to share our thoughts.
By way of introduction: Tavus is a research lab focused on enabling machines to meet us where we are, and to understand the nuances of how we communicate beyond words.
Griffin, our latest model, isn’t publicly available yet. Yesterday’s announcement was a limited research preview to demonstrate what the model is capable of. With AI progressing so quickly, we prefer to share breakthroughs openly and in real-time as we work on a safe public release.
Face-to-face is how we evolutionarily communicate, it carries the most meaning and intent, and we want computers to be able to help with work that benefits from that emotional understanding, expression, and immersion. Some examples of the kinds of use cases we care deeply about:
- A tutor that can build understanding of how a student learns, see exactly when there is confusion or disengagement, and adapt the lesson to fit them.
- A health expert that can answer any questions about your upcoming appointment or prescription, at the pace you want, at any time you need, even on a weekend.
- A language coach that you can practice speaking with, that can correct your movement and pronunciation, and help build confidence to have real conversations
- Or the perfect assistant for everyone, that understands intent, knows how you work and remembers what matters.
We’re working with partners on safeguards and systems for disclosure, as well as inviting discussions with officials around wider regulation and safe use. People will always know they’re interacting with AI, while providing an interface that removes the need to ‘speak computer’.
We believe in a future where computers understand us well enough to make technology more accessible, more useful, and make us more capable as humans. That is the world we want to build, and we understand the responsibility to do so safely.
Devdeep retweeted
3D generation is moving from “generate an asset” → “build and refine the asset.”
@DeemosTech’s Hyper3D Agentic Mode can generate editable 3D models, adjust dimensions and proportions through natural language, add animation, and even combine multiple reference views into one coherent model.
That’s a much more interesting workflow than one-shot generation - you create, talk to the model, refine, and keep building.
If you work with 3D, CAD, games or product design, this is worth checking out.
Devdeep retweeted
Just wrapped up my backend project an e-commerce system, but not the basic CRUD kind. Node.js + Express, JWT auth with refresh rotation, Redis caching + locks, Razorpay webhooks with HMAC verification, atomic stock reservation.
Would genuinely appreciate feedback from other backend devs what's missing, what you'd do differently, what breaks at scale.
Also open to suggestions what's a good next backend project to build?
repo: github.com/devdeepdhariwal/e…
(don't tell me "JS is bad for backend" tell me what a beginner should actually start with instead )
🤖 Made with AI
