#Developer

I'm 21. Solo founder. Looking to connect with more developers & founders .

Over 380 AI devs wanted me to try their AI games Every week I will make post so you can shill your AI games and I will genuinely test a bunch of them and make a video. Can AI developers make good games? Lets find out! Timestamps and Game links below.

10,000 followers!! 🥳 I still remember when I had just 200, asking for advice on how to grow my account as a founder. It took me 4 months to get just over 50,000 views. I was questioning what I was posting and whether any of it was making a difference. Then developers started reaching out to try what we were building. People I met on X became our top users and strongest supporters. It took 6 months to go from 200 to 1K. Now, it's taken 6 months to go from 1K to 10K... Pretty crazy :) Posting on X has changed the course of our company, forever grateful for the community we've found on here. Let's keep building and shipping. Thank you guys, InstaBox to the moon!!

Opening the model is one thing. Opening the creative process is another. SenseNova 6.8 Code2Video does both. The open-source model turns creative prompts into videos by writing editable code. It can reconstruct the structure and animation of reference videos, then modify the existing source through multi-turn conversation. SenseTime is releasing the model weights alongside creation Skills, demo prompts, source code, and full creation traces, giving developers access to both the result and the process behind it. The example below was officially produced by SenseTime with SenseNova 6.8 Code2Video. See what is open and inspect the workflow on GitHub:

A warehouse, a shopping centre, or even a local car park could become valuable 3D data. The challenge has always been getting that information captured without relying on expensive equipment and specialist teams. @vangrid_io is taking a different route by opening real-world data collection to Android users through its live mobile app. The idea connects people who need spatial data with people who can capture it. Buyers post specific locations they want modeled and offer bounties for the work. Nearby operators use their phones to record the requested surroundings, while the submitted footage is reviewed before the finished 3D model is delivered. Capture evidence is also recorded onchain. This turns an ordinary phone camera into a potential tool for contributing to the spatial data economy. For developers working on physical AI, robotics, or digital environments, access to real-world 3D information can be useful. For operators, the network creates a way to take on mapping requests without buying dedicated scanning hardware. Of course, payment depends on available jobs and whether the footage meets the buyer’s requirements. Simply installing the app doesn’t guarantee earnings. The bigger question is how much of the physical world could be mapped if more people had a reason to capture it. Which location in your city would be most useful to have in 3D? @vangrid_io

Project is stable... as long as the tester is still holding it 😅🚛 #Developer #Tester

An Anthropic engineer reveals how he earns $350K–$950K: “I know how to build harnesses. 99% of developers still assemble multi-agent systems by hand, then struggle to keep them running reliably. I build systems that execute loops, operate inside sandboxes, and transform past logs into new skills. Same model. 10x more reliable agents that continuously improve, even while you sleep.” Opus 5.5 → Agents → Harnesses → Loops → Graphs In a short workshop, he explains how to build this system from the ground up: Step 1 → Control loops, context, and sandboxed tools with a harness Step 2 → Keep the model separate from its tools to generate the first token 60% faster Step 3 → Run agents on servers and recover from crashes using execution logs Step 4 → Handle failures with retries and replays instead of rebuilding everything from scratch Step 5 → Convert past execution logs into memories that help agents improve over time Anthropic calls this process “dreaming.” Most developers spend weeks piecing these systems together manually. This workshop shows you a more efficient approach. Bookmark this and watch it.

The company I work for is hiring AI Developers with 2-5 YOE If you're looking for a switch, DM me for a referral I'll refer you, you might get a new job, and I'll get a referral bonus. 🤝😭 Let's help each other out. 💀

Day 16 of building my SaaS in public ☕💻 Locked in today: polishing our backend and clean UI for HissaFlow (The Commitment Tracker). Come hang out, chat, or co-work with me live: 🔴 #buildinpublic #indiehacker #developer #100DaysOfCode

GOOD MORNING DEVELOPERS ⚡️✨ AI can understand words. But can it understand the world it is supposed to operate in? Imagine a robot entering a warehouse, navigating a crowded street, identifying a building entrance, or moving through an unfamiliar environment. Before it can perform these tasks effectively, it needs something essential: accurate information about the physical world. This is the problem @vangrid_io is working to solve. 🧠 WHAT IS @vangrid_io ? @vangrid_io is building a decentralized spatial data network designed to give Physical AI a better understanding of real-world environments. While traditional AI learns from digital information, robotics and autonomous systems also need detailed, ground-level representations of physical spaces. The challenge is that collecting this information can be expensive, time-consuming, and difficult to scale. Vangrid takes a different approach: turning everyday smartphones into tools for collecting spatial data. People capture real environments, those recordings are reconstructed into 3D models, and organizations can commission the specific locations and information they need. The bigger vision is to build a distributed spatial intelligence layer that connects human contributions with the growing demand for real-world data. 🌍 HOW DOES IT WORK? The system brings together three important participants. 1. Human contributors People use their smartphones to record physical environments, from buildings and warehouses to loading bays, walkways, and other locations. Instead of requiring every data collector to own specialized scanning equipment, Vangrid makes use of devices people already have. 2. Organizations that need spatial data Businesses and other requesters can publish funded bounties describing the locations they need captured and the rewards available. Contributors submit recordings, and the requester selects a suitable submission. Accepted captures can then be reconstructed into usable 3D models. This demand-driven approach helps connect data collection to specific requirements rather than generating activity without a clear purpose. 3. AI agents One of Vangrid’s most interesting ideas is enabling software agents to request physical-world data programmatically. An agent can identify a need, fund a capture request, and coordinate with a human contributor who can visit and record the environment. It creates a compelling connection between digital intelligence and physical action: AI identifies the need, humans capture the world, and the resulting data helps power intelligent systems. 🔐 WHY BLOCKCHAIN MATTERS Collecting data is only half the challenge. Organizations also need confidence in where that data came from and whether its recorded fingerprint has been altered. Vangrid uses cryptographic provenance to make capture records more transparent and verifiable. Its system groups capture fingerprints into Merkle trees and anchors the resulting records on Base through the Ethereum Attestation Service. This gives observers a way to verify that a capture fingerprint belongs to an attested record. The objective is to make spatial data more auditable rather than relying entirely on trust in the party providing it. Privacy is another important consideration. Vangrid documents an approach that blurs faces and vehicle registration plates on the recording device before footage is uploaded. 💰 TURNING REAL-WORLD DATA INTO AN ECONOMIC MARKET Vangrid connects spatial data collection with funded demand. Contributors receive payment when their submissions are accepted, subject to the bounty’s conditions and platform fees. The public bounty board currently displays more than $675,000 in settlements, providing a measurable indication of activity within its marketplace. @vangrid_io has also reported a $9 million seed funding round involving investors including HashKey Capital, Borderless Capital, Capital, and Animoca Brands.

A smartphone video can show a place, but a structured 3D reconstruction can make that place much more useful for Physical AI. That difference is central to what @vangrid_io is building. The workflow starts with a real location and a funded bounty. A requester specifies the capture they need, a contributor records the environment with a phone, and the submitted capture goes through a review process before the accepted work is turned into a 3D deliverable. What stands out to me is how the product separates the original footage from the result that the buyer needs. The buyer receives a watermarked preview to evaluate the submission, while the raw recording remains with the contributor rather than becoming an unrestricted download. After acceptance, Vangrid reconstructs the environment and can provide the resulting 3D model in formats such as GLB or ZIP. Reconstruction takes time, and the quality of the original capture still matters. Missing angles or incomplete coverage can limit how useful the final model becomes. The onchain side gives this workflow another important component. Bounties are funded in advance through escrow on Base or Arc, and the payment process is tied to acceptance rather than relying only on an informal promise between strangers. This matters because spatial data needs more than collection. Buyers need a usable deliverable, contributors need clear payment conditions, and both sides benefit from a process whose activity can be checked. That is why @vangrid_io is worth evaluating as infrastructure rather than just another mapping app. It connects location specific requests, human data collection, 3D reconstruction, and onchain settlement into one workflow. For Physical AI developers, the real question is whether the resulting data is accurate and relevant enough to support their applications. The ability to request and verify a capture is a meaningful first step toward that goal. Explore the product and current bounty activity at

1/ Excited to announce our new company Particle This is our first step in a series of models focused on developers. With particle-1, we focused on token efficiency and managed to keep parity in performance while using ~45% fewer tokens. Live now:

Good morning, CT ☀️ 🚨 What if developers didn't have to build every data integration from scratch? Imagine you're building a Web3 app that needs information from an existing website. You need to define where the data comes from and which information your app should retrieve. Doing that setup again for every project can create unnecessary work. This is where @PrimusLabs’ zkTLS data templates become useful. 🔹 Start with a template. Primus provides predefined templates that represent how data should be requested from supported off-chain sources. 🔹 Customize when needed. If your use case is different, developers can create their own templates through the Primus Developer Hub. 🔹 Use the template in your app. Once a template is selected, developers can use its template ID in their application to interact with Primus network attestors. Think of it like using a form that's already organized for a specific purpose instead of designing every field from scratch. The template gives developers a reusable starting point for connecting to data sources. They can focus more on what their application needs to do with that data. One important detail: a data template isn't proof by itself. It defines the data request structure; zkTLS handles the verification process. That's how reusable data templates can make building with off-chain data more practical. 🔗 Official source: @PrimusLabs #PrimusLabs #zkTLS #Web3 #DeveloperTools

Nearly 1,000 Palatial generated assets are now part of SimReady Central, NVIDIA's new open library of SimReady OpenUSD assets on Hugging Face. We're excited to contribute to this open ecosystem alongside @standardbots, @LGUS, @FRANKAROBOTICS, @Universal_Robot, and other industry partners, making it easier for developers to build environments for robot training and evaluation. Explore SimReady Central: Read about our assets:

Made a few more friends today 🎉🎉 #connect #developers #developer

Developers be honest. Is it still worth learning how to code in 2026?

digging into @vangrid_io and found out they have a solid foundation Jensen Huang called it the “chatgpt moment for physical ai” at CES 2026. but the less obvious part of this shift is what happens after the models get smarter. at GTC 2026, Nvidia introduced its physical ai data factory blueprint to automate data curation, generate synthetic scenarios and evaluate training data. that tells us something important: the industry is treating data production as infrastructure, not just a preprocessing task synthetic data can help robots learn rare situations but it still needs grounding in the physical world. models need real environments to anchor simulations, expose unexpected conditions, and help developers understand where their systems may fail. this is where Vangrid has a distinct angle vangrid focuses on sourcing real-world spatial data through smartphone captures commissioned via bounties. rather than trying to replace simulation platforms, it could complement them by helping turn specific physical locations into digital 3d representations. the interesting possibility is a feedback loop: real places provide the starting point, simulation expands the scenarios, and testing reveals where more real-world information is needed. if physical ai is entering its chatgpt moment, the next competition is about the infrastructure that keeps its understanding connected to reality. vangrid is building on the real-world data collection side of that equation.

The Meta VR Start Developer Competition is awarding $1M across 20 cash prizes, with top prizes of $100,000. Build a new VR experience or significantly update an existing one, then submit it by Nov 18. Terms and conditions apply. See the official rules and enter here 👉 #MetaVR #MetaQuest #MetaVRGlasses #DeveloperCompetition

HIRING DEVS! I'm hiring agentic developers to work on a special project. The work is incredibly fun, and we are offering fully remote, well-paid positions. Extra points if you're in Toronto as well. If you want to come work on the coolest thing of your career with other highly motivated A-players, this is your chance! DM's open