Aleksis

Built a full automation layer for the Meteora launch flow on Solana My Meteora Bundler handles the entire setup pipeline: • Pool creation • Mint initialization • FCFS Alpha Vault integration • Deposit & vesting configuration • Multi-wallet launch distribution Flow: → Prepare funded wallets → Launch with Alpha Vault support → Participate at the same effective entry price → Distribute supply across targeted wallets automatically Designed for scalable, coordinated token launches with streamlined execution on Solana. Building infra that makes launch operations faster, cleaner, and more automated. Live Token: axiom.trade/meme/2piaCW5TP5p… #Solana #Meteora #Web3 #DeFi #Blockchain #Crypto #SolanaDev #TradingBots #AlphaVault #SPL #BuildInPublic #CryptoDev

Had a great meeting with the co-founder of validator.com today. Always inspiring to connect with people building strong infrastructure in the space.

The phrase “LP is Lifestyle” is one of LP Army community slogans.

@coredotera I am so excited to see your profile and posts. I am a dev with rich work experience on Solana network, and then I would like to have connection with you.

@localghost Nice to meet you. As an experienced full stack engineer, I am so interested in your profile. Please hit me up if you need a developer. Thank you.

Just shipped a Meteora Bundler for Solana token launches Built an end-to-end automation flow that handles: • Token minting (SPL / Token-2022 + metadata via IPFS) • Meteora DAMM v2 pool creation • Alpha Vault FCFS setup for controlled early access Why it matters: Instead of chaotic launch sniping, this enables structured, fair participation with vault mechanics (caps, vesting, whitelist options). Tech highlights: • Full launch pipeline orchestration • Dry-run support for safe testing • Flexible configs (WSOL / USDC pools, custom liquidity, vault controls) • Clean modular architecture (mint → pool → vault) Let's connect if you need my dev service.

@Playoffcity Let's contact if you are looking to build a NBA project. I am not only dev but also a NBA market trader.

Back on X after a month deep in @Polymarket trading—focused on Tennis and NBA markets. Learned a lot, found a few solid edges, and managed to extract some value along the way. Appreciate the experience. 🤝

People struggle with backend for a single reason. They never take the first step. They're waiting for: • The "perfect" tutorial. • The "best" online course. • A time when things calm down. But the engineers who made it? They started rough. Started small. But they started. Backend engineering comes from practice: • Building your first API. • Messing up your first database schema. • Deploying something that barely works. The compounding effect of learning only kicks in after you begin. Stop waiting for the “perfect moment." Start today and let momentum take over.

If you are a developer and you are ignoring AI, you are making a career mistake. Not because AI replaces developers. Because AI extends what developers can do. And the developers who learn to use it will build faster, ship more, and become harder to replace.

AI strategy isn’t universal — it’s regional. • 53% of US companies already treat AI as core to their business • 49% of UK organizations focus on identifying high-impact use cases • 43% of DACH companies prioritize structured AI workshops If your strategy looks the same everywhere, you’re likely missing the mark.

Ever wondered how Rust lets you write multithreaded code without the classic nightmares of race conditions and deadlocks? I just published a deep-dive article covering everything you need to know about concurrency and parallelism in Rust. Here’s what the article walks through: → The real difference between concurrency and parallelism → Spawning and managing threads with std::thread::spawn → Sharing data safely using Arc, Mutex, and RwLock → Message passing with mpsc channels for clean, lock-free communication → Coordinating threads with multi-channel patterns → async/await basics and how executors work → How Rust’s Send and Sync traits catch threading bugs at compile time, not at 3 AM in production Rust doesn’t just make concurrency possible. It makes it safe by default. The compiler is your co-pilot, and the ownership model eliminates entire categories of bugs before your code ever runs. Whether you’re coming from C++, Go, Python, or just getting started with systems programming, this guide breaks it all down with clear explanations and practical code examples.

Returning 200 for everything is not an API. It is a debugging nightmare waiting to happen. When I first started building backend APIs, I used 200 for almost everything. It worked locally. It broke trust in production. That is not enough to build an API that communicates clearly with its clients. Here are the 18 status codes every backend developer needs to know: 2xx Success: 200 -> request succeeded 201 -> resource was created, use this after POST 202 -> request received but not yet processed 204 -> success but nothing to return, use this after DELETE 3xx Redirection: 301 -> resource has a new permanent URL 302 -> temporarily moved 304 -> cached version is still valid, no need to resend 4xx Client Errors: 400 -> the client sent something invalid 401 -> authentication required 403 -> authenticated but not allowed 404 -> resource does not exist 405 -> wrong HTTP method for this endpoint 408 -> client took too long 5xx Server Errors: 500 -> something broke on your side 501 -> functionality not supported yet 502 -> upstream service returned an invalid response 503 -> server is down or overloaded 504 -> upstream service took too long Example: The code you return tells the client exactly what happened and what to do next. Get it wrong and you force every consumer to guess. That matters because unclear status codes do not just cause confusion. They make every integration harder to build and every bug harder to trace. Takeaway: Great backend developers do not just return a status code that works. They return the code that is correct.

@mistor Thank you for your likes on my post. we can connect if you need a dev. Thank you.

@NuviraTech Are you available to chat now?

If you’re trading memecoins and still sending manual buys… you’re already late. We’re building a bundler for serious traders — faster entries, coordinated wallets, smarter execution. Built for speed. Built for edge. If you’re deep in the trenches and want alpha → DM.

AI + Web3 builder here—focused on memecoin trading systems. Experience building Rust-based bots for on-chain execution, liquidity tracking, and real-time signal processing (Dexscreener, low-latency pipelines). Looking to push smarter, faster trading with AI-driven strategies.

Healthcare is entering a new era — not just AI-assisted, but AI-driven. Agentic AI is redefining how healthcare systems operate. Unlike traditional AI that waits for instructions, agentic AI can plan, act, and adapt autonomously toward clinical goals. So what does this actually look like in healthcare? 🔹 1. Data Agents: From Fragmented to Unified Intelligence Agentic AI connects and analyzes data across EHRs, imaging, labs, and registries — turning silos into actionable insights. 🔹 2. Document Agents: Eliminating Administrative Burden AI agents can extract, structure, and validate clinical documents, reducing time spent on paperwork and freeing clinicians to focus on patients. 🔹 3. Workflow Orchestration: From Assistance to Action Instead of just recommending, agentic AI can coordinate care workflows — scheduling, prioritizing cases, and triggering next steps in real time. 🔹 4. Clinical Decision Support: Faster, Safer Care By synthesizing complex patient data, agentic systems can highlight risks, recommend actions, and support timely interventions. 🔹 5. Drug Discovery & Research Acceleration Agentic AI can analyze multimodal biomedical data, generate hypotheses, and identify therapeutic targets — dramatically speeding up innovation cycles. 🔹 6. Personalized & Continuous Care From patient monitoring to adaptive care plans, agentic systems enable proactive and personalized healthcare delivery. The key shift? Moving from AI as a tool to AI as a collaborator — systems that don’t just assist clinicians but actively help run healthcare operations. ⚖️ But with great autonomy comes responsibility: Human oversight, transparency, and ethical safeguards remain critical to ensure trust and patient safety. #AI #Healthcare #AgenticAI #DigitalHealth #HealthTech #Innovation

There are two types of companies building AI agents right now: Type 1: Treats agents as a feature. Add a chatbot to the product. Sprinkle some "AI-powered" into the marketing. Ship it. Type 2: Treats agents as employees. Gives them real accounts. Real tools. Real permissions. Lets them operate independently inside the company's actual infrastructure. Type 1 is easier to build, easier to demo, and easier to raise money with. Type 2 is harder to build, harder to explain, and 100x more defensible. VCs are funding Type 1 because it demos well. But Type 2 is what will actually survive. The gap between "looks like an agent" and "works like an agent" is where the next wave of real companies will be built.

Think you can just talk to an AI and magically get a useful SAAS business? Not yet. From my experience building with AI, you need at least a semi-technical understanding to build something meaningful. Insight into design, devops, and a ton of business acumen are crucial. What's your take? Have you found a technical background matters when coding with AI? #AI #SoftwareDevelopment