Helder Vasconcelos ⛩️

📅 𝗧𝗼𝗱𝗮𝘆 𝗜'𝗺 𝗽𝘂𝗯𝗹𝗶𝗰𝗹𝘆 𝗿𝗲𝗹𝗲𝗮𝘀𝗶𝗻𝗴 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗜'𝘃𝗲 𝗯𝗲𝗲𝗻 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴: @luziadev 𝗔𝗣𝗜 After years of building trading tools and crypto applications, I kept hitting the same wall. Fragmented exchange APIs. Inconsistent data formats. The tedious work of maintaining connectors for each platform. 𝗦𝗼 𝗜 𝗯𝘂𝗶𝗹𝘁 𝘁𝗵𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗜 𝘄𝗶𝘀𝗵𝗲𝗱 𝗲𝘅𝗶𝘀𝘁𝗲𝗱. @Luziadev is a unified cryptocurrency 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗮𝗻𝗱 𝗠𝗮𝗿𝗸𝗲𝘁 𝗱𝗮𝘁𝗮 𝗔𝗣𝗜 that aggregates real-time data from multiple exchanges through a single, normalized endpoint. One API. One format. No more juggling five different authentication schemes or parsing inconsistent response structures. What's in the beta: ✅ Real-time ticker data from Binance, Coinbase, Kraken, Bybit, and OKX ✅ Consistent JSON responses across all exchanges ✅ Circuit breaker pattern for fault tolerance when exchanges fail ✅ MCP server for AI agent integration (Claude, etc.) ✅ Developer portal for API key management and usage monitoring 𝗪𝗵𝘆 𝗮𝗺 𝗜 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗻𝗼𝘄? The crypto data space is dominated by expensive enterprise solutions or unreliable free tiers with aggressive rate limits. As an indie developer, I wanted something in between: affordable, fast, and simple. This beta is intentionally early. I'd rather ship something useful now and iterate based on real feedback than polish in isolation for months. If you're building: - 𝗧𝗿𝗮𝗱𝗶𝗻𝗴 𝗯𝗼𝘁𝘀 - 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 𝘁𝗿𝗮𝗰𝗸𝗲𝗿𝘀 - 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 - 𝗗𝗲𝗙𝗶 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 - 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗮𝘁 𝗻𝗲𝗲𝗱 𝗺𝗮𝗿𝗸𝗲𝘁 𝗱𝗮𝘁𝗮 I'd love to hear what you need. What's missing? What would make this actually useful for your project? #indiedev #bun

Free Crypto pricing API tiers aren't all equal 🤔 Some give you 100 requests/day. That's one call every 58 minutes. We compared @coingecko , @CoinMarketCap , @realCoinAPI, @binance, and @luziadev side by side, rate limits, hidden costs, and when it actually makes sense to pay. Full breakdown 👇 luzia.dev/blog/free-vs-p…

Ideas are cheap but time isn’t. That’s why @hypermarioal built a Venture Analyst in @claudeai: structured and able to kill bad ideas before they cost money. It runs a raw idea through 10 custom skills: market sizing, customer validation, risk scoring, and GTM planning, all in one session. Now we focus only on opportunities that matter. Download the exact skills he used. 👇

UCL nights are always special in Alvalade

@trq212 You should try out uberSKILLS . A visual workbench to build, test and manage skills uberskills.dev

github.com/uberskillsdev/… uberskills.dev

I built a tool because I was tired of losing my best @ClaudeAI Code Skills. 😤 Let me explain. A few months ago, I went all-in on Claude Code as my daily coding companion. And it was incredible, until I hit a wall. 🧱 I kept writing the same complex instructions over and over. Copy-pasting skills between projects. Losing the good ones. Tweaking system instructions in text files with no way to test them before deploying. My "Claude Code Skills library" was a mess of scattered markdown files across dozens of folders. 😵 So I asked myself: what if I could design, test, and deploy Claude Code skills from a single place? That question became 𝘂𝗯𝗲𝗿𝗦𝗞𝗜𝗟𝗟𝗦. 🚀 Here's what it does: 🎨 Visual editor to create and refine skills (with AI-assisted generation) 🧪 Multi-model testing sandbox — see how your skill performs before you ship it ⚡ One-click deploy to your local Claude Code setup 📦 Import/export to share skills across teams or machines 🕐 Full version history so you never lose a working prompt again The core idea is simple: treat your AI skills like code. Version them. Test them. Deploy them with confidence. It's fully open-source under MIT. 🔓 Whether you're using Claude Code for code reviews, architecture planning, writing tests, or automating workflows, 𝘂𝗯𝗲𝗿𝗦𝗞𝗜𝗟𝗟𝗦 gives you a proper workbench to manage all of it. 𝗡𝗼 𝗺𝗼𝗿𝗲 𝘀𝗰𝗮𝘁𝘁𝗲𝗿𝗲𝗱 𝗳𝗶𝗹𝗲𝘀. 𝗡𝗼 𝗺𝗼𝗿𝗲 "𝘄𝗮𝗶𝘁, 𝘄𝗵𝗶𝗰𝗵 𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗮𝘁 𝗽𝗿𝗼𝗺𝗽𝘁 𝘄𝗮𝘀 𝘄𝗼𝗿𝗸𝗶𝗻𝗴?" 🤯 If you're deep into the Claude Code ecosystem and want to take your setup to the next level, give it a try. cc @bcherny @hesreallyhim @alexalbert__ Link in comments. 🔗

Just submitted a proposal to bring @EFDevcon to Lisbon in 2027 🇵🇹 Lisbon has the builder density, the infrastructure, the track record, and the community to host the best Devcon yet. If you want Devcon in Europe, go show some love 👇 forum.devcon.org/t/proposed-loc…

𝗠𝗮𝘆𝗯𝗲 𝗜 𝗪𝗮𝘀 𝗥𝗶𝗴𝗵𝘁: 𝗝𝗲𝘃𝗼𝗻𝘀' 𝗣𝗮𝗿𝗮𝗱𝗼𝘅 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗗𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 A few months ago, I shared a somewhat contrarian take: the demand for software engineers could actually increase with AI, not decrease. 𝗧𝗵𝗲 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴? Jevons' paradox, the idea that when technology makes a resource more efficient to use, total consumption of that resource goes up, not down. Many disagreed. The narrative was clear: AI writes code, therefore fewer coders needed. Simple math, right? 🤔 Well, Citadel Securities just published a macro strategy report, "𝗧𝗵𝗲 𝟮𝟬𝟮𝟲 𝗚𝗹𝗼𝗯𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗖𝗿𝗶𝘀𝗶𝘀" that brings hard data to this exact debate. And the numbers are telling. The data says the opposite of what doomers predicted: ✅ Job postings for software engineers are up 11% year-over-year in early 2026, according to Indeed data ✅ Unemployment sits at 4.28% far from the apocalyptic scenarios some forecasted ✅ AI adoption in the workplace, per the St. Louis Fed's Real Time Population Survey, remains "unexpectedly stable" not the exponential displacement curve many feared ✅ New business formation is rapidly expanding, creating even more demand for technical talent The report concludes that achieving the catastrophic labor displacement scenario requires an unrealistic combination of simultaneous conditions: full adoption, total substitution, zero policy response, and unconstrained computing scaling. None of these are supported by current evidence. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗲𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗲 𝘄𝗼𝗿𝗸. 𝗜𝘁 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝘀 𝗶𝘁. 𝗔𝗻𝗱 𝗵𝗶𝘀𝘁𝗼𝗿𝗶𝗰𝗮𝗹𝗹𝘆, 𝗶𝘁 𝗰𝗿𝗲𝗮𝘁𝗲𝘀 𝗺𝗼𝗿𝗲 𝗼𝗳 𝗶𝘁. Sometimes the contrarian take is just the historically literate one 😀 citadelsecurities.com/news-and-insig…

Building smart tools with fresh bitcoin prices has never been easier. We are unlocking a huge amount of possibilities.

🌅 We built an MCP server that connects @claudeai to real-time crypto data from 5 major exchanges. Real-time prices from 5 exchanges, powered by Claude: - Price comparisons across exchanges - Arbitrage detection - Portfolio tracking - Market reports No code. Just ask in natural language ✍️ Read the full breakdown: luzia.dev/blog/building-…

Most market making tools give you a start button and a monthly report. Raytrade gives you the full picture: ✅ Real-time logs ✅ Live order book interaction ✅ Price charts ✅ Events ✅ Trade history. Everything running your liquidity, visible as it happens.

Trading bots is fun until it isn't. 🫠 The tooling never kept up with the agents. BotOps, as our CTO @heldervasc calls it, is the category that changes that. @raytradestudio is a proof that it works.

Bots got smarter. The infrastructure around them? Still in the dark ages. 📁 That's the gap BotOps is here to fill: think DevOps, but for autonomous agents. RayTrade Studio is our take on this for algo trading: one platform to deploy, monitor & simulate bots across 7 exchanges. Simple and effective. But this is just one vertical. The era of BotOps is here. Full article ⬇️

@tiagopita Triste é a figura que fazes aqui no Twitter. Passas a vida a criticar a mentalidade de inveja dos portugueses e depois é isto, comentários vazios, sem direcção nem fundamento. A incoerência fala por si.

🚀 We just published a deep dive into how we built Luzia's crypto API to achieve sub-100ms response times. ⏱️ In real-time crypto markets, arbitrage opportunities disappear within 200-800ms. Most aggregators add 300-600ms of overhead. We needed to do better. Here's what we did differently: ⚙️ Runtime: We chose @bunjavascript for its native HTTP/WebSocket support, io_uring-based I/O, and direct TypeScript execution - no transpilation overhead. 🏗️ Architecture - 4 principles that made the difference: 1️⃣ Never fetch on request - continuous WebSocket streams feed the cache. The API never calls exchanges during request processing. 2️⃣ Cache in layers - L1 in-process memory (sub-microsecond) + L2 distributed cache (1-3ms). 95% of requests are served from memory without any network I/O. 3️⃣ Fast rate limiting - a single atomic Redis operation replaces the typical multi-round-trip approach. Fail-open by design. 4️⃣ Separate reads from writes - the write path handles batched ingestion while the read path serves entirely from cache. 📊 The result: 80ms p50, 100ms p95. The biggest takeaway? Architectural decisions matter more than language choice. Performance has to be a design constraint from day one — not something you bolt on later.

Request access ⬇️ raytrade.studio

𝗥𝗮𝘆𝗧𝗿𝗮𝗱𝗲𝗦𝘁𝘂𝗱𝗶𝗼 started as an internal tool to solve our own pain points managing liquidity bots. 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀, and 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 were scattered or nonexistent. But once we saw it working, something clicked: "This isn't just an internal fix, it's a product. 𝗔 𝗳𝘂𝗹𝗹 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝘀𝘁𝗮𝗰𝗸 𝗳𝗼𝗿 𝗯𝗼𝘁 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀, 𝗰𝗼𝗻𝘁𝗿𝗼𝗹, 𝗮𝗻𝗱 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲" We're entering an era where agents are becoming human proxies, automating everything from trading to workflows, and as bot adoption scales, so does the complexity of managing them. That's why I believe a new software category is emerging, one I'd call #𝗕𝗼𝘁𝗢𝗽𝘀 . Platforms purpose-built for the operational lifecycle of autonomous agents. Deployment, monitoring, performance analytics, incident response, version control, the same rigor we brought to DevOps, now applied to bots 🔄 Think of it this way: BotOps is to autonomous agents what DevOps is to software delivery 🎯 𝗥𝗮𝘆𝗧𝗿𝗮𝗱𝗲𝗦𝘁𝘂𝗱𝗶𝗼 is our take on BotOps for trading 📈. But the pattern is universal. Wherever bots operate at scale, BotOps platforms will follow. 𝗧𝗵𝗲 𝗲𝗿𝗮 𝗼𝗳 𝗕𝗼𝘁𝗢𝗽𝘀 𝗶𝘀 𝗵𝗲𝗿𝗲. 𝗧𝗶𝗺𝗲 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘁𝗵𝗲 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘁𝗵𝗮𝘁 𝗸𝗲𝗲𝗽𝘀 𝘁𝗵𝗲 𝗯𝗼𝘁𝘀 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗿𝗶𝗴𝗵𝘁 ⚙️🔥

@levelsio It is very hard to get the exposure and appear on our friends timeline. @x algorithm is quite broken nowadays. Loads of bots , farms are taking the staging from us. Most of time we are talking to a wall and it’s getting worse with the time .

The first time in X history I think I don't really like the algorithm so much It seems most posts get stuck at 10-50 RTs, and the delay until they grow to even there can take like 24 hours to 3 days! And I feel like you have to tweet quite extremist now to get views I liked before more where you could post a regular blog post and personal story and it'd get more views now it barely does

Great evening at @swordhealth 's AI Internal Talks yesterday. Excellent presentations from Rui Quintino and Luís Maia🔥 Thanks to Margarida Prozil Vieita for hosting and inviting us to share a bit about @LayerXlab journey navigating this new paradigm. For those who couldn't make it, I'm sharing the slides below. The presentation is based on a longer blog post where we documented our AI journey over the past year. #slide=id.g3c8f5c11996_0_144" target="_blank" rel="nofollow noopener">docs.google.com/presentation/d…