Tessera

As Ronaldo's career winds down, it's tough seeing a legend without that World Cup trophy. Still, his records and passion inspired generations. GOAT debate lives on. 🇵🇹⚽ #Ronaldo #WorldCup

Haaland was unstoppable yesterday vs Brazil – that finishing is pure class. Norway's got a superstar leading the charge! ⚽🇳🇴 #Haaland #WorldCup

nana🦄@ds-nana.bsky.social · 2y ago

Diving deep into Transformers this week – the math behind attention is wild but so powerful for everything from chatbots to vision. Anyone else geeking out on this? #AI #Transformers

Revisiting Chunking in the RAG Pipeline towardsai.net/p/machine-le...

Revisiting Chunking in the RAG Pipeline | Towards AI

Author(s): Florian June Originally published on Towards AI. Unveiling the Cutting-Edge Advances in ChunkingThis member-only story is on us. Upgrade to acces ...

towardsai.net

Claude Dispatch blew my mind today. Text tasks from my phone and it just handles them on the desktop. Tried it while out—fixed some SoundSafari code easy. Game changer for real. #ClaudeAI

If you're an early-career engineer worried about AI: learn system design. Not because AI can't do it — it can, sort of — but because knowing what's a bad design is still a human job.

The "software factory powered by AI" pitch misses the point entirely. The hard part was never writing the code. It was figuring out what to build. AI doesn't fix that. It just makes the wrong thing faster.

The best software teams we've worked with share one trait: They say no more than they say yes. No to the feature that sounds cool but serves 2% of users. No to the integration that adds complexity without value. Constraint is a design tool. Use it.

Most "AI features" aren't AI features. They're search bars with a chatbot on top. Real AI integration means: • The system learns from user behavior • Decisions adapt without manual rules • The product gets smarter over time That's the difference between AI-washed and AI-native.

AI agents aren't just automating tasks. They're changing what software is. From apps users operate → systems that act on their behalf. Building for this requires rethinking product architecture from the ground up. That's where we spend most of our thinking at Lycore.

The hardest part of building a product isn't the code. It's knowing what NOT to build. Every feature you add is a feature you have to maintain, support, and explain. Ship the core. Validate. Then add. We help founders do exactly that — lycore.com

Founders: stop burning runway on the wrong tech bets. We've shipped 300+ projects — AI agents, Flutter apps, SaaS platforms, fintech tools — across 30+ industries. Fast. Scalable. Production-ready. lycore.com

The best client feedback we get isn't "great code." It's: "You actually understood what we were trying to build." Technical execution matters. But clarity, communication, and trust matter more. That's the Lycore difference. 🔧 lycore.com

Every company is becoming an AI company whether they're ready or not. The ones winning right now? They're not waiting to hire a 10-person AI team — they're partnering with specialists to ship fast. Lycore has been in the room for 300+ of those builds. lycore.com

300+ projects. 30+ industries. One team. Lycore builds custom AI software, mobile apps, e-commerce platforms, and cloud infrastructure for startups and enterprises worldwide. If you're scaling and need a dev partner — let's talk. lycore.com

The startup graveyard is full of apps that worked technically. What killed them: → No real user problem → Built for themselves, not customers → Launched without a single paying user → Overengineered before validated Talk to 10 potential customers before writing one line of code.

Hot take: most startups don't need a more powerful AI model. They need better data pipelines feeding the model they already have. Garbage in, garbage out — no matter how smart the LLM. We see this every week building AI solutions for clients. Fix the data layer first.

A client came to us after spending £120k building an app nobody wanted. They'd built everything. Auth, dashboard, admin panel, notifications, analytics. But never answered: do users want this at all? An MVP would've told them in 6 weeks for a fraction of the cost. lycore.com/mvp-development/ ✨

MVP Development Services - Lycore

Build a lean, production-ready MVP in 8-12 weeks. Fixed price after discovery. You own all code and IP. Talk to Lycore senior engineers.

lycore.com

The question isn't "should we use AI?" — it's "which problems does AI actually solve for us?" We've written about how smart teams answer that. Practical breakdowns, real examples, no hype. Our blog → lycore.com/category/blog/ #AI #SoftwareDevelopment #TechStrategy

blog - Lycore

lycore.com

Founders: your MVP doesn't need to be perfect. It needs to be testable. The biggest MVP mistakes we see: → Building too many features before user #1 → Spending months on polish nobody asked for → Skipping the "will anyone pay?" test Ship fast. Learn faster. lycore.com/mvp-development/

Most startups waste their first AI budget on the wrong things. What we see building custom AI solutions: ❌ Automate before nailing the manual process ❌ Pick the flashiest model, not the right one ❌ Skip user testing ✅ Start with one high-ROI workflow ✅ Measure before & after lycore.com

How AI Is Changing the Economics of Fintech: What Founders Need to Know in 2026 This is not about building the most impressive AI demonstration. It is about understanding where AI ch... #Fintech #ArtificialIntelligence #Startup #Finance #Entrepreneurship medium.com/@lycore/how-...

How AI Is Changing the Economics of Fintech: What Founders Need to Know in 2026

The cost of fraud, the opportunity in personalisation, and the decisions that separate fintech companies that scale from those that stall.

medium.com