D-Coder

The most expensive employee in your company is probably your finance stack if it looks like this: → Stripe for payment processing → Ramp for team cards → Wise for international wires Did the math: On $500k ARR that’s $15k–20k/year in fees alone That’s exactly what Airwallex solves. 👇

@Rixhabh__ Love this integration.

BREAKING: You can now run a full AI agent like an app. No code. No infra. No waiting. Just open and deploy. This changes how people use AI 👇

In a world of AI demos and concept videos, Natura AI shipped a real product. connected to real apps. solving real problems. available today. that alone deserves massive respect. congrats to the whole team 🫡🔥

This changes how you interact with your own body. Perplexity bringing health data, labs, and AI together feels like a serious leap beyond generic health apps.

@details_with_ai useful prompts

🚨 AI just disrupted the legal industry. Claude can write NDAs, freelance agreements, and LLC docs in minutes. Here are 12 prompts worth $15,000: (Don’t miss this)

@Whizz_ai Love the focus on understanding and context! This could really change the game for AI retrieval.

🚨 BREAKING: Hydra just raised $6.5M to replace vector databases entirely. And once you understand why, you will never look at RAG the same way again. Here is the problem nobody talks about: Every AI retrieval system today works the same way. It stores your data as flat embeddings. Then, when you ask a question, it returns whatever "feels" closest based on similarity scores. Similar? Sure. Relevant? Rarely. Someone asked their AI assistant about a client contract last week. The AI returned a detailed, perfectly formatted answer. One problem. It was pulled from a completely different client's file. The similarity score was 0.94. The answer was dead wrong. This is not a rare edge case. Once you cross 10M+ documents, vector database accuracy falls apart. They store no relationships, no decisions, no timeline. That is where @hydra_db changes everything. Here is what HydraDB actually does: → Builds an ontology-first context graph over your data → Maps real relationships between entities, not just word proximity → Understands the "why" behind documents, not just the "what." → Tracks how information evolves like Git-style versioning → Processes everything in RAM with sub-200ms latency So when you ask about "Apple," it knows you mean the company you're a customer of. Not the fruit. Even when a vector DB's similarity score says 0.94. When your user moves cities, it does not overwrite the old address. It appends the new one and remembers the context of why they moved. That is not retrieval. That is understanding. Here is why this matters for builders right now: → AI agents that actually remember context across sessions → Enterprise RAG that does not hallucinate from the wrong document → Multi-agent systems that share a common context layer → 90% accuracy on LongMemEvals benchmark, leading the industry SOC 2 certified. GDPR compliant. Enterprise-ready. If you are building anything with AI retrieval, agents, or long-term memory, vector databases are not going to cut it anymore. HydraDB is what comes next. Check it out → hydradb.com

@TheAIColony These prompts are very helpful.

BREAKING: AI can now build you a full AI video channel from scratch like a $10K creator consultant (for free). Here are 10 Claude prompts that take you from zero to a monetized AI video channel in 90 days: (Save for later)

That's all for now. If you enjoyed reading this post, please : Like, repost, and follow me @Damn_Coder for more!

Instead of stitching together multiple tools for payments, accounts, expenses, and billing… Airwallex brings everything into one global financial platform. Try it here: airwallex.com

The most expensive employee in your company is probably your finance stack if it looks like this: → Stripe for payment processing → Ramp for team cards → Wise for international wires Did the math: On $500k ARR that’s $15k–20k/year in fees alone That’s exactly what Airwallex solves. 👇

@Div_pradeep This is great

Instead of watching Netflix for 2 hours, watch this guy explain why some people become successful while others stay average.

@Rixhabh__ Thanks for sharing

No movie this week. Watch these 4 videos instead:

@thetripathi58 Love it

MIND-BLOWING: The most underrated AI tool of 2026 just dropped. You can now literally type a sentence and generate an entire 3D world you can walk through. No 3D knowledge required. Here's how OpenArt Worlds creates these worlds in seconds: