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This is a platform i built to ease trading using AI, it is an AI trading bot💯
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Most businesses don't need another chatbot.
They need AI that can actually get work done.
I've been helping companies connect AI, automation, CRMs, APIs, and business workflows to eliminate repetitive tasks and improve efficiency.
The biggest wins happen when AI becomes part of the process—not just a conversation.
#AIAgents #Automation #AIEngineering #FullStackDeveloper #SaaS #BusinessAutomation #NextJS #ReactJS #NodeJS #Contra
The process vs. conversation framing is a good way to put it. Most companies trying AI are treating it like a search bar upgrade. The ones actually getting ROI are using it to automate the stuff that was quietly draining engineer time.
Working software is becoming increasingly available on demand.
Anthropic’s Claude Fable 5 release is an important signal for where AI-native software development is heading.
The benchmark results show strong performance across several high-value categories:
▪️ 💻 Agentic coding
▪️ 🧠 Knowledge work
▪️ 👁️ Vision understanding
▪️ 🔬 Scientific reasoning
▪️ 🔐 Cybersecurity
▪️ 📚 Long-horizon problem solving
But the bigger point is not just the benchmark chart.
It is what this means for teams building real products.
As models become better at handling long, complex, multi-step tasks, the bottleneck starts to shift.
Not from “can we write the code?”
But toward:
▪️ Can we define the right problem? ▪️ Can we design the right architecture? ▪️ Can we validate the output properly? ▪️ Can we secure what gets built? ▪️ Can we deploy and monitor it safely?
This is where AI-native execution starts becoming very powerful.
Teams can now move faster on:
▪️ 📈 Internal dashboards
▪️ 🧪 Larger test suites
▪️ 🔍 Research automation
▪️ 🎨 Custom visualizers
▪️ 🛠️ Workflow-specific tools
▪️ 🚀 MVPs and prototypes that were previously too expensive to justify
Jevons Paradox is already starting to show up in software.
As software becomes faster and cheaper to produce, demand for software increases.
At RaptorLabs, we see this as a major opportunity for companies that combine AI execution speed with strong engineering discipline.
The future is not just generating more code.
It is building more useful, secure, and production-ready systems.
⚠️ AI-generated software still needs serious review:
▪️ Code review ▪️ Security checks ▪️ Testing ▪️ Observability ▪️ Production monitoring
The ceiling is moving higher.
The companies that benefit most will be the ones that pair AI-native speed with architecture, security, and product judgment.
Most finance apps hide AI behind dense numbers and sterile spreadsheets.
It pairs high-performance intelligence with a premium, editorial design. Using sophisticated dark tones, refined typography, and intuitive features like the "Forecaster" card, we translated complex algorithms into clean, human-centered insights.
A refined user experience built for modern wealth management.
Let me know what you think! 👀✨
📩 Collaborate with Us? Contra Odama Studio
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