🎉$50000 ethereum:0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48 GIVEAWAY
Drop your Solana wallet address in the replies 👇
I’m sending random USDC amounts to almost everyone until the full $50K is gone.
No forms. No catches. Just your address.
Let’s drain this bag 🔥
X1 EcoChain × Sides: New ECOsystem Tasks 🔥
👉 https://t.co/0WcHjEzWIO
Sides is an AI-powered, Telegram-native prediction market platform. It simplifies trading on real-world outcomes right inside Telegram, leveraging smart AI agents to automate prediction strategies.
Your tasks:
🟢 Follow Sides on X
🟢 Open Sides Telegram bot and explore how predictions work
Ready to test your market intuition? Jump in and claim your reward!
🔥 X1 Domains Is Officially Live!
X1 EcoChain is launching its native domain name service — X1 Domains. Now, instead of long combinations of characters, your wallet and Web3 profile can get a readable name with the .x1eco extension.
👉 https://t.co/8S7buFkYGI
Why does it matter?
🟢 Error-Free Transactions: Eliminate the risk of sending funds to the wrong place due to a copy-paste error in a long address.
🟢 Your Digital Brand: Lock in a single, recognizable identity across the entire X1 EcoChain ecosystem.
🟢 Future-Proof Advantage: Claim top-tier, short, and rare handles before someone else takes them.
Domain Specs: Build your ideal combination from 3 to 63 characters using letters, numbers, and _.
Check for available options right now!
X1 EcoChain 🤝 @duel_duck: Making Predictions More Accessible and Engaging
We are thrilled to announce our partnership with Duel Duck - together, we are set to advance transparent P2P prediction markets and drive mutual ecosystem growth.
This union opens the door to new competitive formats and deeper community interaction. Ahead of us is the launch of joint pools, where everyone can put their market intuition into action, challenge peers, and prove the power of their analysis.
How to become AI engineer in next 6 months:
By the end, you want to be able to:
- build LLM apps end-to-end
- use APIs from OpenAI / Anthropic / open-source stacks
- design prompts and context properly
- add tool calling and structured outputs
- deploy real projects
So, let’s discuss your roadmap month by month
Month 1: Get solid enough in coding and fundamentals
What to learn:
- Python really well
- Git + GitHub
- CLI / terminal basics
- JSON, APIs, HTTP, async basics
- basic SQL
- basic data handling with pandas
- virtual environments, package management, error handling
- FastAPI or Flask
Month 2: Master LLM app development
What to learn:
- prompting fundamentals
- system vs user instructions
- structured outputs / JSON schemas
- function/tool calling
- streaming responses
- conversation state
- cost / latency / token basics
- failure handling
- prompt injection awareness
Month 3: Learn RAG properly
What to learn:
- embeddings
- chunking
- vector databases
- metadata filtering
- reranking
- retrieval quality issues
- hallucination reduction
- citations and grounding
Month 4: Agents, tools, workflows, evals
- agent loops
- tool selection
- state management
- retries
- when NOT to use agents
- multi-step workflows
- evaluation harnesses
- task success metrics
Month 5: Deployment, product thinking, and reliability
What to learn:
- FastAPI production patterns
- Docker
- background jobs
- queues
- auth + API key security
- logging
- observability
- prompt/version management
- eval dashboards
- cost monitoring
- rate limits
- caching
Month 6: Specialize and become hireable
these knowledge and skills you gained can be applied in three directions
you need to choose one of them and focus on practice
although everything mentioned above is also best learned purely through practice
Direction 1: AI product engineer
Best if you want startup jobs fast
Focus on:
- LLM apps
- RAG
- agents
- deployment
- product UX
Direction 2: Applied ML / LLM engineer
Focus on:
- fine-tuning
- when to fine-tune vs prompt
- evaluation
- inference optimization
- open-source models
- training pipelines
Direction 3: AI automation engineer
Focus on:
- workflow orchestration
- business process automation
- multi-tool systems
- CRM, docs, email, support, ops use cases
This roadmap will help you go through a practical path, and the key is to study each of these points and then test them in real work
By month six, you will already have several built products or examples of completed tasks
And it will be much easier to get a job as an AI engineer
Save it so you don't lose it and can return to study later
Google just dropped a 1-hour course on agentic engineering from scratch:
00:00 – How to build your first AI agent
08:24 – Build agent memory (short, persistent, long)
28:34 – Agentic loops, long-running AI agents
40:04 – How to build MCP (MCP vs API)
1:00:22 – Multi-agentic systems
This 1-hour watch will replace 10 paid agentic courses on the internet.
Bookmark this. Watch this weekend.
LitVM's LiteForge testnet is live 🔥
For the first time, the Litecoin ecosystem has access to smart contracts, DeFi, and Web3 applications — running on LitVM, powered by zkLTC.
The next chapter of Litecoin starts now.
🌐 Explore: https://t.co/qsPxOXibiC