Lexagent

Full walkthrough now live: Lexagent Dashboard Inside the dashboard, we cover: - Wallet connection & account overview - Real-time SOL balance + price tracking - Deploying your own Telegram AI agent - Natural-language transfer flow (Agent Transfer Chat) - Token swap flow (SOL/USDC/USDT) - Transaction history & activity monitoring - Settings and agent configuration From prompt to on-chain execution — all in one place.

we are just done working with : - Thread memory per chat - auto create/get thread by agent_id + chat_id - save message history per thread - Context-aware replies - inject recent history + saved memories into the prompt before calling LLM - Memory extraction v1 (heuristic) - detect patterns such as: my name is, call me, i prefer, don't, always, remember that - upsert to memory store - New API endpoints - GET /api/threads?agentId=&chatId= - GET /api/threads/:id/messages?limit= - POST /api/threads/:id/reset - GET /api/memories?agentId=&chatId= - DELETE /api/memories/:id - Updated both runtimes - server.ts (prod/server mode) - vite.config.ts middleware (dev mode The function of the update is: - Saves chat history per thread - So the bot's responses are connected to previous conversations. - Saves user preferences (memory) - Examples: "Call me Jenn", "I prefer short answers". - The bot can use this in subsequent replies. - Context is injected into the model before generating a response - System prompt + memory + recent messages are combined, so answers are more personalized and consistent. - There are endpoints for observability/control - View thread, view message content, reset thread, view memory, clear memory. Product impact: - More "true assistant" UX (persistent context), - Fewer user instructions need to be repeated, - A foundation for advanced features (smart personalization, long-term memory, agent behavior tuning).

Most people see a message. I see a command path. Intent parsed. Risk contained. Signature earned. Settlement final. No noise. Just execution.

LexAgent isn't just a tool. I want it to be an execution layer that people actually use every day. Less talk, more deliveries.

Imagine sending crypto, swapping tokens, and deploying agents… just by typing. That’s Lexagent. AI meets on-chain execution $LEXA

If you haven’t joined our Telegram community yet, feel free to hop in: t.me/LexagentHq Thank you - $LEXA | Lexagent

We move in silence. Every push is a signal. While they watch the timeline, we build the future in the background.

$LEXA | Dexscreener Updated : dexscreener.com/solana/5pLCpJJ…

40M $LEXA Locked : app.streamflow.finance/contract/solan…

$LEXA LexAgent is now LIVE on Pumpfun : 5pLCpJJRcNcXr24AQzMzEe4SERRbopKkFn1J1qZXpump

Every message has a path. User → Signal → Logic → Intelligence → Return. In Lexagent, the Sequence Diagram isn’t documentation its prophecy.

Most people ask AI for answers. We ask AI to execute.

Blueprint before blitz. This is the core architecture behind Lexagent.

No hype. No promises. Just execution. Lexagent has entered the arena.