Eliza Times

Shaw and his team at Auto.fun are focused on development and trading.

He mentioned they're 'shipping hard' and will be doing extensive 'playtesting' (trading) over the coming weeks to ensure Auto.fun provides a great trading experience. They're working with Raydium and another organization to be announced, with plans to allow users to choose where their pool goes and earn fees.

Shaw has been commenting on AI development, noting that getting LLMs to be consistent and grounded is challenging but solving that will 'unlock much alpha.' He's shifted focus to 'useful organizational agents and workflows for remote team/DAOs' as he sees this as an underserved need in AI tooling.

He also reflected on his creation Eliza, apologizing for 'shitting on $LLM' and ...

expressing that he should have been more honored/flattered seeing Eliza being 'endlessly recycled into new memes and formats.' He clarified that he 'didn't make a damn dollar off any of that.'

Several bug fixes have been implemented in the ElizaOS system.

These include fixing the GitHub Authentication Prompt during the Start CLI Command (PR #4242), resolving GUI TTS issues (PR #4237), addressing transcription problems (PR #4236), fixing an Anthropic JSON parse issue (PR #4222), repairing agent subcommands (PR #4220), fixing the delete character button (PR #4197), correcting plugin installation priority order (PR #4256), replacing a deprecated vision model (PR #4254), moving initialization after adapter.init in runtime (PR #4253), and removing duplicate declaration in api.ts (PR #4246).

New features have been added to enhance functionality.

These include OpenAI TTS testing and implementation (PRs #4259 and #4255), a new message API (PR #4247), and the addition of message buttons (PR #4187).

Several code improvements and refactoring efforts have been made to enhance the system's performance and maintainability.

These include multiple CLI cleanup operations (PRs #4240 and #4239), improvements to CLI and start code (PR #4250), and the use of console log for non-error cases in CLI (PR #4248). Additionally, a reflections agent that communicates with other deployed agents has been implemented (PR #4257).

## ElizaOS Development and Issues The Discord chat focused heavily on ElizaOS d...

evelopment issues, particularly around Twitter plugin integration and LLM configuration. Users reported problems with the Twitter plugin not replying to mentions or quote reposts in v1.0.0-beta-28, with solutions including enabling `TWITTER_SEARCH_ENABLE=true` and using `callback()` in custom actions. A forked Twitter client using Twitter API v2 was shared to reduce ban risk. LLM configuration conflicts were also common, with users like skyblue.tsx facing issues where LLM (llama3.2 via ollama) overrode custom chatbot responses. Solutions included removing the llama model, adjusting ollama config, and deleting the sqlite DB in ./agent/data/. Version compatibility was a recurring issue, with v0.25.9 reported as the most stable. Users encountered problems with plugin mismatches across versions (e.g., @elizaos/client-discord only works on 0.1.9, while @elizaos/plugin-discord is compatible with v1.0.0). Other technical issues included MongoDB adapter problems (fixed by adding "types": ["node"] to tsconfig.json) and dynamic require errors when using bun install on WSL2.

## Pump.fun Trading and Token Analysis The Discord chat primarily revolves arou...

nd real-time trading and analysis of meme coins and low-cap tokens on the Solana-based platform pump.fun. Users actively share contract addresses, track market caps, and discuss token performance metrics such as % bonded and price movement. Several users identify promising tokens early (e.g., ReFi, KITGPT, BUTTDICK, Gamify), and others follow up with .cc and .dp commands to check token stats via Rick bot. Key technical discussions include token bonding, DEX payments, and wallet activity analysis. For example, users confirmed bonding for tokens like Poohcoin and ScopeScanner, indicating active liquidity provisioning. DEX integration was also discussed, with Rick confirming that Poohcoin had its DEX paid, linking to Dexscreener and a Telegram bot. Users also analyzed wallet behavior related to tokens like Eduardo (First Tokenized Mouse), noting when a user bought 6.4% of the supply, leading to speculation about motives and potential manipulation. This highlights the importance of on-chain transparency in the community.

## SpartanV2 Development Status The Discord chat confirms that SpartanV2, a new...

version of the DegenAI agent, is still under development and has not yet replaced SpartanV1 in production. odilitime, a core contributor, clarifies that SpartanV1 is currently active and being used publicly, while SpartanV2 will be deployed once it is fully ready. In a related conversation, odilitime agrees to allow the current agent to remain active ("yapping") on v1 while development continues, indicating a temporary solution to maintain engagement during the transition. A feature request to add a contract address to the account profile was quickly implemented by odilitime. There is also mention of potentially recovering a previously lost follower base (25k followers), though no technical details are provided on how this might be accomplished.

## Discord Bot Performance Optimization A detailed discussion focused on debugg...

ing a performance issue in the /report command of a Discord bot. The command was reported to be slow and occasionally timing out. [dev_riko] identified that the command was fetching too much data from the database without pagination or filtering and proposed limiting the query to the last 100 reports and adding an index on the timestamp column to speed up retrieval. [techtonic] confirmed the database was using PostgreSQL and recommended using EXPLAIN ANALYZE to profile the query. They also pointed out that the current ORM (Prisma) was not leveraging query optimization features, leading to a proposal to switch to raw SQL for this specific query. After implementing the raw SQL version, [spynter] reported a 60% improvement in response time. The team also added error handling with try/catch blocks and implemented Redis caching with a 5-minute TTL to further reduce database load. This comprehensive approach to performance optimization demonstrates effective collaborative debugging and implementation of best practices.

## AI Agent Interoperability and Decentralized Registries The chat centered aro...

und several technical discussions related to AI agent interoperability, avatar generation workflows, and decentralized agent registries. dankvr shared that they have developed AI-powered workflows to mass-produce avatars for DAO partners and pitch submitters, with the next episode of their show (Clank Tank) ready for feedback. They're considering enabling token holders to vote alongside AI judges. notrickfox and odilitime discussed the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication. odilitime explained that MCP serves as a bridge between static APIs and dynamic agents, noting that while APIs will remain relevant for high-volume/low-latency tasks, agent frameworks like elizaOS could become central tools. doriand0963 proposed a decentralized agent registry using JSON-based "Agent Cards" for capability discovery, combined with a trust graph for agent selection. They emphasized the need for a searchable directory and suggested repurposing web-of-trust models for agent reputation. Other discussions included Auto.fun platform development, with k_carv clarifying it's being used in hackathons to support scientific IP and research causes, particularly through bioDAO.

The elizaos/eliza repository showed increased activity over a two-day period.

From April 9-10, 2025, there were 8 new PRs (all merged), 2 new issues, and 13 active contributors. Activity increased the following day (April 10-11, 2025) with 13 new PRs (11 merged), 4 new issues, and 14 active contributors. This represents growth in both contributions and contributor base across the two-day period.

The provided sources mention 'Top contributors for elizaOS/eliza' but do not provide any specific details about who these contributors are or their contributions to the project.

Without additional information, it's not possible to generate a detailed summary about the contributors to the elizaOS/eliza project.