Aiden

Weco AI is an autoresearch agent platform for running and inspecting optimization experiments. It repeatedly proposes code changes, evaluates them against a fixed command and measurable goal, keeps changes that improve the score, and discards weaker attempts. Its dashboard presents the search as an experiment tree with scores and diffs, allowing users to branch from promising runs and steer an ongoing search toward a different idea. The workshop materials demonstrate the approach with Mini Parameter Golf and a Flappy Bird controller evaluated across multiple conditions, including hidden validation data and limits on editable code.

Waku Agent is an open-source, local-first personal assistant and AI-agent harness built by seanchen.io. It runs on a laptop through a terminal, local browser dashboard, voice input, or Telegram gateway, and is organized around four components: a harness for tool execution, an approximately 95-line plain-Python agent loop, memory, and evaluation/LLM operations. Its memory uses semantic, episodic, and procedural stores in a local SQLite database, with a gate that decides whether to retrieve or save memory and a pass that determines what to retain. The project includes deterministic tests alongside LLM-as-judge evaluation with a release gate. The dashboard displays message flow through the harness, including gate decisions, tool calls, loop iterations, memory updates, traces, costs, and latency; it also includes views for workflows, tools and MCP connectors, memory, and the SQLite state database. It can be installed with pip and exposes the `waku` command. The dashboard runs a local web server at `127.0.0.1:7777`, and the Telegram gateway starts when `TELEGRAM_BOT_TOKEN` is configured. Model providers are selected through a provider setting and API key, with support stated for Anthropic, OpenAI, Gemini, DeepSeek, MiniMax, Kimi, GLM, OpenRouter, OpenCode Zen, and OpenCode Go.

AI-Native Workshop is a repository-based workshop for practicing AI-native software development workflows. Its curriculum covers voice coding, agent sessions, loops and measurable goals, Git worktrees, verification gates and hooks, adversarial review, and scheduled tasks. The repository includes setup skills, exercises, slides, a glossary, a facilitator guide, and an optional local `aie-coach` MCP server with seven tools for check-ins and setup scoring. Its setup workflow runs inside Claude Code and can install and verify Bun, the Codex CLI, and Git; the workshop is organized in four blocks covering voice, loops and goals, gates, and schedules.

An AI software engineering agent developed by Cognition that runs isolated cloud coding sessions, writes and modifies code, and can test applications through a browser. Devin is designed as an end-to-end software-development environment for planning and implementing coding tasks. Vals evaluated it internally and increased its adoption after finding it to be token-efficient.

ai-memory is an open-source local server for long-term memory and session handoff among AI coding agents. It captures prompts, tool calls, and agent context through MCP integrations and lifecycle hooks, storing the material in a searchable, Git-backed Markdown wiki. When a session ends or is explicitly finalized, it generates handoff context for a subsequent session, including the project architecture, failed approaches, and open questions, so work can continue across agent vendors without restating the context; clients without a true session-end hook use explicit finalization commands. The project documents integrations for Claude Code, Codex, Command Code, Devin CLI, OpenCode, Cursor, Gemini CLI, Oh My Pi, Pi, and Crush, with agent-specific configuration, generated plugins or extensions, and capture exclusions. It runs on Linux, macOS, and Windows through WSL2, with experimental native Windows support, and is distributed through Docker images and native release binaries.