A developer building Olano, a platform for hosting and configuring AI agents, shared an 11-minute walkthrough of the first-run experience. The demo covers deploying an instance, opening the dashboard, and creating a first agent via two setup paths: a manual form or a conversation with a built-in setup agent called AgentFather. The post seeks feedback on which onboarding style users prefer.
Animam is an infrastructure layer for deploying personalized AI agents at scale. It allows one account to manage multiple agents (multi-tenant) sharing the same knowledge base, persona, and tools, exposed via embeddable widget, REST API, voice, and MCP server per tenant. It solves the problem of agencies and builders needing to spin up custom agents for each client without rebuilding from scratch.
Animam is an infrastructure layer for deploying personalized AI agents at scale. It allows one account to manage multiple agents (multi-tenant) sharing the same knowledge base, persona, and tools, exposed via embeddable widget, REST API, voice, and MCP server per tenant. It solves the problem of agencies and builders needing to spin up custom agents for each client without rebuilding from scratch.
Backprompter is a platform that lets developers and researchers build, test, and deploy AI agents without managing a backend, database, or secrets. It supports model selection, prompts, RAG, and tools (HTTP API calls), and allows versioning, mock users, simulated conversations, and evaluations. It solves the problem of tedious setup and iteration for AI app development.
Backprompter is a platform that lets developers and researchers build, test, and deploy AI agents without managing a backend, database, or secrets. It supports model selection, prompts, RAG, and tools (HTTP API calls), and allows versioning, mock users, simulated conversations, and evaluations. It solves the problem of tedious setup and iteration for AI app development.
A developer on r/AI_Agents asks how others handle the high setup complexity and execution risk of agentic workflows for non-technical users. They propose a chat-based approach with plain-text task descriptions and a one-click human approval gate to mitigate hallucinations triggering unwanted actions.
A developer on r/AI_Agents asks how others handle the high setup complexity and execution risk of agentic workflows for non-technical users. They propose a chat-based approach with plain-text task descriptions and a one-click human approval gate to mitigate hallucinations triggering unwanted actions.
A user describes configuring fresh AI harnesses by sending a markdown document that the agent executes on itself, installing skills, subagents, MCP servers, and asking for credentials. The approach reduces repetitive manual setup for role-specific agents.
A user describes configuring fresh AI harnesses by sending a markdown document that the agent executes on itself, installing skills, subagents, MCP servers, and asking for credentials. The approach reduces repetitive manual setup for role-specific agents.
AgentHost is a persistent chat interface that lets users route tasks across Claude, Codex, and local models (e.g., Hermes) without rebuilding conversations. It solves the problem of fragmented agent workflows by providing a shared task board, live per-engine cost ledger, and autonomous run reporting. Built for developers managing multiple AI agents.
AgentHost is a persistent chat interface that lets users route tasks across Claude, Codex, and local models (e.g., Hermes) without rebuilding conversations. It solves the problem of fragmented agent workflows by providing a shared task board, live per-engine cost ledger, and autonomous run reporting. Built for developers managing multiple AI agents.