docs: update links in the README.md
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Richard Tang
@@ -137,18 +137,18 @@ Skills are also available in Cursor. To enable:
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## Features
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- **Goal-Driven Development** - Define objectives in natural language; the coding agent generates the agent graph and connection code to achieve them
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- **Adaptiveness** - Framework captures failures, calibrates according to the objectives, and evolves the agent graph
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- **Dynamic Node Connections** - No predefined edges; connection code is generated by any capable LLM based on your goals
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- **[Goal-Driven Development](docs/key_concepts/goals_outcome.md)** - Define objectives in natural language; the coding agent generates the agent graph and connection code to achieve them
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- **[Adaptiveness](docs/key_concepts/evolution.md)** - Framework captures failures, calibrates according to the objectives, and evolves the agent graph
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- **[Dynamic Node Connections](docs/key_concepts/graph.md)** - No predefined edges; connection code is generated by any capable LLM based on your goals
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- **SDK-Wrapped Nodes** - Every node gets shared memory, local RLM memory, monitoring, tools, and LLM access out of the box
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- **Human-in-the-Loop** - Intervention nodes that pause execution for human input with configurable timeouts and escalation
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- **[Human-in-the-Loop](docs/key_concepts/graph.md#human-in-the-loop)** - Intervention nodes that pause execution for human input with configurable timeouts and escalation
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- **Real-time Observability** - WebSocket streaming for live monitoring of agent execution, decisions, and node-to-node communication
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- **Cost & Budget Control** - Set spending limits, throttles, and automatic model degradation policies
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- **Production-Ready** - Self-hostable, built for scale and reliability
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## Why Aden
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Hive focuses on generating agents that run real business processes rather than generic agents. Instead of requiring you to manually design workflows, define agent interactions, and handle failures reactively, Hive flips the paradigm: **you describe outcomes, and the system builds itself**—delivering an outcome-driven, adaptive experience with an easy-to-use set of tools and integrations.
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Hive focuses on generating agents that run real business processes rather than generic agents. Instead of requiring you to manually design workflows, define agent interactions, and handle failures reactively, Hive flips the paradigm: **you describe [outcomes](docs/key_concepts/goals_outcome.md), and the system builds itself**—delivering an outcome-driven, [adaptive](docs/key_concepts/evolution.md) experience with an easy-to-use set of tools and integrations.
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```mermaid
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flowchart LR
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@@ -195,11 +195,11 @@ flowchart LR
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### How It Works
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1. **Define Your Goal** → Describe what you want to achieve in plain English
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2. **Coding Agent Generates** → Creates the agent graph, connection code, and test cases
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3. **Workers Execute** → SDK-wrapped nodes run with full observability and tool access
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1. **[Define Your Goal](docs/key_concepts/goals_outcome.md)** → Describe what you want to achieve in plain English
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2. **Coding Agent Generates** → Creates the [agent graph](docs/key_concepts/graph.md), connection code, and test cases
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3. **[Workers Execute](docs/key_concepts/worker_agent.md)** → SDK-wrapped nodes run with full observability and tool access
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4. **Control Plane Monitors** → Real-time metrics, budget enforcement, policy management
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5. **Adaptiveness** → On failure, the system evolves the graph and redeploys automatically
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5. **[Adaptiveness](docs/key_concepts/evolution.md)** → On failure, the system evolves the graph and redeploys automatically
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## Run pre-built Agents (Coming Soon)
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@@ -238,6 +238,13 @@ See [environment-setup.md](docs/environment-setup.md) for complete setup instruc
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- [Configuration Guide](docs/configuration.md) - All configuration options
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- [Architecture Overview](docs/architecture/README.md) - System design and structure
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### Key Concepts
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- [Goals & Outcome-Driven Development](docs/key_concepts/goals_outcome.md) - Why Hive is outcome-driven and how goals define success
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- [The Agent Graph](docs/key_concepts/graph.md) - Nodes, edges, shared memory, and how agents execute
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- [The Worker Agent](docs/key_concepts/worker_agent.md) - Sessions, iterations, headless execution, and the runtime
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- [Evolution](docs/key_concepts/evolution.md) - How agents improve across generations through failure data
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## Roadmap
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Aden Hive Agent Framework aims to help developers build outcome-oriented, self-adaptive agents. See [roadmap.md](docs/roadmap.md) for details.
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@@ -382,7 +389,7 @@ Yes! Hive supports local models through LiteLLM. Simply use the model name forma
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**Q: What makes Hive different from other agent frameworks?**
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Hive generates your entire agent system from natural language goals using a coding agent—you don't hardcode workflows or manually define graphs. When agents fail, the framework automatically captures failure data, evolves the agent graph, and redeploys. This self-improving loop is unique to Aden.
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Hive generates your entire agent system from natural language [goals](docs/key_concepts/goals_outcome.md) using a coding agent—you don't hardcode workflows or manually define graphs. When agents fail, the framework automatically captures failure data, [evolves the agent graph](docs/key_concepts/evolution.md), and redeploys. This self-improving loop is unique to Aden.
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**Q: Is Hive open-source?**
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@@ -402,7 +409,7 @@ Yes. Hive is explicitly designed for production environments with features like
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**Q: Does Hive support human-in-the-loop workflows?**
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Yes, Hive fully supports human-in-the-loop workflows through intervention nodes that pause execution for human input. These include configurable timeouts and escalation policies, allowing seamless collaboration between human experts and AI agents.
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Yes, Hive fully supports [human-in-the-loop](docs/key_concepts/graph.md#human-in-the-loop) workflows through intervention nodes that pause execution for human input. These include configurable timeouts and escalation policies, allowing seamless collaboration between human experts and AI agents.
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**Q: What monitoring and debugging tools does Hive provide?**
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@@ -430,7 +437,7 @@ Contributions are welcome! Fork the repository, create your feature branch, impl
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**Q: When will my team start seeing results from Aden's adaptive agents?**
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Aden's adaptation loop begins working from the first execution. When an agent fails, the framework captures the failure data, helping developers evolve the agent graph through the coding agent. How quickly this translates to measurable results depends on the complexity of your use case, the quality of your goal definitions, and the volume of executions generating feedback.
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Aden's [adaptation loop](docs/key_concepts/evolution.md) begins working from the first execution. When an agent fails, the framework captures the failure data, helping developers evolve the agent graph through the coding agent. How quickly this translates to measurable results depends on the complexity of your use case, the quality of your [goal definitions](docs/key_concepts/goals_outcome.md), and the volume of executions generating feedback.
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**Q: How does Hive compare to other agent frameworks?**
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