AI Automation: Deep Sequential Research &get;s Managed through Iterative Planning

Automation Stack & Architecture

• Agent Framework: Hyper Research (Claude-based researcher teamset)
• Execution Logic Layer: Manus Plan Mode (Planning + Execution engine)
• Target Outcome: Comprehensive multi-step investigative reports or project builds (sites, apps, presentations).

Agent Roles & Tools Assignment

• Research Agent (Hyper Research / Claude)
  • Goal: Perform enough depth to complete up to 16 verification steps.
  • Tools/Capabilities: Sequence task decomposition, source matching, local storage report generation.
• Project Manager Agent (Manus Plan Mode)
  • Goal: Analyze requirements and verify feasibility before action.
  • Tools/Capabilities: Task analysis tool, plan editing interface, context gathering (asking clarifying questions), progress monitoring during active tasks.

Step-by-Step Workflow Orchestration

1. Initialize research via `Hyper Research` where the agent breaks a complex query into sequential stages (`task_decomposition`).
2. Execute recursive deep-dives through potentially 16 check cycles per topic.
   
3. Collected data is matched across hundreds of sources using internal comparison logic.
4. Switching to execution phase with `Manus`: The system triggers an initial requirement or project prompt.
5. The agent enters `Plan Mode`, conducting mandatory preliminary assessment instead of immediate building.
6. System generates a draftly prepared detailed way forward; user can modify or rewrite this output manually if required.
7. Upon confirmation signal, any interim plans are executed toward final outputs like sites, apps, or presentations.

Error Handling & Loop Prevention

• Requirement Validation Gate: Using Plan Mode prevents errors caused by misunderstanding requirements before heavy computation begins.
• Contextual Correction: Agent uses proactive questioning/clarification loops (asking questions when context is lackng)to prevent incorrect task direction.
• Iterative Checkpoint Control: Ability to pause during active work allows for mid-process plan re-evaluation and correction via human intervention.

Bottom Line: This setup transforms AI from a simple executor into a sophisticated research team capable of deep investigation while eliminating costly mistakes through forced planning gates.

! DYOR (Do Your Own Research)