Continuous Alignment: Collaborating Effectively with Agentic AI

As artificial intelligence systems become more agentic—capable of planning, reasoning, and executing complex tasks—our methods of interacting with them must evolve. We can no longer treat AI as a simple question-and-answer machine; instead, we must treat it as a collaborator. This requires a new paradigm for human-AI interaction, a process I call Continuous Alignment.

Continuous Alignment is a structured, iterative process designed to ensure that you and your AI agent share a deep, mutual understanding of a task before any significant execution begins. By focusing on alignment upfront, you minimize wasted effort, reduce hallucinations, and achieve better outcomes.

Here is a breakdown of the Continuous Alignment process:

1. Start with a High-Level Idea

Begin by discussing your overarching concept or goal with the AI agent. This doesn’t need to be perfectly formed; it’s the starting point for a conversation. Treat it like a brainstorming session with a capable colleague.

2. Provide Supporting Context

AI models have vast general knowledge but lack specific context about your project, your environment, or your specific needs. Provide any supporting documentation, code snippets, architectural diagrams, or contextual information the AI needs to truly understand the problem space.

3. Invite Clarification and Improvement

Don’t just dictate; invite the AI into the process. Explicitly ask the AI to ask clarifying questions or suggest improvements to your initial idea. A good agentic AI can often spot edge cases or alternative approaches you might have missed.

4. Request a Summary to Verify Alignment

This is a critical step. Ask the AI to generate a summary of the concept, the goals, and the proposed approach. Read this summary carefully. Does it accurately reflect what you intended? This is the core “alignment check.”

5. Iterate Until Aligned

If the summary isn’t quite right, repeat steps 2 through 4. Provide more context, answer the AI’s questions, and ask for a revised summary. Continue this iterative loop until you read the AI’s summary and think, “Yes, exactly. We are on the same page.”

6. Save the Alignment as a “Plan”

Once you are fully aligned, save the AI’s final, approved summary as a “plan” file (e.g., plan.md). This document serves as the ground truth for the implementation phase. It’s a contract between you and the AI.

7. Execute Using the Plan

Now, authorize the AI to begin implementation, using the saved plan file as its blueprint. Because you invested time in the alignment phase, the AI’s execution will be much more targeted and accurate.

8. Review and Cleanup

Once the AI has completed the implementation, review the work. While Continuous Alignment significantly reduces errors, human oversight is still crucial. Clean up the implementation, make necessary adjustments, and ensure it meets your quality standards.

9. Document Learnings for the Future

At the end of the collaborative session, don’t just close the terminal. Have the AI write documentation on what it learned, what new patterns were established, and what changed in the system.

This final step is vital. We use these learnings to bootstrap future agentic AI work. By documenting the newly established context, the next AI agent you spin up will start with a much higher baseline understanding, making the next Continuous Alignment cycle even faster and more effective.