By Glue Team

What Is Agentic Engineering Intelligence?

Agentic engineering intelligence is AI that autonomously analyzes codebases, identifies issues, and recommends actions.

The Traditional Model

Current tools require humans:

1. Ask a question ("What's my technical debt?")
2. Wait for analysis
3. Interpret results
4. Make decisions
5. Take action

Humans are in the loop at every step.

The Agentic Model

Agentic intelligence:

1. Autonomously monitors codebase
2. Identifies issues (debt, gaps, risks)
3. Analyzes impact
4. Recommends actions
5. Tracks results
6. Learns and improves

AI is autonomous. Humans approve/reject recommendations.

Examples

Traditional: "Is test coverage good?" → Run coverage tool → Read report

Agentic: Coverage drops to 75% → System detects → Recommends: "Add tests to payment service" → Tracks if recommendation improves things

Benefits

• Proactive instead of reactive
• Autonomous instead of manual
• Continuous instead of periodic
• Learning instead of static

Challenges

• How to ensure AI recommendations are good?
• How to prevent over-automation (losing human judgment)?
• How to maintain trust (AI making decisions)?

The Future

Agentic engineering intelligence is coming. Teams will have AI agents:

• Continuously analyzing codebases
• Recommending improvements
• Tracking outcomes
• Learning from results

Humans will focus on strategy and decisions. AI handles the heavy lifting.

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Frequently Asked Questions

Q: Will agentic AI replace engineers? A: No. It will replace tedious analysis. Engineers will focus on decision-making and strategy.

Q: Is agentic AI ready today? A: In early stages. Most tools are still in the "human asks questions" phase.