Building Better Software: A New Blueprint for the Agentic SDLC | Sonar Summit 2026

Описание: How will software development evolve as AI coding agents become more autonomous?

In this Sonar Summit 2026 keynote, Tariq explores how the rise of agentic AI development is reshaping the software development lifecycle. Traditional continuous integration workflows rely on frequent human-driven commits, but AI agents can generate large batches of code asynchronously—introducing new challenges for verification, maintainability, and software quality.

To address this shift, Tariq introduces the Agent-Centric Development Cycle (AC/DC)—a blueprint designed to help organizations scale AI-driven development while maintaining strong standards for code quality and security.

In this talk, you’ll learn:
How autonomous coding agents are changing the SDLC
Why traditional CI workflows struggle with AI-generated code
What the Agent-Centric Development Cycle (AC/DC) is and how it works
How organizations can implement reliable software verification for AI-generated code
How development teams can maintain trust and accountability in AI-assisted workflows

Discover how engineering teams can adapt their development processes to support AI coding agents while ensuring their codebases remain secure, maintainable, and trustworthy.

Timestamps:
00:00 — Introduction
00:35 — Sonar’s Origins and Global Developer Community
01:21 — Supporting 40+ Programming Languages and 7,000 Issue Types
02:25 — Quality Gates and Reducing False Positives in Code Analysis
03:13 — AI Integrations and Trusted Code Quality Outcomes
03:49 — Reducing AI-Related Outages with Sonar Code Quality Tools
04:16 — Why Traditional CI/CD Is Giving Way to Agent Workflows
05:04 — The Rise of Agent-Centric Software Development
05:30 — Developers Shifting from Coding to Design and Review
05:53 — Why Agentic Development Requires Guardrails
06:16 — Introducing AC/DC: A New AI Development Lifecycle
06:57 — Why Traditional Code Review No Longer Scales with AI
07:30 — Validating AI-Generated Code Before Check-In
07:47 — The Four Stages: Guide, Generate, Verify, Solve
08:31 — Why Every Company Needs an AI Agent Platform
09:03 — Guide Stage: Context, Constraints, and Coding Standards
09:35 — Verify Stage: AI Can Introduce Complex Bugs and Vulnerabilities
10:05 — Inner-Loop and Outer-Loop Verification for AI Code
10:45 — Solve Stage: Automated Remediation and Learning Loops
11:22 — What the AC/DC Model Requires: Environment, Context, and Trust
12:05 — Why Code Verification Is Mandatory for AI-Generated Code
12:43 — Deterministic Static Analysis Grounding AI Code Review
13:36 — Best Practice: Verification Signal Fusion for AI Development
14:02 — Embedded Context and Fine-Tuned Models for Better AI Coding
14:53 — Specialized AI Coding Agents vs General-Purpose Models
15:43 — Practical Steps to Adopt the AC/DC Development Model
16:04 — Step 1: Require Verification for All AI-Generated Code
16:30 — Step 2: Enable Tool Calling for AI Coding Agents
16:48 — Step 3: Use Agents to Detect and Remediate Code Issues
17:17 — How Sonar Maps to the AC/DC AI Development Framework
17:42 — Dynamic Context and the Sonar Sweep Roadmap
18:21 — AI-Enhanced Code Verification and Issue Prioritization
19:04 — Sonar Analyzers Designed for Agentic Code Analysis
19:29 — AI Hunting Agents Expanding Code Verification Coverage
19:57 — Solve Stage: AI CodeFix and Remediation Agents
21:00 — End-to-End AI Workflow: Guide, Verify, and Solve

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