Sonar Summit 2026
| title | author | length |
|---|---|---|
| Building Better Software: A New Blueprint for the Agentic SDLC | Tariq Shaukat | 22m |
Argues that CI’s micro-commit model breaks when autonomous coding agents batch large changes and proposes the Agent-Centric Development Cycle (AC/DC) with four… | ||
| Software Engineering + AI = ? | The Future of Development | Gergely Orosz | 37m |
Industry adoption is rapid and concrete: internal data shows 40–50% of Cursor’s code authored by Cursor, engineers commonly run 4–8 parallel agents, and more… | ||
| Building the Trust Layer for the Agentic Era | Ori Yitzhaki | 21m |
Shows a concrete roadmap: Sonar deploys context augmentation that serves code, docs, tickets and live SonarQube state to agents, an MCP server to connect IDEs… | ||
| The Future of Engineering Teams in an AI-Native World | Laura Tacho, Lauren Hanford | 44m |
Argues that tool choice is often least important and organizations win by investing in CI/CD and DevX as AI accelerants; reports 96% distrust, 45% verify for… | ||
| How to Verify AI-Generated Code with Codex | Vaibhav Srivastav, Tom Howlett, JOHN CLIFTON | 48m |
OpenAI uses Codex to review every pull request and assist across app, CLI and IDE surfaces; Codex 5.3 Spark runs ~60% faster than 5.2, spins up sub‑agents to… | ||
| Code Security and Verification in the AI-Centric SDLC | JEFF CLAWSON | 16m |
Sonar positions itself as a verification layer across IDEs, pipelines and governance, shipping an MCP server that partners (Microsoft, Google, JFrog) use to… | ||
| The reality of developers using AI | State of Code Developer Survey | Anirban Chatterjee | 15m |
Survey of 1,100+ developers finds 72% daily users and 58% using AI in production, but 96% don’t fully trust AI-generated code while only 48% always review it… | ||
| Solving the AI Accountability Crisis in the Software Supply Chain | SEGEV SHARABI | 12m |
Claims that AI creates a 10x code volume surge and a 300% rise in supply‑chain attacks, with almost 80% of compliance issues found post‑deploy, drive a demo… | ||
| How Freshworks Scales Shift-Left Security with SonarQube | PRAVIEN SK, Anirban Chatterjee | 22m |
Freshworks embeds SonarQube into CI templates and IDEs so every pull request gets real‑time quality, vulnerability and secrets checks, reducing onboarding from… | ||
| The AI Code Review Bottleneck: Escaping the Velocity Trap | ABHI DAS | 19m |
AI tools boost output but create bigger, messier PRs: median PR size +33%, lines per developer +76% and 91% longer review time while MER’s RCT shows developers… | ||
| AI-Generated Code: Who Is Responsible for the Bugs? | ABHISHEK VEERAMALLA | 23m |
Claims that 46% of new GitHub repos are AI-assisted and that AI code shortens review cycles drive the argument: automated checks must run on every PR with SCA… | ||
| Which Code Issues Actually Matter? | Prioritizing SonarQube Findings | Anand Kulkarni | 14m |
CoreStory and Sonar integrate via MCP so an AI agent pulls Sonar findings and CoreStory architecture context to decide what to fix. Demo shows an agent… | ||
| How Sonar Builds a Culture of Innovation and Accountability | ANDREA MALAGODI | 06m |
Company-wide Weekly Friday Demo Day runs at 4:30 CET for 30 minutes on Zoom as an unedited open mic where engineers show experiments, features and failures… | ||
| Sonar-Powered LLM Context Augmentation for AI Coding Agents | ANTONIO AVERSA | 15m |
SonarQube connects to AI IDE agents (Cursor, Claude Code) via an MCP server that exposes tools like get intended architecture and get neighbor to inject… | ||
| Achieving Trusted Code in the Agentic SDLC | Baruch Sadogursky | 19m |
Live demo copies an Express REST API prompt into Claude Code, analyzes the generated task-tracker with SonarQube and Sonar MCP (shows 65 issues to zero), then… | ||
| The Self-Healing Applications Decade | Future of Software Reliability | BORIS PASKALEV, Anirban Chatterjee | 22m |
Claim: engineering teams must add a structured decision engine that correlates SonarQube, Sentry, Jira and AI-generated PR signals to prioritize what to fix… | ||
| Software Architecture Management in SonarQube | Chris Chedgey | 18m |
SonarQube extracts a current architecture on every scan and displays it as a navigable map (classes, packages, modules) with pan/zoom and high‑level views… | ||
| Streaming Code Quality and Security in Healthcare | CHARY NARASIMHA, DEEPAK PANDEY, ANDREW OSBORNE | 22m |
Roche moves from fragmented workflows to a standardized DevSecOps blueprint that scales across 20,000 developers and ~80 million lines of code, using SonarQube… | ||
| Scaling Code Quality at Cisco | The Evolved AI-Driven SDLC | STEPHEN BYRNES, Lauren Hanford | 38m |
Cisco embeds SonarQube intelligence into an agentic SDLC, running an autonomous teammate called Koda agent in Jira that pulls Sonar issues, creates plans… | ||
| Building Guardrails for AI Coding Systems | JOHN CLIFTON, Cole Medin | 34m |
Engineering teams face rapid AI code generation—Sonar finds 42% of committed code is AI‑generated (6% in 2023, projected 65%) while 96% of developers distrust… | ||
| SonarQube MCP Server Demo | Secure AI Coding Workflows | DANIEL BOREK | 15m |
SonarQube MCP Server runs as a local Docker container, central host, or JAR and connects IDE agents like Cursor, VS Code or CLI assistants to SonarQube Cloud… | ||
| SonarQube Enterprise Architecture | Deploying SonarQube at Scale | DANIEL BOREK | 15m |
Architecture options for running SonarQube at enterprise scale include self-hosted vs SaaS with concrete tradeoffs: self-hosting requires VMs or containers, a… | ||
| Learning in the AI Era | Future of Software Development | Cat Hicks, Luis Villa | 29m |
Argues that measurable learning culture predicts team productivity and that small habits beat big one‑offs, reporting surveys across thousands of developers in… | ||
| Automating Code Fixes with SonarQube Remediation Agent | ALEXANDER RAGE, EDGAR KUSSBERG | 12m |
SonarQube Remediation Agent pairs static analysis with an AI CodeFix to generate verified patches inside the IDE or SCM and open PRs automatically, turning… | ||
| The AI Productivity Paradox in Engineering | CHRIS GRAMS, Ganesh Datta | 22m |
Data shows AI coding assistants raise deployment velocity ~20% while incidents per PR climb ~23.5%, and fewer than expected organizations have formal AI… | ||
| Why AI Code Passes OWASP but Fails MISRA | Geoffray Adde | 19m |
Explains why identical C++ snippets can be accepted by one standard and rejected by another because standards have different goals and decidability… | ||
| AI-Powered Security in GitLab | Sonar Integration Demo | George Kichukov, Manish Kapur | 26m |
Demo shows Sonar scanning wired into GitLab CI and merge requests so Sonar results appear inline, the security dashboard aggregates findings, and GitLab… | ||
| Code Security in the AI Era | SAST, SCA & Secrets Detection | Johannes Dahse | 22m |
Claims a research set of 8 billion lines, 1 million developers, 40,000 orgs finds ~400 million issues — about one issue every 800 LOC (≈1–2 security issues per… | ||
| AI Code Quality Debt: What Strong Engineering Teams Do Differently | Kesha Williams | 21m |
AI-generated code increases merged output but hides a growing quality debt that teams pay as a measurable rework rate. Example numbers: teams see ~40% more… | ||
| Humans + AI: The Future of Software Development Teams | Kunal Kushwaha | 18m |
AI coding tools deliver a measured boost—about 15% productivity improvement across organizations—with pockets of bigger wins like a 6x jump in test generation… | ||
| Why Software Quality Is the Key to Scaling AI Development | Lena Hall | 28m |
Argues that AI speed is commoditized so teams must build verification systems that catch non‑deterministic failures, citing a three week ETL bug from a missing… | ||
| The LLM Leaderboard: Benchmarking AI Coding Models | Manish Kapur | 16m |
Sonar evaluates 40+ coding LLMs on 4,400+ Java assignments using Sonar’s leaderboard and SonarCube-based analysis and reports concrete findings: Opus 4.5 leads… | ||
| How to Scale AI Coding for Real Business Outcomes | Jellyfish Use Case | NICHOLAS ARCOLANO, PHD | 27m |
Jellyfish aggregates 20 million pull requests from roughly 200,000 engineers at 1,000 companies and finds concrete effects: interactive tools like Copilot… | ||
| Automated Code Review for AI Agents | Nicolas Peru | 11m |
Demonstrates running automated verification against AI-generated commits using a simple Gradle project, a copied Java quality profile with one added rule, and… | ||
| How to Manage Software Architecture with SonarQube | Olivier Gaudin | 20m |
SonarQube adds a concrete architecture layer that reverse‑engineers a current architecture per analysis, lets teams define a top‑down intended architecture… | ||
| The Context Flywheel for AI Coding Teams | Patrick Debois, EDGAR KUSSBERG | 37m |
Argues that organizational context—not model choice—drives AI coding quality, and describes a runnable loop: Context Development Lifecycle (generate, evaluate… | ||
| Scaling Software Integrity with Automated Code Verification | PAUL EDWARDS, JOHN CLIFTON | 27m |
Wolters Kluwer embeds automated verification into pull requests using SonarQube PR analysis to enforce a single baseline of checks, mandates 80% test coverage… | ||
| The AI Accountability Mandate: Securing the Software Supply Chain | Ronny Belenitsky, Anirban Chatterjee | 22m |
Organizational strategy focuses on automated guardrails: Sonar runs code and SCA scans to create SBOMs and pass/fail quality gates, JFrog attaches those scan… | ||
| How TD Bank Scaled Code Quality & Security with SonarQube | SANJIT PAIKARAY | 10m |
TD Bank scales SonarQube across thousands of projects to turn it from a developer IDE helper into an enterprise governance platform supporting $2.1 trillion in… | ||
| I’m Not Writing Code Anymore—Now What? | The 7-Step Workflow | SANTIAGO VALDARRAMA | 26m |
Argues developers shift from coding to orchestrating AI with a practical 7-step workflow that assigns planning, single‑responsibility tasks, strict context… | ||
| Scaling Software Quality at Xero with SonarQube Cloud | Sarah Burgess | 16m |
Xero migrates SonarQube Server to SonarQube Cloud, onboarding about 3,000 repositories in one scripted run and ending with 3,500 repositories live; a mistaken… | ||
| What’s New in SonarQube | Governance and Quality Gates at Scale | Brian Cipollone | 16m |
SonarQube adds enterprise SCA with SBOM export and portfolio-level dependency risk plus license profile management that can break builds via quality gates and… | ||
| Engineering Intelligence & Developer Productivity in the AI Era | Şükrü Çakmak, Emre Dündar, Ömer Çelebioğlu | 16m |
Claims that engineering intelligence platform Oobeya centralizes SonarCloud/SonarQube, Jira, GitHub and CI/CD into team scorecards and an AI assistant that… | ||
| Symbolic Execution Explained: Finding Bugs in Complex Code Paths | Tim Pohlmann | 18m |
Sonar’s static analyzer uses symbolic execution to simulate execution paths with symbolic ranges (e.g., remainder 0..9 or -9..0) and flags contradictions; it… | ||
| How to Verify AI-Generated Code with AI Coding Agents | Tom Howlett | 16m |
Sonar integrates with MCP-enabled AI agents (Claude demoed) to run run advanced code analysis on code diffs, returning deep static-analysis results in 1–3… | ||
| SonarQube & Dynatrace Integration: Enrich Security Findings | Valeriy Leykin | 14m |
Dynatrace ingests SonarQube findings via a SonarQube extension, maps them into a semantic dictionary, and runs workflows that trigger on new critical/high… | ||
| Developing with AI: Balancing Speed and Code Quality | VIKTOR VORONA | 13m |
An experiment builds a complex Electron app with multiple backends and native integrations using Claude AI and ships fast until complexity rises. The team… | ||
| Escape the Try-Again Loop: Verifying AI-Generated Code | NATE MCKIE, TONY PERETTI, JIM DECARLO | 32m |
Worldwide Technology reports AI coding agents make teams about twice as fast, finishing a customer mobile app in half the contract time, but that velocity… | ||
| Shifting Security Left: Scaling Code Quality in a Regulated Landscape | Abhay Sharma, Anirban Chatterjee | 33m |
A regulated Australian organization moves from a fragile self‑hosted SonarQube Server to SonarQube Cloud, enforces mandatory quality gates in every CI/CD… | ||
| Advanced SAST: How to Secure AI-Generated Code | Mario Bastardo | 16m |
AI code gets treated as regular code but needs extra verification: Sonar combines SCA and taint-style static analysis to trace data flows into dependencies and… | ||
| How to Secure the AI Stack from Code to Runtime | ORON NOAH, DONALD FISCHER | 25m |
Explains a concrete Sonar + Wiz integration that ingests Sonar static-analysis findings into the Wiz security graph to map where a repo issue becomes a runtime… | ||
| How to Improve AI-Generated Code with SonarSweep | Joe Tyler | 13m |
SonarSweep uses Sonar static analysis to analyze, deduplicate and automatically remediate training code, then fine‑tunes models on a curated corpus of 70K Java… | ||
| GitHub Copilot Agents + Sonar | The Blueprint for Agentic Development | HARRY WANG, LUIS BITENCOURT-EMILIO | 24m |
Claims that code generation now outpaces reading and testing and that verification becomes the real bottleneck, demonstrated with a live Copilot Agents +… | ||
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