Individual AI adoption creates team-level risk. This track covers governance, security architecture and how to move from individual AI to organisational AI that is actually owned.
One engineer uses Claude carefully. Another is vibe coding a feature. A third has wired up an MCP workflow no one else knows about. The organisation does not see the risk until something reaches production. Track 4 provides the framework to close that gap systematically.
Guide series for Track 4 is in development. Start with the articles below.
The tool your team uses will change. The rules in your repository won't. Organizations that encode their AI standards in repo-level rule files build lasting capability. Those that leave it to individual prompting build nothing that survives the next tool switch.
→ Reality CheckWhat nobody warns you about the security consequences of multi-component AI architectures in production.
→ TechnicalClaude's Code Review runs a fleet of agents against every pull request. 54% of PRs get findings. Less than 1% are false positives. The accountability still lands on the engineer who merges.
→ MethodologyWhen senior developers spend their days cleaning up AI-generated chaos, the problem isn't the AI — it's the organization choosing the wrong paradigm. An analysis of what actually goes wrong when vibe coding enters production pipelines.
→A deep dive for technical leaders. Governance frameworks, security architecture and concrete decisions about how your organisation owns AI usage going forward.
Duration: 7–9 hours