The "AI SOC Analyst" is a band-aid on a broken leg. A ton of security startups are dropping autonomous agents into legacy SOC queues to speed up triage. It’s a waste of budget. You are just optimizing a workflow that shouldn't exist in an AI-native world. Think about factory electrification in the 1920s. Early factories just swapped massive steam engines for large electric motors and saw zero productivity gains. It was only when they threw out the blueprints, put tiny motors at individual workstations, and changed the floor layout that productivity skyrocketed. Cybersecurity is stuck in the steam era. Legacy SIEMs force you to pay an insane markup on basic data storage while your team wastes finite engineering cycles tuning noisy alerts. The future isn't a faster SOC. It's a decentralized security data lake. New platforms like @RunReveal and @scanner_dev are cutting out the middleman by running directly on top of cheap infrastructure like S3 and ClickHouse. Meanwhile, tools like @cotoolai are perfecting the AI blue-team application layer. The real win here isn't autonomous code remediation; it's fixing the tuning loop. Most alerts are false positives. When an alert hits, tools like RunReveal can run an immediate background investigation, auto-close the noise, and hand the human generalist the exact context needed to tune the rule in seconds. You don't need a dedicated SOC or an army of analysts anymore. You need elite data infrastructure and software that lets a single generalist focus on outcomes, not implementation details. open.substack.com/pub/frankl…