App days are numbered: The end state of software will be private, personal, verified, and AI agent-built

A notable development has hit the crypto markets. AI agents could end the app era by turning software into verified, user-built systems AI agents may make running code written by strangers one of those behaviors that later generations struggle to process. A society can normalize a risk for decades, then later reclassify it as reckless once a safer default becomes available. Drinking before driving, riding without seatbelts, smoking indoors, and installing arbitrary binaries from the internet all belong to the same family of historical blind spots.

The common feature is social permission. The behavior persists when the alternative is costly, inconvenient, or technically unavailable. Once the safer path becomes cheap and routine, the old path begins to look irrational.

Market Dynamics

AI agent verification could replace software trust assumptions with attested execution paths, safer defaults, and user-controlled infrastructure. AI agents expose the weakness in the software trust model Modern software still runs on a bargain that we rarely inspect. A developer, company, foundation, or anonymous maintainer writes code.

A distribution channel packages it. A user, enterprise, or operating system runs it. Security then becomes a layered attempt to manage the consequences of that decision.

Permissions, code signing, app stores, endpoint detection, sandboxing, vendor due diligence, and incident response all exist because the core act remains dangerous: executing someone else’s instructions on your machine, inside your account, with access to your data. That trust model has failed at the institutional scale. The SolarWinds compromise showed how malicious code inserted into a trusted software build process could be distributed through normal updates and reach government agencies, technology firms, telecom networks, and other targets across multiple regions.

Market Impact

The operational lesson was structural, and the attack surface was the vendor's legitimacy itself. Once the build process was compromised, the normal marks of trust became delivery infrastructure for the attack. The same pattern appeared in the XZ Utils backdoor, where CISA warned in March 2024 that malicious code had been embedded in versions 5.

1 of a compression library present across Linux distributions. The National Vulnerability Database later described how a disguised test file and build-process manipulation produced a modified liblzma library capable of intercepting and modifying data interactions in linked software. A software supply chain can be compromised far upstream from the user, and then arrive through channels that appear routine.

We've seen that in crypto countless times with DNS and JavaScript npm exploits. The industry response has been to add a stronger process. The NIST Secure Software Development Framework gives organizations a common set of practices for building and acquiring software with reduced risk.

Crypto markets are watching this development closely as investors weigh its potential impact on prices.