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    Axon

    Axon is the leading public safety technology company with an integrated ecosystem of hardware (body cams, in-car cameras, TASER devices, drones) and cloud software (Evidence.com) to help law enforcement, fire, EMS, and commercial security capture, manage, and analyze digital evidence, aiming to increase officer productivity, transparency, and community safety, all while striving to "Protect Life."

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    Opening the Evidence Vault: Platform Strategy for AI-Era Integrations

    @axon•Product Manager

    The Platform Decision You are the newly hired Principal Product Manager for Developer Platforms at a major public safety technology company. The company's flagship product is a cloud-based digital evidence management platform used by thousands of law enforcement agencies. It handles body camera footage, interview recordings, incident reports, and case files — all governed by strict chain-of-custody requirements, audit logging obligations, and PII handling regulations. The platform currently has a basic REST API used by a handful of internal tools and two legacy integration partners. Leadership has decided to evolve it into a composable, open evidence backend — a platform where any authorized surface (internal or third-party) can access, act on, and contribute to evidence data through well-governed APIs. Simultaneously, agencies are beginning to deploy their own AI tools for case analysis, predictive workflows, and automated reporting. These AI agents need to query evidence, check chain of custody, surface case connections, and take actions — all through a permissioned, auditable interface. This is not a traditional API use case. AI agents operate autonomously, make decisions without human confirmation at each step, and may chain multiple operations together. Your VP has asked you to present, in 30 minutes, the first version of your platform strategy. She specifically wants to understand: What gets exposed first vs. later — and why that sequence, not a different one. How you govern who gets access and under what conditions — particularly for AI agents vs. traditional integrations. How you bring engineering, legal, security, and go-to-market into alignment when they will disagree about speed, openness, and risk. What the developer experience looks like for partners who want to build on this platform — and how you measure whether the ecosystem is healthy. Constraints to Consider Chain of custody is legally required. Any integration that touches evidence data must maintain an unbroken, auditable chain of custody. A platform decision that introduces chain-of-custody gaps could invalidate evidence in court proceedings. This is not a product risk — it is a legal and public safety risk. Agency IT environments vary wildly. Some agencies run modern cloud infrastructure; others run legacy on-premise systems with limited API capability. Your platform strategy must work for agencies at both ends of the spectrum. AI agents are not human users. They operate autonomously, may chain multiple API calls without human review, and their actions must be as auditable as a human officer's. Governance for AI agent access is architecturally different from traditional API key access. Legal and security stakeholders have veto-equivalent weight. Shipping a feature that legal or security has not cleared is a non-starter. Your alignment strategy must account for this without becoming paralyzed. You have no existing developer portal, sandbox, or partner certification program. Everything must be built from a basic REST API and two legacy partners. AI Usage Guidance We expect you to use AI tools. We evaluate how you use them — not whether you use them. Evidence of iteration, redirection, and critical evaluation scores higher than a polished output with no process documentation. The single highest-signal indicator: your video answer to the mandatory AI question. If you cannot name a specific moment where you redirected AI output, evaluators will assume you did not. Mandatory AI question for your video: Walk me through one moment where you disagreed with, pushed back on, or redirected what the AI gave you — and what you did instead. Name the specific moment. Explain what the AI produced that didn't meet the bar, what you did differently, and why. Communication note: This is a Principal PM role. You will represent the platform externally to partners and internally to leadership. Speak naturally and with strategic clarity — as if you're briefing your VP of Product. We are assessing the quality and clarity of your reasoning, not verbal polish, accent, or pace. Submission: Upload each deliverable as a separate file directly on the Provn platform: your Platform Strategy Brief, your README document (Sections A, B, and C), and your video walkthrough (MP4 or MOV).

    30 minutes0 submissions
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    Platform Strategy
    Developer Experience
    API Governance
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