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Axon CPTO on How Law Enforcement Uses AI to Save Lives, Not Just Hit Metrics | Jeff Kunins | E303

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jeff Kunins, Chief Product Officer and Chief Technology Officer at Axon, the company that created the Taser and the body cameras law…

Jeff KuninsguestCarlos González de Villaumbrosiahost

Jul 8, 202641mWatch on YouTube

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Chapter summaries

Axon’s moonshot goals and early AI ethics stance
Jeff Kunins opens with two defining themes: Axon’s long-term goal to cut gun-related deaths between police and the public, and a firm posture on responsible AI. He frames differentiation as building only what’s necessary while still engaging with hard societal trade-offs rather than avoiding them.
- •Axon set a 10-year goal to reduce gun-related deaths between police and the public in the US by more than 50%.
- •Axon was the first tech company Jeff cites as declaring a moratorium on facial recognition due to bias and risk concerns.
- •Jeff emphasizes a philosophy of not rebuilding what’s unnecessary, but building what’s required for market differentiation.
- •He argues progress requires engaging with difficult issues rather than avoiding them.
- •Axon’s job, as Jeff describes it, is to build products that help agencies choose policies thoughtfully rather than setting policy themselves.
Host framing: why Axon is a unique real-world AI + hardware company
Carlos introduces Jeff and positions Axon as a large, fast-growing public safety technology company that combines AI, software, and hardware. He previews topics like AI use in devices, Axon’s facial recognition moratorium and re-evaluation, embedding external voices in product work, and model strategy.
- •Carlos introduces Jeff as Chief Product Officer and Chief Technology Officer at Axon.
- •Axon is described as ingesting more video per year than YouTube and producing Tasers and body cameras.
- •The host frames the conversation around using AI to “save lives, not just hit metrics.”
- •Planned discussion includes Axon’s facial recognition moratorium and what later changed.
- •Planned discussion includes embedding activists/researchers into product squads and a build-vs-buy model approach.
What Axon builds: from body cameras and Tasers to a broad public safety platform
Jeff explains Axon’s scope beyond its best-known devices, describing a portfolio spanning hardware, cloud software, and adjacent markets. He also emphasizes Axon’s scale and its founder-led mission focus.
- •Jeff describes Axon as the leading public safety technology company and a high-growth S&P 500 company.
- •Axon is widely known for police body cameras and Taser products, plus cloud-based digital evidence management.
- •He says Axon is reinventing many hardware and software categories used in public safety globally.
- •Axon serves law enforcement agencies and also adjacent markets like federal government, retail, and healthcare.
- •Jeff highlights Axon’s founder-led mission: “protect life and obsolete the bullet.”
Founder origin story: from tragedy to commercializing the Taser
Jeff tells the founding story centered on Rick Smith’s motivation after a road rage tragedy and his belief that “obsoleting the bullet” is a solvable technology problem. He describes how the company commercialized the Taser and why Axon views it as uniquely effective with minimal severe harm.
- •Jeff says Rick Smith founded the company in 1993 after two high school football teammates were killed in a road rage incident.
- •Rick sought a non-lethal alternative and found a retired NASA scientist who had conceived a taser concept but hadn’t commercialized it.
- •The company began in a garage in Scottsdale, Arizona, originally as Taser.
- •Jeff claims Tasers have saved hundreds of thousands of lives around the world.
- •He argues Tasers “hack the curve” by combining high effectiveness with near-zero serious injury/death compared to other force options.
Scaling founder leadership: trust in the field + deep invention focus
Jeff explains how Axon’s founder remains effective at scale by concentrating on two poles: deep customer engagement and hands-on invention. Jeff describes his own role as translating the founder’s ideas into what the company can actually build and ship.
- •Jeff predicts Rick Smith will be viewed as one of the most impactful tech founders of the last 50 years.
- •Rick spends significant time with customers to build vision and trust in “trust-centric markets.”
- •Rick also stays deeply involved as an inventor/technologist in specific parts of the portfolio.
- •Jeff describes his job as turning “infinite idea generation” into shippable products.
- •The founder’s focus allows the rest of the leadership team to run the company at scale.
C-suite structure and why “perfect org charts” can be a trap
Jeff and Carlos discuss how Axon structures leadership so the founder can focus on strengths without becoming an operational bottleneck. Jeff shares a principle learned earlier in his career: if an org chart looks too clean on a slide, it’s likely wrong for real execution.
- •Jeff argues organizations should be dynamic, not optimized to look neat on PowerPoint.
- •Axon has the founder as CEO and a president (Josh Isner) who helps run and operate the company.
- •Jeff says C-level officers (including himself) report into the president to free the CEO to focus.
- •The structure is designed to support founder focus on field engagement and invention.
- •Carlos frames the challenge as balancing invention vs. business operation at large scale.
Product/R&D org design for a hardware + software business with bundled subscriptions
Jeff explains Axon as both high-scale SaaS and a hardware company, with a go-to-market approach he compares to “Amazon Prime-ification.” He then describes a hybrid org model mixing GM ownership of product lines with functional engineering leadership.
- •Jeff describes Axon as “hardware plus software,” operating at scale in both.
- •Axon sells multi-year, all-in bundled subscriptions covering hardware, consumables, and software across tiers.
- •Bundles can include devices like Tasers, body cameras, drones/first responder docks, and VR headsets, plus various SaaS tools.
- •Jeff’s org includes SVP/GM-style leaders for major product lines with dotted-line engineering support.
- •He also maintains top-level functional leaders for hardware, software, and science, with dedicated leaders mapped to each pillar.
Why Axon keeps InfoSec inside R&D
Security is presented as foundational to Axon’s products and customer trust, so Jeff explains the organizational choice to embed InfoSec within R&D rather than separating it. This is tied to building secure devices and systems from the ground up.
- •Jeff says security is fundamental to everything Axon does.
- •Axon places InfoSec within R&D rather than elsewhere in the company.
- •The CISO sits on Jeff’s staff as part of his organization.
- •Jeff links this structure to the “security lifecycle” being core to engineering and building.
- •The approach reflects the high-trust environment of public safety technology.
Selling to government: long cycles, complex procurement, and predictability via bundles
Jeff compares government sales to “large whale enterprise” sales with a relatively small set of big customers, each wanting custom considerations. He highlights long, intricate procurement processes and how predictable, bundled pricing helps agencies secure approvals.
- •Jeff describes government as a “head-weighted market” with fewer, larger customers that feel like special cases.
- •Sales cycles are longer and involve complex procurement requirements.
- •Procurement can require approvals from bodies like city councils and mayors, depending on the agency.
- •Axon’s Prime-like bundles are designed to make buying easier and spending more predictable.
- •Jeff says most Axon contracts tend to be around five years, with some extending to ten years or more.
Federal footprint and the Dedrone acquisition as a wedge into defense-adjacent use cases
Jeff outlines Axon’s presence in federal civilian agencies and limited military contexts like base protection, while noting a smaller footprint in “raw defense.” He describes Dedrone’s role in counter-drone protection and how it expands Axon’s reach into defense-adjacent deployments.
- •Jeff says Axon has a substantial footprint in federal civilian agencies, including the FBI and parts of DHS.
- •Within the military, Axon is more present in non-combat contexts like military police and base protection.
- •Axon is relatively small in core defense today, but sees it as a growth area.
- •Jeff describes Axon’s acquisition of Dedrone as a major move into counter-drone protection.
- •He cites Dedrone deployments including early Ukraine war RF sensor deployment and upcoming protection for World Cup cities in the US.
Measuring outcomes: tying product strategy to lives saved and time returned to officers
Carlos asks how Axon measures impact beyond conventional SaaS metrics. Jeff describes a measurable moonshot KPI (gun-related deaths) and explains how certain products influence the outcome directly while others help indirectly by freeing officer time.
- •Carlos contrasts traditional SaaS KPIs with Axon’s focus on outcomes like lives saved.
- •Jeff describes a 10-year goal to reduce gun-related deaths between police and the public in the US by more than 50%.
- •He notes the metric is measurable via public records, even if Axon’s precise contribution is hard to isolate.
- •Jeff lists products he says directly influence outcomes: Taser, VR training, and drones as first responder programs.
- •He also describes productivity tools (including DraftOne) as indirectly helping by giving officers more time back.
Shipping hardware fast and improving it over time with OTA + cloud updates
Carlos probes how Axon iterates quickly despite shipping physical devices. Jeff describes “multiple clock speeds” across projects, then gives an example of shipping a pole-based license plate camera system in under a year and continually improving capabilities via secure OTA updates and cloud changes.
- •Jeff says Axon must operate at multiple clock speeds, balancing scrappy speed with high-volume rigor.
- •He cites a new pole-based license plate detection camera system shipped from decision to GA in less than one year.
- •Jeff positions the initiative as ethics-first and transparency/auditability-oriented given market concerns.
- •He explains Axon has long experience delivering safe, secure OTA firmware updates to devices in the field.
- •Capabilities can be improved through a mix of edge processing, firmware/app updates, and cloud-side updates without changing hardware.
How Axon runs OTA rollouts: security reviews, reliability, flighting, and customer-controlled adoption
Jeff details the operational requirements for safely updating connected public safety devices. He emphasizes security hardening, an OTA stack that avoids bricking devices, staged rollouts, and managing which changes are automatic vs. customer-controlled.
- •Devices must pass security reviews so updates are authorized and resilient even if someone gains physical access.
- •A reliable OTA update stack is required to deliver firmware/software without bricking devices.
- •Axon uses a flighting system to roll out to subsets, validate performance, and soak before broad release.
- •Cloud updates follow similar staged approaches with partial rollout and validation.
- •Some updates are pushed broadly (especially new settings), while others require customers to choose when to adopt, requiring strong version/release management.
AI strategy in products: build what differentiates, buy what’s commoditized
Jeff explains Axon’s approach to AI as using AI across products and internal engineering, while being selective about building models. He distinguishes between first-party models for demanding real-time computer vision tasks and using widely available LLMs for other workflows.
- •Jeff says Axon aims to build AI into everything it builds and use AI to build what it builds.
- •He states Axon does not build foundation LLMs.
- •Jeff describes a principle: don’t rebuild what you don’t have to; build what you must to be differentiated.
- •Axon builds first-party models for real-time license plate and vehicle attribute detection where price/performance demands are high.
- •For products like DraftOne, Jeff says Axon uses best-in-class open LLMs and continuously experiments rather than being “precious.”
AI on top of massive video evidence: redaction workflows and human-time savings
Jeff describes how Axon’s digital evidence pipeline historically focused on ingestion, storage, and sharing across the “capture to courtroom” lifecycle. He then explains where AI adds value: assisting specialized workflows like redacting sensitive information that departments otherwise handle manually.
- •Jeff says the core workflow is high-scale ingestion and secure storage of body camera video, plus sharing, editing, redacting, and courtroom-related processes.
- •He describes the end-to-end flow from capture through prosecutors, defense attorneys, courts, and public records requests.
- •AI becomes important in “workloads on top” of storage, particularly redaction.
- •Redaction removes personally identifiable or inappropriate information, focusing on victims/suspects rather than bystanders or screens.
- •Axon has long used AI-powered redaction assistants to reduce manual, time-consuming video editing work, and expects improvement with more sophisticated models.
When not to deploy AI: facial recognition moratorium, cautious re-entry, and responsible innovation governance
Jeff explains Axon’s decision to pause facial recognition for years due to insufficient value relative to bias and risk, and how the company is now carefully testing narrow facial matching use cases. He also describes Axon’s independent ethics/equity advisory approach and how external voices are embedded in product development to anticipate issues and build transparency.
- •Jeff says Axon has maintained independent third-party ethics/equity advisory boards in some form for many years.
- •Axon declared a moratorium on facial recognition in 2019 because the risks outweighed benefits at the time, and held it for six years.
- •Jeff says Axon recently began careful evaluation of narrow facial matching use cases in conjunction with its ethics council and agencies in Canada.
- •He argues the technology itself is similar across contexts; what changes is context, expectations, and consequences, with policing carrying higher stakes.
- •Jeff describes Axon’s Responsible Innovation approach: seek external advice, maintain transparency about what’s being built, and embed advisory members with product managers—aiming to “make the right things easier and the wrong things harder.”

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