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    Kavak Integrates AI Agents Into Core Business Functions

    Venture firm shares details from the used-car marketplace on agent deployment.

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    8 Sources, 51d ago, first seen 51d ago

    TLDR

    Posts from Andreessen Horowitz quote Kavak's chief product and AI officer on scaling agents that handle sales, loans, and coaching. The officer describes a training program called the Jedi Academy for mechanics and other staff to build and ship agents. One post compares today's AI adoption challenges to the gap between early electrical generators and later factory redesigns around electricity. A separate share highlights founders and engineers using agent systems in San Francisco.

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    545.9K

    8 Sources, first seen 51d ago

    Combined views

    545.9K

    8 Sources, first seen 51d ago

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    93 comments
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    210 reposts

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    93 comments
    2K saves
    210 reposts
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    8 Sources

    @a16zAI agents at Kavak sell the cars, underwrite the loans, coach the mechanics, and in one Mexican city, run the entire operation. The Latin American used-car marketplace bet on agents three years ago. Today ~95% of interactions and transactions run end-to-end on AI: NPS tripled, sales conversion doubled, warranties down 26%, car loans approved in less than three minutes. CPO & AI Officer Alejandro Maza joins a16z's Angela Strange and Gabriel Vasquez on how they pulled it off, why adoption without redesign fails, and why they deleted two years of working architecture to start over. 00:00 Intro 01:03 ML before transformers 02:23 Kavak's agent-per-customer architecture 04:59 Three bets: redesign the company, build superhuman agents, change the metrics 10:49 Agents with 2.1x conversion 14:23 Car loans approved in minutes 16:13 1.5x profits in a real city in six weeks 20:13 "Jedi Academy": training mechanics to ship agents 28:44 Destroying two years of work 32:52 Ford's factory: why adoption isn't enough 34:45 Advice for founders @alehandromz @astrange @GEVS94
    @VirtualElenasomething that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai researchers who all behave as if they're living 3-5 years in the future. this manifests in a lot of bruce wayne-type behavior. i've seen workflows of engineers who lie supine on the couch as they wisprflow commands to their agent swarms without ever touching a keyboard. i've seen people build out entire second brains that they orchestrate with openclaw / hermes agents. i know guys who spend $1m +/year on tokens. so i think this conversation with alejandro maza, kavak's chief product and ai officer, with @astrange and @GEVS94 is super interesting because it 1) shows us what an entire organization built around living in the future looks like 2) kavak isn't even based in sf (or the us) so it's very cool to see how an organization outside of the bay area approaches ai from first principles. some takeaways: - alejandro's governing question is what kavak would look like in 2035 with much more capable, cheap intelligence. kavak moved from functional specialists and transactions toward a persistent *agent per customer*, with a long-term goal of maximizing that customer’s lifetime value. -every major model release should trigger a fresh model–harness experiment. kavak had developed a multi-agent framework, but a new model release rendered the company's legacy orchestration outdated, so they discarded 2 years of working infra and rebuilt everything around a simpler agent harness. the lesson is to keep asking: what's the minimum scaffolding the newest model needs to express its intelligence safely and at scale? -kavak built an ai ceo for one city, and says it increased profits by 1.5x in its first month. customer satisfaction, inventory rotation, financing penetration, and other KPIs also improved. maza attributes the result to fields medal-level intelligence applied relentlessly to every number and customer: forecasting performance, assigning daily work, and collecting progress reports. -in light of above points, alejandro's deeper thesis is that the organization, not merely the model or individual worker, should self-improve as new intelligence becomes available.
    @DanielleFongRT @VirtualElena: something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai rese…
    @eriktorenbergRT @VirtualElena: something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai rese…
    @garrytanRT @VirtualElena: something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai rese…

    8 Sources

    @a16zAI agents at Kavak sell the cars, underwrite the loans, coach the mechanics, and in one Mexican city, run the entire operation. The Latin American used-car marketplace bet on agents three years ago. Today ~95% of interactions and transactions run end-to-end on AI: NPS tripled, sales conversion doubled, warranties down 26%, car loans approved in less than three minutes. CPO & AI Officer Alejandro Maza joins a16z's Angela Strange and Gabriel Vasquez on how they pulled it off, why adoption without redesign fails, and why they deleted two years of working architecture to start over. 00:00 Intro 01:03 ML before transformers 02:23 Kavak's agent-per-customer architecture 04:59 Three bets: redesign the company, build superhuman agents, change the metrics 10:49 Agents with 2.1x conversion 14:23 Car loans approved in minutes 16:13 1.5x profits in a real city in six weeks 20:13 "Jedi Academy": training mechanics to ship agents 28:44 Destroying two years of work 32:52 Ford's factory: why adoption isn't enough 34:45 Advice for founders @alehandromz @astrange @GEVS94
    @VirtualElenasomething that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai researchers who all behave as if they're living 3-5 years in the future. this manifests in a lot of bruce wayne-type behavior. i've seen workflows of engineers who lie supine on the couch as they wisprflow commands to their agent swarms without ever touching a keyboard. i've seen people build out entire second brains that they orchestrate with openclaw / hermes agents. i know guys who spend $1m +/year on tokens. so i think this conversation with alejandro maza, kavak's chief product and ai officer, with @astrange and @GEVS94 is super interesting because it 1) shows us what an entire organization built around living in the future looks like 2) kavak isn't even based in sf (or the us) so it's very cool to see how an organization outside of the bay area approaches ai from first principles. some takeaways: - alejandro's governing question is what kavak would look like in 2035 with much more capable, cheap intelligence. kavak moved from functional specialists and transactions toward a persistent *agent per customer*, with a long-term goal of maximizing that customer’s lifetime value. -every major model release should trigger a fresh model–harness experiment. kavak had developed a multi-agent framework, but a new model release rendered the company's legacy orchestration outdated, so they discarded 2 years of working infra and rebuilt everything around a simpler agent harness. the lesson is to keep asking: what's the minimum scaffolding the newest model needs to express its intelligence safely and at scale? -kavak built an ai ceo for one city, and says it increased profits by 1.5x in its first month. customer satisfaction, inventory rotation, financing penetration, and other KPIs also improved. maza attributes the result to fields medal-level intelligence applied relentlessly to every number and customer: forecasting performance, assigning daily work, and collecting progress reports. -in light of above points, alejandro's deeper thesis is that the organization, not merely the model or individual worker, should self-improve as new intelligence becomes available.
    @DanielleFongRT @VirtualElena: something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai rese…
    @eriktorenbergRT @VirtualElena: something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai rese…
    @garrytanRT @VirtualElena: something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai rese…