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Larry Cheng

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@larryvc

Co-Founder/Managing Partner, Volition Capital. Journaling general business thoughts so I don't forget them. Christian. Harvard. Several private/public boards.
Boston, MA volitioncapital.com/team/larry-che… Joined March 2009
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Larry Cheng Verified account @larryvc
As I've mentioned before, we've begun asking new employees at Volition, as part of their onboarding, to legally replicate a commercial software application in two weeks. Here are two key learnings from it - one of which is counterintuitive.

First, it's surprisingly easy. That's the feedback of those who have done it. Everyone has done it faster than two weeks.

Secondly, here's the counterintuitive one. One of the barriers to entry in SaaS is community. If you have a robust online community of users who are sharing best practices, being a help desk, teaching other users how to optimize the application - that can be a distinct advantage over other SaaS companies. However, it can also create a huge disadvantage.

The reason it can be a disadvantage in an AI world is that communities are creating content about the product. They are showing screenshots, they are doing video demos, they are describing features and use cases all in the public square.

All of that content is getting indexed by the LLMs therefore effectively becoming a free outsourced spec for the world. The more content in the public record on the application, the closer you are to a few prompts to replicate it.

Therefore, while it’s true that robust online community can make a SaaS company harder to displace, it’s also true that it makes the product easier to replicate. Balancing those competing realities will be key for SaaS companies going forward.
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Larry Cheng Verified account @larryvc
This is how things played out in the cloud computing era as well. The Fortune 500 CIOs were the most skeptical of cloud applications as well. As one CIO said to me, "No one will store their data on third party servers." History repeating itself...
Nick Mehta Verified account @nrmehta Oct 30
I've had dozens of conversations with CIOs of Global 2000 organizations in the last 3 months. One big learning: many CIOs are the most skeptical execs in their companies about AI.

Some of this comes down to risk - they view AI projects as being so bumpy and that the bumps will mean lumps for them.

Some of this comes down to knowledge - they know that their underlying systems, processes and data need to be rewired for agents to successfully operate.

Some of this comes down to signal - they are inundated with AI pitches and are tuning them out.

My takeaway: startups need to use more plain language - and ideally case studies - in their pitches. Drop the buzzwords - harnesses, models, memory, tools, self-improvement, evals. The AI lead in a customer will care about these.

The CIO cares about the actual specific outcomes you drive (much deeper than the obvious like "faster," "cheaper" and "better") and proof of these in the real world.
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Larry Cheng Verified account @larryvc
My guess is legacy brands will play this dynamic more conservatively and newer brands with less to lose will just go all-in on AI video advertising. The video ad unit that used to cost $10,000-$250,000 to make now costs $9. That will enable hyper-customized video advertising through human-first ad channels like broadcast TV, CTV, DOOH, etc. A national campaign will not be one ad unit distributed nationally but 4,000 custom video ad units targeting the 20,000 zip codes you care about. Expect CPMs to go up in the human channels - this is a boon to their business. Over time (and very quickly) the quality of video will be at parity and the objection will gradually dissipate.