Great post. The companies that are able to get their unique IP, institutional knowledge, and data into a format and architecture that lets them capture all of the gains and progress in AI are going to be in the best position in the future.
“the real opportunity is not in picking the best model but instead in building a learning loop on top of models where human capital and token capital compound. You can offload a task, or even a job, but you can never offload your learning. The future of the firm is the ability to compound that learning across people and AI.
This requires a new architectural approach where every business is able to build agentic systems that improve over time, while still retaining control over their IP. A company should be able to switch out a “generalist” model without losing the “company veteran” expertise built into their learning system.”
We’re all collectively figuring out the right architecture for the future of AI. But it’s clear that so much of the power and value will accrue to wherever can best leverage any AI system against their information. This is also why the applied AI layer will also gain so much value over the coming years.
@JaySahnan This will get solved if (cold) emails are gated behind paywalls
I.e. To reach someone's inbox you have to pay $ X - if that happens cold email outbound turns into just another supply / demand driven paid marketing channel.
Salesforce may never fall or will be one of the last to be affected but even those advantages will degrade over time.
F500 companies will likely still use Salesforce but more focussed alternatives will be built for niche(r) verticals.
This is a good thread that summarizes the landscape well imo: https://t.co/9iQzJsmni6
@alxfazio How granular are your feature spec files?
Have you thought of adding a splitter that takes a very large feature spec and breaks this down into smaller chunks?