PostCurrent Build Log 8/13: The new color scheme and post previews are live! Starting to feel like this is its own distinct brand https://t.co/7PmLJK82gX
With OpenAI dropping the price of o3 by 80%, today is a great reminder about how important it is to build for where AI is going instead of just what's possible now. You can now get 5X the amount of output today for the same price you were paying yesterday.
If you’re building AI Agents, it means it's far better to build capabilities that are priced and designed for the future instead of just economically reasonable today.
In general, we know there's a tight correlation between the amount of compute spent on a problem and the level of successful outcomes we can get from AI. This is especially true with AI Agents that potentially can burn through hundreds of thousands or millions of tokens on a single task.
You're always making trade-off decisions when building AI Agents around what level of accuracy or success you want and how much you want to spend: do you want to spend $0.10 for something to be 95% successful or $1 for something to be 99% successful? A 10X increase in cost for just a 4 pt improvement in results? At every price:success intersection a new set of use-cases from customers can be unlocked.
Normally when building technology that moves at a typical pace, you would primarily build features that are economically viable today (or with some slight efficiency gains anticipated at the rate of Moore's Law, for instance). You'd be out of business otherwise. But with the cost of AI inference dropping rapidly, the calculus completely changes. In a world where the cost of inference could drop by orders of magnitude in a year or two, it means the way we build software to anticipate these cost drops changes meaningfully.
Instead of either building in lots of hacks to reduce costs, or going after only the most economically feasible use-cases today, this instructs you to build the more ambitious AI Agent capabilities that would normally seem too cost prohibitive to go after. Huge implications for how we build AI Agents and the kind of problems to go after.
Every time you ask AI how to handle a complex human interaction you are allowing it to drive the direction of culture.
No easy answer means a chance to rewrite norms. With 1B+ users it's already happening. Make your own choices or we end up in a world run by Reddit consensus.
@paulg Assuming you have lots of ideas, how do you decide which ideas are worth pursuing? What you do with good ideas you don't have time or expertise to execute?