TurboPuffer achieved its massive cost savings by building on slow S3 storage. While this increased write latency by 1000x—unacceptable for transactional systems—it was a perfectly acceptable trade-off for search and AI workloads, which prioritize fast reads over fast writes.

According to Flexport's CEO, large incumbents hold significant AI advantages over startups. They possess vast proprietary data for model training, the domain expertise to target high-value problems (features, not companies), and instant distribution, allowing them to deploy AI solutions to thousands of customers overnight.

Legacy industries are often slow to adapt due to inertia and arrogance, creating massive opportunities. Flexport built a simple duty calculator in three days that the entire trade industry adopted, proving that a startup's key to success can be entering a field where competitors are technologically complacent.

Past tech solutions for fragmented industries like logistics often failed because they required universal adoption of a new platform. AI can succeed by meeting users in their existing, messy channels—email, texts, calls. It automates work within current workflows rather than forcing a difficult behavioral change, lowering adoption barriers.

AI labs like Anthropic find that mid-tier models can be trained with reinforcement learning to outperform their largest, most expensive models in just a few months, accelerating the pace of capability improvements.

The neural nets powering autonomous vehicles are highly generalizable, with 80-90% of the underlying software being directly applicable to other verticals like trucking. A company's long-term value lies in its scaled driving data and core AI competency, not its initial target market.

OpenAI's new GDPVal framework evaluates AI on real-world knowledge work. It found frontier models produce work rated equal to or better than human experts nearly 50% of the time, while being 100 times faster and cheaper. This provides a direct measure of impending economic transformation.

Flexport uses AI agents for tasks that were previously skipped because they were too costly for human employees, like calling warehouses to confirm addresses. This shows that AI's value isn't just in replacing existing work, but in performing new, marginally valuable tasks at a scale that is finally economical.

The initial impact of AI on jobs isn't total replacement. Instead, it automates the most arduous, "long haul" portions of the work, like long-distance truck driving. This frees human workers from the boring parts of their jobs to focus on higher-value, complex "last mile" tasks.