Enterprise AI race boils down to two plays:
$PLTR → Army of Forward Deployed Engineers building custom systems. You own your IP, full stack control. Sticky AF once deployed. Trade-off? Rigid, slow to scale.
OpenAI/Anthropic → Lean on god-tier models, bottom-up adoption through internal champions. Fast deployment, less hand-holding. Trade-off? Your data trains their models. IP risk is real.
It's the classic build vs buy. Palantir = full control, high switching costs. OpenAI = speed, flexibility, but you're renting intelligence.
Which model wins long-term? Depends if enterprises value sovereignty over speed.
$PLTR → Army of Forward Deployed Engineers building custom systems. You own your IP, full stack control. Sticky AF once deployed. Trade-off? Rigid, slow to scale.
OpenAI/Anthropic → Lean on god-tier models, bottom-up adoption through internal champions. Fast deployment, less hand-holding. Trade-off? Your data trains their models. IP risk is real.
It's the classic build vs buy. Palantir = full control, high switching costs. OpenAI = speed, flexibility, but you're renting intelligence.
Which model wins long-term? Depends if enterprises value sovereignty over speed.