OpenClaw, Pi, and the 10,000x Gap

Feb 8, 2026

The real AI gap isn’t model quality — it’s extraction depth. Top builders can extract 10,000x value, while most teams only get 5x. That gap is where the biggest opportunities live.

1) Why people disagree so much about AI

The split in AI opinions often comes from one thing: how deeply someone can extract capability.

Some builders feel we are “3 steps from AGI.” Others feel we are “7 steps away.” That 4-step perception gap is not academic — it’s commercial.

We were too quick to say, “AI can’t do this,” when in many cases we simply hadn’t pushed hard enough.

2) In the AI era, there are three paths — with wildly different upside

Path 1: Use AI for efficiency (most conservative)

Improve existing workflows, reduce labor, speed up execution. Useful, but the upside is limited. Traditional companies are often strong here.

Path 2: Build with new AI tech itself (startups can have a 10x edge)

Large companies face real constraints: org silos, internal politics, and “must-use-our-own-model” mandates. Products like OpenClaw and YouMind — which connect across models instead of locking into one — show why startups can move faster.

Path 3: Build AI-native products (largest upside)

Not just “using a car to transport grain faster,” but creating a brand-new category. Look for products that cannot exist without AI.

This requires strong foresight, the kind seen in people like Bill Gates and Allen Zhang.

3) Learn from Peter Steinberger: how to unlock 10,000x

The performance gap is staggering:

The key is not longer prompts. It’s:

LLMs are still weak at repeated iterative patching. You get better outcomes with one-shot generation + smart process design.

Action plan

  1. Study how Peter actually works, in detail.
  2. Avoid “wandering exploration.” Pick a concrete goal and ship something real.
  3. Prioritize task-oriented products over taste-oriented products when trying to extract AI capability.