← Ben Lai

90-second evaluator dossier

Hire Ben Lai

A proof-first page for people deciding whether the work is relevant. Start with availability, then check the receipts and the cited answers.

Fit

Problems worth calling about

Receipts

Evidence before adjectives

Questions

Five answers with citations

Has he shipped production software?

Yes. The current public receipts include live products for agent registry, agent payment controls, agent games, travel writing, and AI education. The strongest evidence is the live-product set rather than a private repository tour.

What is the clearest technical through-line?

Auditability for AI systems: stable identity, policy gates before action, signed receipts after action, and replayable workflows. That shows up as products, not just essays.

Can he explain engineering tradeoffs clearly?

The writing is mostly short operational essays: cost ownership, agent deployment boundaries, MCP as production dependency, and the habit of proving work through logs, receipts, and boring defaults.

Is there public code to inspect?

Some, but not all. Several product repositories are private. Public code receipts include Learn AI, a small DeepSeek compatibility proxy, and other public GitHub work; use the live products as the broader shipped-work evidence.

What should I not infer from this page?

Do not infer team size, revenue, or customer adoption unless a receipt says it. This page is deliberately evidence-first: when public proof is thin, it says so rather than filling the gap with adjectives.

Next step

Ask for the missing proof

If a claim matters and the public receipt is thin, ask directly. The right answer may be a private walkthrough, a repo screen share, or "no public evidence yet."