The Frontier

Theo Taba defines an AI native organization as one where people manage agents, those agents can read and write to company data, and the company gets smarter over time.

The core AI native system comprises people, agents, and context. The people manage agents who interface with a shared context layer, which gives agents a comprehensive view of the company's data and operations.

In an AI native workflow, AI handles the middle execution work, freeing humans to focus on the strategic beginning and critical review stages. Theo Taba argues everyone essentially becomes a manager of AI agents.

Theo Taba outlines a progression for agent autonomy: from basic chat use to requiring manual approvals, and finally to full autonomy. He stresses autonomous agents need clear goals, skills, tools, and rich context to succeed without constant oversight.

Skills are markdown files that define specific capabilities for agents, similar to uploading knowledge. Skill chains are sequences of skills executed in order to produce complex, high-quality outputs and reduce AI hallucinations.

Theo Taba demonstrates a proposal workflow where a skill chain automatically builds a branded microsite, refines the copy, and conducts quality assurance, generating a complete proposal in under five minutes from a trigger.

He states this automated proposal system has generated millions of dollars in revenue for LCA by enabling speed and deep personalization, giving them an edge over non-AI-native competitors in closing deals.

The 'context layer' or 'brain' is a structured repository of company data that gives agents perfect vision of the organization. It involves capturing data from tools like Slack and email, curating it, storing it in a searchable format, and leveraging it for execution.

Greg Isenberg highlights that this context allows proposals to incorporate personalized details from past conversations, like a client's analogy about record stores, which would otherwise be forgotten.

In a second demo, Theo Taba uses a voice command and a skill chain to build a functional Spotify feature prototype, complete with a usability test, in under ten minutes. The chain included building, testing, synthesizing feedback, and planning a V2.

Theo Taba advises bootstrapping context by leveraging public resources like Mobbin for design patterns and a company's public design system, then creating skills around them to produce high-quality outputs even without internal data.

He posits that building AI-native service firms for specific niches is one of the hottest startup markets. The strategy is to niche down by industry, function, and company size, master those workflows, and use the AI-native system to deliver speed and insight.

Greg Isenberg and Theo Taba reference Demis Hassabis's quote at Google I/O: 'Running 100 miles an hour in the wrong direction is worse than standing still,' linking it to the AI-native principle that speed must be directed by customer signal.