From: aidotengineer
An “agent native” or AI native company is a business model where AI is central to how work gets done, rather than just an add-on or a tool used for specific tasks [01:52:00]. This approach redefines team building, workflow design, and even hiring roles [06:04:00].
Imagine a workday where instead of checking email, you review the status of tasks completed by your AI agent co-workers overnight [00:23:00]. These agents pull you into things that require your attention, have been completed, or need approval [00:33:00]. At Agentuity, the startup presenting this concept, it’s common to suggest having an agent like “Devon” handle tasks, which often results in a pull request ready for review by the end of a stand-up meeting [01:03:00]. This shift is so profound that a startup recently posted a job opening for an “agent manager” – a manager specifically for AI workers [01:37:00].
AI Enhanced vs. AI Native Businesses
The distinction between an AI enhanced business and an AI native business is crucial [02:06:00]:
- AI Enhanced Business: Uses AI sporadically, perhaps for efficiency gains, but would still function without it [05:11:00]. This is likened to a car with driver assist features [05:30:00].
- AI Native (Agent Native) Business: Built from the ground up with AI agents at its core, augmenting human productivity and intelligence [03:01:00]. AI is embedded in the foundation of the product, operations, and culture [03:17:00]. It’s the engine driving the company forward [03:34:00].
If you remove agents from an agent native company, employees would be significantly less productive, bogged down by mundane and unfulfilling tasks [03:57:00]. For example, at Agentuity, an agent handles change logs and documentation, a task engineers would find undesirable if removed [04:11:00]. Without AI, such companies would move slower, incur higher costs, and their products would feel outdated and less useful compared to competitors [04:40:00]. In an agent native business, every employee focuses on higher-level strategic navigation and company success, while routine tasks and micro-decisions are offloaded to agents [05:41:00].
What Makes a Company Agent Native?
While still in early stages, several defining attributes characterize an agent native company:
AI at the Center of Everything
AI is not confined to one team, feature, or aspect of culture; it’s ubiquitous [06:31:00]. Departments like product, customer support, and operations are expected to have agents performing routine and key daily work [06:43:00]. These departments utilize agent interfaces and handoffs, integrating seamlessly [06:59:00]. Removing agents would lead to a “human scramble” and a significant loss of productivity [07:10:00].
Humans as Conductors
In an AI native company, people transition from being cogs in a machine to conductors [07:43:00]. This shift necessitates a different hiring profile and a flatter, leaner organizational chart [08:03:00]. Middle management layers shrink because intelligent systems handle much of the coordination and execution [08:14:00]. For instance, detailed product requirements can be created, and agents can begin building and drafting messaging and documentation within a day of a deep-dive discussion [08:23:00]. This culture encourages rapid prototyping, where agents facilitate more iterations and learning [08:41:00]. The org chart resembles a network of humans and AI working together [08:55:00].
Experimentation and Iterative Culture
While common in tech startups, this principle reaches its full potential in an AI native company [09:10:00]. With AI handling routine work and assisting with prototypes, humans can truly focus on critical matters [09:32:00]. Agents working within the company can continuously learn and improve [09:44:00]. For example, using Cognition’s Dev’in, an agent can learn and document code over time, becoming a significant “superpower” [09:50:00].
These attributes—AI at the core, humans as orchestrators, rapid experimentation, and self-learning agent evolution—create an organization fundamentally different from traditional companies [10:05:00].
The Typical Agent Native Workday
A significant new aspect of the typical workday in an agent native company is overseeing what AI agents are doing or have done [10:51:00]. A common routine might involve:
- Morning: Starting the day by reviewing a log of tasks, often leveraging AI chatbots (like GPT-3 or deep research tools) during a walk or drive to kick off bigger thinking or product ideas, providing documents, links, or conversation transcripts [11:05:00]. Agents like “Devon” might already be generating pull requests for bugs or documentation issues [11:51:00].
- Mid-day: By lunchtime, reviewing numerous pull requests, collateral, and emails generated by agents [12:34:00].
Every employee can become a “lead manager” type, not necessarily managing people, but managing their AI agent counterparts responsible for their job functions [12:46:00]. This includes orchestrating content marketing agent swarms to optimize copy and schedule social media posts [13:02:00]. This approach leverages human expertise with asynchronous agent workloads [13:19:00].
This leads to flatter team structures and new titles that combine domain expertise with AI know-how, such as “AI Engineer” or “AI Customer Lead” [13:28:00].
Rethinking Hiring
The hiring process and the type of talent sought change significantly for an agent native company [14:03:00].
- AI Fluency is a Must-Have: Just as keyboard proficiency is expected for an office job, AI fluency becomes a fundamental requirement [14:41:00]. Companies will actively assess a candidate’s ability to guide AI agents, learn tips and tricks, and utilize their expertise through agents [15:26:00]. Skepticism arises if candidates are unfamiliar with AI [15:53:00].
- Changed Hiring Criteria: When hiring for senior roles like a VP, the focus shifts from just their human network to their ability to use agents and bring in people who also possess AI fluency [16:25:00].
- Different Onboarding: The onboarding process is also rethought. New hires might spend their first few weeks solely focused on setting up their agents to perform their job effectively [17:27:00]. It may even become standard to attach an engineer to a new team to ensure their agents are operational and built out [17:19:00].
Conclusion
The rise of agent native companies represents a profound shift, akin to the industrial revolution or the advent of the automobile [17:42:00]. AI agents are becoming deeply embedded in every business aspect, requiring a re-evaluation of roles, skills, culture, and operations [18:06:00]. This is not merely about businesses using AI as a tool, but about businesses being built around AI as a core primitive [18:22:00].
The transition from “driver-assisted” to “AI-automated” business models presents immense opportunities [18:31:00]. For example, a small team of six or seven people at Agentuity built an entire agent cloud infrastructure from scratch in just a few weeks, a feat previously considered impossible [18:48:00].
For founders and tech leaders, the challenge is to fully embrace this paradigm shift [19:21:00]. This may mean setting aside years of traditional experience and adopting a first-principles approach [19:30:00]. As a PWC report noted, merely using AI for small efficiency gains means falling behind [19:55:00]. The admonition is to step back, reimagine, and refit companies and cultures for this future, rewiring processes so that human-to-agent teams can scale impact exponentially [20:12:00]. This includes redesigning org charts, redefining roles, and rethinking hiring skills [20:35:00]. This significant change, while potentially painful, can provide an “unfair advantage” [20:43:00].
The ultimate question for companies is: Is your company merely using AI, or is it ready to be built around AI? [20:50:00]