Tenex: Paying AI engineers for outcomes, not hours
In brief
- Tenex pays AI engineers based on output, not hours, to align incentives with AI-driven efficiency.
- MetaHarness structures projects with AI agents, plans, and decisions versioned in Git.
- The firm supports 75 employees and Fortune 2000/PME clients in AI transformation, with a growing model.
Tenex, an applied AI partner for large enterprises, pays engineers based on delivered results rather than hours worked. According to cofounder Alex Lieberman, this model aligns incentives with AI-driven efficiency, preventing automation from reducing engineers’ earnings.
The company has built MetaHarness, a framework that structures projects around AI agents and shared documents, embedding plans, decisions, and code in a version-controlled system. CJ Hess, Director of Engineering, notes this approach makes agent and human work more legible, though warns it may be overkill for small teams. Tenex now employs 75 people and supports Fortune 2000 and mid-market firms in their AI transformation.
The model challenges how to value non-coding work like customer understanding or architectural design. It also questions the viability of vertical AI products as general-purpose models improve, while exploring alternatives like in-house software development despite maintenance costs.
What it changes for you
- Public SectorPublic administrations could adopt outcome-based compensation models for AI projects, reducing costs while improving efficiency.
- Industry & ManufacturingIndustrial companies could integrate AI agents into their SDLC to speed up development and reduce software maintenance costs.
This summary gives you the essentials. The full article, its figures and quotes are on Latent.Space.
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