Why Agentic SaaS Forces Us to Rethink the Unit We Charge For
A look at where each of the three pricing models — per-seat, usage-based, and outcome-based — slips, and why the market ultimately drifts toward blending all three.
Dispatch-Style AI PMs as SaaS — How Big Tech's FDE Model Differs from ONTLE
Modeled on Palantir's FDE, Big Tech's dispatch-style AI efforts arrived one after another between May and July 2026. We break down where ONTLE fits among them, by type.
The 2026 AI PM & Automation SaaS Landscape — Competitive Analysis for the Agent Era
In 2026, when collaboration tools, AI execution tools, and automation platforms have all bolted on agents, the axis of competition is no longer whether you have an agent but where it lives and who assembles it. This piece places ONTLE's embedded-staff position honestly on that map.
Rules, Fixed LLM Workflows, and Agents — How to Pick Among the Three Levels of Automation
What to use for automation comes down to one question: can a human map out the flow in advance? Conditional logic calls for rules; text that needs understanding but follows a fixed path calls for an LLM workflow; and when the LLM has to decide its own steps and tools on the fly, you need an agent.
Where the Real Moat Lives in Agentic SaaS — It's the Accumulated Context, Not the Model
Once everyone can tap the same frontier model at the same price, the battleground for agentic work automation shifts away from model performance and toward wherever a customer's working context piles up.
Two Weeks Into Meta Muse — Where Is the Personal AI Agent Market Actually Headed?
The next battleground after chatbots is the agent that does the work for you. We dig into Meta Muse's early traction and turbulence, and trace where this market is converging.