Operations | Monitoring | ITSM | DevOps | Cloud

Network operations teams have heard plenty about AI this year. Most of it answers the alert in front of it, then hands the rest of the incident back to an engineer. Someone still has to correlate the evidence, find the cause, prepare the fix, and prove it held. This week, we announced Selector Foundry, the agentic NetOps solution built into the Selector platform. Foundry adds a team of specialized AI agents on top of the full-stack observability and AIOps foundation our customers already run.

A roadmap for the Telecom, Media, Entertainment, and Gaming industries.

Somewhere in the last year, your team's code output went up. Pull requests are opened faster. The backlog of small fixes and routine changes started clearing quicker than it used to. If delivery still feels roughly as slow as it did before, that's what happens when you speed up one part of a process without touching anything downstream of it.

There’s a specific kind of measurement problem worth naming precisely rather than dramatizing: this month we found that our model-routing agent was assigning a token budget to every unit of work, and that budget was noise in the strict sense. Fixing it meant improving a system that’s mostly right, not tearing one down.

Enterprises are running AI agents nobody has counted, holding credentials nobody reviewed, taking actions nobody can audit. AgentIQ governs what agents are allowed to do at the moment of action—inside the execution flow—not after the fact through a gateway watching from outside.

TypeSafe AI released Jev in September 2026 to do one thing: make decisions. Give it a state (a string or a JSON object) plus a set of typed questions, and it returns typed answers with probabilities. It never explains itself, and that constraint is the whole idea. Evaluation pipelines have spent the last two years asking text generators for yes/no verdicts, wrapping the reply in a JSON schema, and paying generation prices for what amounts to a single bit.