Mezmo Mezmo engineers the context and orchestration foundation teams Spark insight with Mezmo.

Mezmo is the intelligence layer for production AI, pairing a production-grade control plane (AURA) with an optimized data plane (Mezmo) to make autonomous operations fast, efficient, and safe.

AI agents donโ€™t invent bad decisions out of nowhere.They inherit them.๐Ÿ”ธ Messy telemetry.๐Ÿ”ธ Missing ownership.๐Ÿ”ธ Stale runb...
05/26/2026

AI agents donโ€™t invent bad decisions out of nowhere.

They inherit them.

๐Ÿ”ธ Messy telemetry.
๐Ÿ”ธ Missing ownership.
๐Ÿ”ธ Stale runbooks.
๐Ÿ”ธ Broken context.

Then they package it up with confidence.

If your agents touch prod, this oneโ€™s for you.
๐Ÿ”—https://www.mezmo.com/blog/when-your-agents-hallucinate-at-2-am-it-is-not-a-model-problem

Context engineering is the deliberate design of telemetry, metadata, and feedback loops so AI agents reason accurately over production systems...

Your SRE agent does not need its 147th tool.It needs boundaries.Real incident response is not one job. It is investigati...
05/21/2026

Your SRE agent does not need its 147th tool.
It needs boundaries.

Real incident response is not one job. It is investigation, context retrieval, decision-making, documentation, and ex*****on. Stuffing all of that into one agent is how things get weird.

Why agentic SRE needs orchestration, not just more tools.

๐Ÿ”— https://www.mezmo.com/blog/why-sre-agents-need-orchestration-not-just-more-tools

AURA orchestration mode routes SRE workflows across scoped workers configured in TOML, reducing tool overload, context confusion, and single-agent...

The latest Gartner Analyst Take makes it clear: context engineering and decision intelligence are becoming foundational ...
05/19/2026

The latest Gartner Analyst Take makes it clear: context engineering and decision intelligence are becoming foundational to the success of agentic AI.

For SRE and platform teams, this lands especially hard.

An AI agent making recommendations during production incidents is only as reliable as the telemetry, metadata, and operational context it can reason over.

No amount of model tuning fixes fragmented knowledge of systems.

Our perspective on what the Gartner findings mean for production AI teams:

๐Ÿ”—

Context engineering is the deliberate design of telemetry, metadata, and feedback loops so AI agents reason accurately over production systems...

Production AI checklist:โœ– Dump every log into the context windowโœ– Hope for the bestโœ– Call it innovationActual production...
05/14/2026

Production AI checklist:

โœ– Dump every log into the context window
โœ– Hope for the best
โœ– Call it innovation

Actual production AI runs on context engineering, memory, governance, and earned autonomy.

More than vibes.
๐Ÿ”—

56% of teams have zero agents in production. The five steps that move SREs and platform engineers from agent demo to autonomous ops, with notes on...

Missed the webinar? We got you.Getting an AI agent running is easy. Keeping it reliable in production is the hard part.W...
05/08/2026

Missed the webinar? We got you.

Getting an AI agent running is easy. Keeping it reliable in production is the hard part.

Watch Andre Elizondo break down how teams are moving from AI experiments to trusted, production-ready workflows with AURA.

Open source. Better context. Less chaos.

Watch now โ†’

Most teams are experimenting with AI agents. Few are running them reliably in production. This session breaks down how to move from first agent to trusted, repeatable workflows with real telemetry, strong context, and control over cost, accuracy, and scale.

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