How Kernel keeps shipping fast with Firetiger
Mason and Sayan, founding engineers at Kernel, talk about what changed when Kernel turned on Firetiger Change Monitors across their pull request workflow.
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How Voxel engineers keep safety systems in check with Firetiger
Jorge Villatoro is a principal engineer at Voxel, an industrial workspace safety and analytics company.
Jorge and I have known each other for over a decade, he's one of the engineers I trust most when it comes to infrastructure and reliability. So I was delighted to learn about
Agentically optimizing LLM prompt cache TTLs for fun and profit
A case study on production objective hill climbing
Firetiger runs a few hundred large language model (LLM) agents in production, and prompt caching is a critical tool to manage the cost of running such a workload. Properly setting cache time-to-live (TTL), how long a cached prefix survives before the next
How Town keeps AI assistants running with Firetiger
George Kontridze, founding engineer at Town, works across infrastructure and developer productivity.
I sat down with him to talk about what changed when his team plugged Firetiger into their deploy pipeline.
Kill the Session. Earn the Memory.
The Problem With Long-Running Agents
Firetiger has many agents with long task horizons (persistent goals which evolve over months). Some are user-defined: “I want my api service to get healthier…” or “I want to ensure our agent output doesn’t degrade…” Agents monitor the system, propose changes, see what happens,
Firetiger Change Monitors: does your PR do what it says on the tin?
Today, we're making Change Monitors generally available for all Firetiger customers.
Firetiger Change Monitors pair with every pull request to form a per-change safety net: an agent reads your diff, studies the systems it touches and how they behave in prod, and drafts a targeted post-deploy monitoring plan
Object store as a primitive for Agent runtime
In this article, we are presenting how Firetiger uses S3 and Lambda as the core primitives for the development of long-horizon agents.
Our agents run 24/7, tirelessly helping software engineer with production operations, from monitoring deployments to joining the incident response team when problems unexpectedly hit.
I've
Agent SLOs: Grounding autonomous agents in metrics that matter
Today we're shipping Agent SLOs, a new feature that gives every Firetiger agent a structured way to track the health of the missions it's assigned. Agents now define their own service level objectives (SLOs), evaluate them every session, and use those evaluations to triage the issues
Claude Code, meet the Firetiger plugin! Giving Claude Code super powers in prod
Firetiger makes software in production should be self-operating and self-improving. Our agents understand your observability data, codebase, and the outcomes you care about, and make sure they come true. Think of our agents as little tooth fairies that keep the "bad news" monsters away and leave treats under
Agent Engineering Patterns: Dealing with very large tool results
Agents are models with tools in a loop. Your first job then, when building an agent, is to give them useful tools. But wasting tokens on unimportant information is catastrophic for agent brains, so you need to be careful and protect your agents from tools that can blast out 40,