HeyJaredWarp
The open platform for automating development. Infrastructure to build, measure, and interact with agents across the SDLC warp.dev/factories
- Indexed videos, last 90 days
- 16
- Latest publication
- Sep 28, 2026
- Audience
- ~113K subscribers
- Earliest in this view
- Jul 7, 2026
Latest videos
Warp Factories - the complete guide (opens the original)
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A complete tour of Warp Factories, infrastructure to build your own AI software factory. I'll show how to set up agents and automations, launch work from Slack, then use spending dashboards, scoring, self-improvement, and benchmarks to improve results. 0:00 Overview 0:55 Create your first factory 3:22 Manage agent orchestration 4:42 Connect agents to automations 6:25 Set up integrations, MCPs, and secrets 8:09 Start a factory run from Slack 10:48 View the metrics dashboard 13:18 Using scoring ag
You should have an agent that grades your agents (opens the original)
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Try Warp Factories: warp.dev/factories/request-access Let's measure the quality of coding agents (Claude Code, Codex, etc) with scoring agents. These use LLM-as-a-judge to measure output quality along metrics you care about, like code quality, efficiency, verbosity, and task compliance. These feed self-improvement and benchmarking workflows to improve your software factory automatically.
The secret to cheaper, smarter coding agents (opens the original)
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With Warp Factories Benchmarking it’s now possible to build custom coding agent benchmarks (Claude, Codex, Grok, Kimi, etc) on your team’s real data and workflows with a few clicks. This is a deep dive of Factory Benchmarks: how to read the report, pick the right models, and build custom routers to reduce cost-per-PR.
How to build a model bench on your own coding tasks (opens the original)
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Factory Benchmarks are the model bench generated from your own agent coding tasks. They help you measure, test and improve coding agents by replaying past agent runs. We used these benchmarks to cut our cost-per-PR by 63% Get early access: warp.dev/factories/request-access
Your agent skills should improve themselves (opens the original)
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What if coding agents (Claude Code, Codex, Warp, etc) could improve Skills by reviewing past conversations? Here's the three step loop: - Score conversations from criteria you define - Isolate failures - Generate skill improvements 0:00 Why agents need self-improvement loops 0:25 Three-step scoring system 1:12 Configuring a code quality scorer 2:14 Self-improvement agents 3:13 Closing the loop
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~113K subscribers
Measured Sep 19, 2026
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