How Ramp automated engineering with AI agents

Ramp runs AI agents across its entire engineering lifecycle: writing code, reviewing it, watching production, and root-causing incidents. Boris sat down with Austin Ray and Rahul Sengottuvelu of Ramp to talk about how they got there. Building for the models that are coming rather than the ones that exist, giving every engineer uncapped access to intelligence, and the guardrails that make it work. They compare notes on Claude Code setups, loops versus dynamic workflows, and what Claude Fable 5 unlocked. Claude Code: anthropic.com/product/claude-code Claude Cowork: anthropic.com/product/claude-cowork Office Hours LP: claude.com/office-hours Chapters 0:00 "Fix all our import cycles" 0:32 Stress-testing Fable on Ramp's Python modules 1:33 Fable and dynamic workflows cut CI time 66% 3:36 Loops vs. dynamic workflows for long-horizon tasks 5:15 Claude Code setups: vanilla vs. background-heavy 6:49 AI agents across the engineering lifecycle 7:23 Building for future models, not today's 9:11 AI agent guardrails and least privilege 12:00 Cost controls and AI code review 13:08 Ramp's culture of experimentation 13:52 Glass and Inspect: Ramp's AI coworkers 16:05 On-call assistant: an AI SRE on Claude Code 17:13 More agent sessions from automations than humans 18:44 No token budgets for engineers 20:48 Advice for CTOs adopting AI agents

Rahul SengottuveluguestBorishostAustin Rayguest

Aug 6, 202621mWatch on YouTube ↗

EPISODE INFO

Released: August 6, 2026
Duration: 21m
Channel: Claude
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

Ramp runs AI agents across its entire engineering lifecycle: writing code, reviewing it, watching production, and root-causing incidents. Boris sat down with Austin Ray and Rahul Sengottuvelu of Ramp to talk about how they got there. Building for the models that are coming rather than the ones that exist, giving every engineer uncapped access to intelligence, and the guardrails that make it work. They compare notes on Claude Code setups, loops versus dynamic workflows, and what Claude Fable 5 unlocked. Claude Code: anthropic.com/product/claude-code Claude Cowork: anthropic.com/product/claude-cowork Office Hours LP: claude.com/office-hours Chapters 0:00 "Fix all our import cycles" 0:32 Stress-testing Fable on Ramp's Python modules 1:33 Fable and dynamic workflows cut CI time 66% 3:36 Loops vs. dynamic workflows for long-horizon tasks 5:15 Claude Code setups: vanilla vs. background-heavy 6:49 AI agents across the engineering lifecycle 7:23 Building for future models, not today's 9:11 AI agent guardrails and least privilege 12:00 Cost controls and AI code review 13:08 Ramp's culture of experimentation 13:52 Glass and Inspect: Ramp's AI coworkers 16:05 On-call assistant: an AI SRE on Claude Code 17:13 More agent sessions from automations than humans 18:44 No token budgets for engineers 20:48 Advice for CTOs adopting AI agents

SPEAKERS

Rahul Sengottuvelu
guest
Engineering leader at Ramp focused on AI-agent infrastructure, CI/CD, and engineering productivity.
Boris
host
Host/interviewer from Claude who leads the discussion and closes by thanking the guests.
Austin Ray
guest
Engineering leader at Ramp describing internal AI-agent tools and a terminal-centric Claude Code workflow.

EPISODE SUMMARY

In this episode of Claude, featuring Rahul Sengottuvelu and Boris, How Ramp automated engineering with AI agents explores ramp scales engineering velocity using AI agents, workflows, and guardrails Ramp used the Fable model to tackle hard monolith problems (import cycles and lazy-loading) and to build empirically verifiable CI improvements through shadow testing and production data validation.

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