Speed & Parallel Processing
Making agents fast enough for production
TL;DR
Making agents fast enough for production
> Overview
Agents can run multiple tasks simultaneously: researching, analyzing, and drafting at the same time instead of sequentially. This dramatically reduces wait times. But each parallel branch costs money, so you are trading dollars for speed. This module teaches PMs how to identify parallelizable tasks, calculate cost-speed trade-offs, and design UX for progressive results.
> Why This Matters for Your Product
User patience is measured in seconds. A sequential 5-step agent taking 25 seconds will lose users. Running 3 of those steps in parallel might cut total time to 12 seconds. But 3 parallel branches mean 3x the API cost for that portion. The PM must define the right balance for each use case.
> Interactive & tools
Progressive results demo
Progressive results: cards appear as each step completes
Compare: all 5 at once after 10s vs. one every ~2s. The second feels faster.
Related Engineering Patterns
These are the technical patterns your engineering team will implement. Understanding them helps you have better conversations.
Key Product Decisions
- [01]What is the maximum acceptable response time for your use case?
- [02]Which tasks are independent and can run simultaneously?
- [03]Is the cost of parallel execution justified by the UX improvement?
- [04]Should you show a progress indicator or stream partial results?
Ask Your Engineering Team
- →What is our current end-to-end latency and where are the bottlenecks?
- →Which steps can we safely parallelize without dependency issues?
- →What is the cost impact of running N branches in parallel?
- →Can we implement progressive streaming to show results as they arrive?
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