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Scaling Inference-Time Compute with Teams of Agents for Software Engineering

Cohere Labs researcher Nouha Dziri opens ODSC AI West's virtual track with a keynote on using teams of agents to spend more inference-time compute on software-engineering tasks.

Open Data Science and AI Conference · 2026 featured video

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What this video shows

The first session in this ODSC stream is Nouha Dziri's keynote on teams of agents for software engineering. It asks whether a system can improve difficult engineering outcomes by assigning more work at inference time, rather than relying only on a larger model or one longer response.

Use the talk to form a testable design, then compare one agent, repeated samples and a coordinated team on the same task set. More agents can add search and critique, but they can also duplicate work, propagate errors and spend more tokens without improving accepted outcomes.

Read the official ODSC session description for the speaker, level and 25-minute session scope. Use Learnetto's AI agent test-set guide to compare agent configurations with stable cases and release thresholds.

What you will learn

  • Compare agent teams with repeated single-agent sampling, not only with one baseline run.
  • Count accepted task outcomes, elapsed time, tokens, tool calls and review effort.
  • Give agents distinct roles only when the task has separable work or useful independent checks.
  • Stop adding agents when coordination cost grows faster than accepted-task quality.

How to apply this safely

  1. Choose ten representative engineering tasks with known acceptance checks.
  2. Run one agent, repeated independent attempts and a coordinated team under the same tool and token limits.
  3. Record merge conflicts, duplicated work, incorrect consensus, elapsed time and human review.
  4. Keep the smallest configuration that meets the quality threshold, and preserve a fallback for tasks that need deeper search.

Important limitations

  • The YouTube item is a full conference stream, and this guide covers its first 25-minute keynote rather than every later session.
  • A conference presentation cannot establish that one agent topology works across repositories, models or tool environments.
  • Extra inference-time compute raises cost and latency, and coordinated agents can share the same mistaken assumption.
  • The official schedule describes the session, but teams still need task-level measurements from their own codebase.

Sources to check

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