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Mike Spitz

Conference affiliation: PFF · 2026

Mike Spitz is chief technology officer of Pro Football Focus (PFF), the sports-data company serving professional and college football teams and consumers. He is reshaping software delivery around a specific premise: when AI agents accelerate implementation, engineering organizations must optimize specifications, coordination, testing, and customer feedback instead of individual coding speed.

Spitz initially tested coding agents on low-risk projects before recruiting two experienced engineers for a three-month experiment inside PFF’s distributed engineering organization. Their agent-assisted team deployed more frequently than a larger conventional team, although Spitz acknowledges that smaller teams naturally move faster. His decisive measure was whether the resulting software improved customer satisfaction—not pull-request counts or code volume.

His account of PFF’s agent-first engineering experiment describes a post-engineer engineering organization that retains engineers while concentrating their judgment on architecture, security, product quality, and clearly defined requirements.

  • Optimize the organization for agent speed. Replace standups, sprint planning, and manual status updates with automated ticket coordination, short cross-functional huddles, rapid releases, and immediate production feedback.
  • Make design intent executable. Human-defined specifications become agent-generated lightweight design documents reflecting established engineering patterns; engineers review them before agents produce sequenced tickets and pull requests.
  • Encode engineering culture as composable skills. Capture team-specific conventions—including trunk-based development, feature flags, API architecture, analytics, and product presentation—so automated implementation preserves the organization’s standards.
  • Judge delivery by customer outcomes. Faster deployments matter only when customers receive better products; satisfaction surveys and production feedback provide stronger signals than code volume alone.
  • Automate verification before remediation. PFF’s acceptance-criteria-driven QA checks staging deployments against ticket requirements. Agent-generated fixes and self-healing workflows remain goals, not established capabilities.

Spitz advocates introducing these practices gradually: begin with senior engineers, repetitive work, low-risk systems, and reliable guardrails before expanding agent autonomy.

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PFF’s two-engineer pilot changed more than coding speed: it moved coordination into design documents, automated status updates and staging QA, while keeping humans responsible for intent and product quality.

  • What if the workflow optimized for agents?
    0:18 ↗
  • More deployments, then a harder question about output
    2:30 ↗
  • Finishing sooner releases capacity sooner
    3:40 ↗
  • Replace ceremonies with a shorter feedback loop
    4:53 ↗
  • Let work events carry the status
    6:51 ↗
  • Start with people who know where the system bends
    8:28 ↗
  • Automate verifiable work; preserve design judgment
    10:09 ↗
  • Compose the workflow, then test the result
    12:00 ↗
  • Make guardrails work before expanding autonomy
    14:09 ↗
  • Move urgently, at a pace engineers can sustain
    16:34 ↗

References