Rick Pollick
Valuestream

Episode 5 — Live

Valuestream.

Where value actually flows.

A podcast from Rick Pollick on how modern companies turn strategy into shipped software — the operating systems, delivery practices, and agentic-AI patterns moving value from the roadmap to production. New episodes Monthly.

Valuestream Podcast — Episode 5 cover artEpisode 5

Episode 5 · 22 min

Context Is the Job

Why Reliable AI Agents Are a Context Problem, Not a Prompt Problem

August 31, 2026

Reliable AI agents fail on context, not prompts: what the model can actually see when it acts. A 2026 survey traced 57% of enterprise agent reliability failures to missing or inconsistent context, not the model. This episode walks the context budget, the four failure modes, and how to run context as a delivery discipline, with version control, evals, ownership, and observability.

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The format

Three segments. One coherent show.

Every episode follows the same spine — so guests, teardowns, and solo pieces all feel like one show, and you always know what's next.

  • Segment

    Intake

    The problem or opportunity entering the stream — framing, signal, strategic intent.

  • Segment

    Flow

    How the work actually moves — operating model, platform, delivery practice, the agentic layer.

  • Segment

    Outcome

    What changed — shipped software, org behaviour, customer metrics, what we'd do differently.

Episode 5 — segment by segment

  • Intake. Prompt engineering was the tutorial; context engineering is the job. A 2026 survey traced 57% of enterprise agent reliability failures to missing or inconsistent context, not the model. The fix is a delivery discipline: govern what the agent can see.
  • Flow. The context budget (attention degrades before the window fills), the four failure modes (retrieval, tool-output flooding, memory that never forgets, history that never compacts), and the operating model: version control, evals, and observability, with a named owner.
  • Outcome. A support agent that was confidently wrong 22% of the time drops to about 4% on the same model, by fixing what it could see: context cut from about 38k tokens to 12k, retrieval quality from 60% into the low 90s, and mean time to understand incidents measured in minutes.

Earlier episodes

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Valuestream Podcast — Where value actually flows — Rick Pollick