SPEAR — Management Framework for Agent Runs

Source: Ryan Waliany, Introducing SPEAR: The Management Framework for AI (May 2026). One-line summary: Standard PM phases (initiate, plan, execute, monitor, close) compressed for the software factory. Core insight: The strong-start-weak-finish problem is a process problem, not a model problem. Skipping Plan or Assess is what makes agents feel unreliable.

When to load this skill

Load BEFORE starting any task that has more than one acceptable answer or that the user will visibly inspect when you're done. That covers:

• Bug fixes that touch shared code (auth, runtime, tool registry)
• Any feature with user-visible behavior
• Anything where "looks good to me" is not a sufficient acceptance test
• Multi-step refactors, migrations, multi-platform launches
• Customer-facing artifacts (reports, landing pages, ad creatives, support replies)

Do NOT load this skill for: typo fixes, single-line config changes, pure reads, simple lookups.

The five phases (gates, not checkboxes)

╭───────╮   ╭──────╮   ╭─────────╮   ╭────────╮   ╭─────────╮
│ Scope │──▶│ Plan │──▶│ Execute │──▶│ Assess │──▶│ Resolve │
╰───────╯   ╰──┬───╯   ╰─────────╯   ╰───┬────╯   ╰─────────╯
               ▲                          │
               │       gap found          │
               ╰──────────────────────────╯
                  (narrow Plan to the gap,
                  rerun Execute + Assess)

The inner loop is Plan → Execute → Assess. If Assess fails, narrow Plan to the gap (do not re-plan the whole task) and re-run Execute + Assess. Repeat until the rubric holds.

Designing the Assess rubric (the hardest part)

A rubric works when it is MECE:

• Mutually exclusive — items don't overlap. A failure on one item must be independent of every other. Overlap creates drift (you'll fix one and break another, then declare victory on a regression).
• Collectively exhaustive — items cover every dimension that has to pass. Gaps create false positives ("looks good" with a silent missing dimension).

Each item is scored 1–10. Only 10/10 is a pass. Anything else = the inner loop runs again, with the next round's rubric stricter than the last.

How to author the rubric

1. Write the rubric BEFORE Execute, not after. Otherwise you grade what you produced, not what you needed.
2. Aim for 4–8 items. Fewer is usually wrong (too coarse). More is usually wrong (overlapping items).
3. Each item is a single observable fact: "X is true" / "X is present" / "X matches Y". Never aesthetics ("looks clean").
4. Ask "if I score this 10/10 and the user still complains, which item should have caught it?" — that's a missing item.
5. Ask "if both item A and item B fail together, is one of them the actual cause of the other?" — if yes, merge them or remove one.
6. For agent code changes the rubric almost always includes: behavior change verified by test, no regression in adjacent surfaces, types/build pass, observability added, no secret/PII leak, docs updated where contract changed.

Worked example — applying SPEAR to a code task

See examples/agent-bug-fix.md for a full SPEAR run on a representative agent bug (multi-surface default mismatch), including the MECE rubric, two inner-loop iterations, and Resolve.

Anti-patterns that defeat SPEAR

Time budgets

Same five phases, only the clock changes:

If Assess keeps failing, the right move is almost always shrink the scope (move items to follow-up PRs), not loosen the rubric.

How to combine with spec-driven-dev and code-review

Order: spec-driven-dev (set up the spec) → spear (do the work) → code-review (independent assess from the reviewer angle).

Output discipline

When applying SPEAR in a user-visible thread, surface only the gates that just changed, not every intermediate thought. Format:

**Scope:** <1 line>
**Rubric:** <4–8 bullets, observable items>
**Plan:** <numbered steps>
**Execute:** <what you did or the diff link>
**Assess:** <scored rubric table>
**Resolve:** <summary + next action>

Skip phases the user already approved. Show the rubric table fully on each Assess round so the user can spot a regression.

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