AI executive brief: FACTS to DECISION—not yesterday's slide deck

Friday night: a PM builds the board deck—green charts, optimistic timeline, tiny risk footnote. Monday before the meeting, the CTO discovers CI pipelines are red and two epics are overdue without owners—but the slide deck already went out.

An AI executive brief earns trust when it comes from live data. In WKFGo, the MCP tool executive_brief accepts a role parameter (ceo, cfo, cto, coo, chro, cpo, ciso) and returns structured output: FACTS from tasks, git, and finance; DIAGNOSIS with ranked hypotheses; proposed DECISIONS—grounded in PostgreSQL, not PM narrative.

This is not a replacement for judgment. It is a replacement for assembling fiction from memory at midnight.

Symptoms and cost of broken executive briefs

Symptom Cost
CEO and CFO share one deck CFO wants numbers; CEO wants story—both get half-truths
Metrics without source "About 80% complete" with no definition of complete
Generic risk lists "Resource constraints" without task or project names
Post-meeting amnesia Nobody can cite the evidence behind a decision
Slides contradict /dashboard Stakeholders pick whichever number supports their position

Good briefs are decision-ready: evidence, tradeoffs, timing, owners. Bad briefs are morale theater—pretty charts that age poorly by Monday.

The hidden cost is strategic delay. When leadership spends the meeting reconciling numbers instead of choosing among options, the organization pays in slipped releases, unowned risks, and repeated debates about the same overdue epics.

executive_brief output structure in WKFGo

The executive_brief tool applies role-specific lenses:

Role Typical focus
CEO Portfolio synthesis, officer tensions
CFO finance_summary, burn, budget variance
CTO Git commits, CI/pipeline, quality signals
COO Delivery SLA, flow_aging
CHRO workload_heatmap, capacity
CPO Roadmap, epic progress
CISO Audit, identity signals

Output includes diagnosis (hypotheses with confidence), trend (did the last decision move its target metric?), and for CEO board.tensions where officers disagree and debate is required. Honest dataGaps appear when finance or git data is incomplete—partial truth beats confident invention.

Six-step weekly brief framework

Step 1: Pull raw brief one day ahead

In Claude or Cursor: executive_brief role=cto projectId=Atlas (repeat for CFO if needed). Store output in a wiki page titled "Brief 2026-W30" so the team shares one artifact.

Step 2: PM spot-checks FACTS

Verify three random facts in the web app: overdue count on /dashboard, pending approvals on /task-approvals, git pipeline status in Git integration. On mismatch, fix data—not slides.

Step 3: Human-edit the DECISION section

AI proposes three decisions—PM assigns real owners and timing. Log with record_decision for audit. Decisions without owners are wishes, not commitments.

Step 4: Pair every brief with decision_inbox

Every weekly brief should reference at least one open decision_inbox item—or explicitly state "no decisions required this week." Briefs without inbox action are information only; they do not change behavior.

Step 5: Run a 30-minute exception-only meeting

Agenda from the brief—not round-robin. Debate board.tensions for CEO lens. Use simulate_scenario when scope or release tradeoffs appear.

Step 6: Post-meeting accountability

Call resolve_decision_item for decided inbox items. Next week's trend shows whether metrics moved. This closes the loop between narrative and reality.

Anti-patterns

WKFGo leadership ecosystem

All permission-scoped via FeatureAccess—directors without finance access cannot pull confidential summaries. Personal wk_ keys attribute MCP calls per user.

Interpreting CEO board.tensions

When executive_brief role=ceo returns CFO vs CTO disagreement:

The CEO's job is to resolve—not average. Run simulate_scenario on each option. Call record_decision with rationale. Next week's trend calibrates whether the forecast was accurate. Structured debate beats political sidebar.

FAQ — AI executive brief

Does it replace a BI tool?
No—operational PM data from tasks, git, and finance, not a full data warehouse. Complementary to existing analytics.

How often should we run briefs?
Weekly for directors; daily exception scans via list_tasks and git for engineering leads; ad-hoc before release decisions via decision_inbox.

Can non-English executives use it?
Prompt in Persian or English; mixed FA/EN task data is fine—the summary language follows your prompt.

Is output 100% accurate?
No—spot-check FACTS in the web app. AI synthesizes; it does not oracle. dataGaps tell you where to dig manually.

Next step

Pull one executive_brief for your active project before next week's leadership sync. Spot-check three facts. Link it to the top decision_inbox item. That single cycle beats another hand-built deck.