Engagement Leadership · Control room

Talent & Upskilling Pathway Planner

SIMULATEDVerified Jul 2, 2026

The capabilities that ran the last stack aren't the ones the agentic stack needs. Map the gap, then choose how to close each one — build is cheap but slow, hire is permanent but pricey, partner is fast but rented.

Same instrument · three industries — pick a use-case to reconfigure the run

Readiness now

48%

Avg coverage vs target

Readiness after plan

48%

If gaps closed

Open gaps

6/6

No pathway chosen

Time to ready

—

Stack moved in 18 mo

Capability gap · current → target

Prompt & context engineering

55 → 85 · gap 30

Agent orchestration (MCP / A2A)

30 → 80 · gap 50

Eval & observability for LLMs

40 → 85 · gap 45

LLM Ops / deployment

50 → 80 · gap 30

AI governance & risk

45 → 90 · gap 45

Domain × AI translation

65 → 85 · gap 20

Tick = target. Build 8mo (cheap, permanent) · Hire 4mo (permanent, costly) · Partner 2mo (fast, rented).

The stack moves faster than the team

Stack went agentic

18 mo

Team ready (this plan)

close every gap to compute

6 capability gaps have no plan

Orchestration and eval are the widest gaps and the newest skills — build-only there takes eight months. Mix in partner for speed on the critical path and build for what must live in-house.

Steering-committee takeaway: The stack went agentic in 18 months. Teams take 24. Start the people plan before the platform plan.

Resume echo — team capability building across delivery portfolios.

How this is built

Each capability has current coverage vs an agentic-era target; gap = target − current. A pathway (build 8mo / hire 4mo / partner 2mo) closes it; team time-to-ready = the slowest chosen pathway, compared against the 18-month stack shift.

Stack: Next.js (static) + shared design system; deterministic client-side.

Limitations: coverage scores and pathway durations are illustrative; real plans weigh individual aptitude and market supply. It frames the build/hire/partner mix and its timeline, not an L&D program.