Session-start prompts cannot govern tool calls at dispatch. Buyers expect request-level policy enforcement on every irreversible agent step.
[4] NIST (2024). Generative AI Profile. Primary source ↗Evidence discipline
Every claim cited. Product metrics labeled.
Independent research on agentic AI governance — linked to primary sources. SourceA product specs (boot checks, replay time) are labeled separately from market hypothesis stats.
Why proof matters now
Board-level questions need receipts
Enterprises must define agent autonomy levels, decision boundaries, behavior monitoring, and audit mechanisms — formalized for development, deployment, and usage.
[2] McKinsey & Company (2025). Seizing the agentic AI advantage. Primary source ↗Governance must answer: Can we reconstruct agent decisions end-to-end? Do we have rollback when something goes wrong? — proof of control, not policy slides.
[3] McKinsey (2025). Trust in the age of agents. Primary source ↗Framework alignment maps
Educational mapping only
Alignment maps only · not certification · not legal advice
Reference list
- Gartner (2025). Gartner predicts over 40% of agentic AI projects will be canceled by end of 2027. Press release ↗
- McKinsey & Company (2025). Seizing the agentic AI advantage. Article ↗
- McKinsey (2025). Trust in the age of agents. Article ↗
- NIST (2024). Generative AI Profile. Profile ↗
- SourceA product spec.
sourcea-boot --jsonfour checks · live replay under five minutes · documented on proof chain.
Methodology for capability comparisons: COMPETITOR_SITES_UI_BENCHMARK_2026-06-15_v1.md (SourceA archive).
Go deeper
Every story. Its own chapter.
See it on your stack
Walk shadow mode → export bundle → tamper-FAIL — live on your screen.