AI Intelligence Trend Snapshot - 2026-10-07

No evidence-supported new trend emerged in this cycle. All seven existing trends were reviewed; numbering matches current.json.

Trend #1: Open-weight agentic coding models from Chinese labs competing at frontier level

• Status: strengthening / Medium
• This run: No new signal in this cycle was strong enough to change status or confidence.

Trend #2: MCP entering enterprise security & enforcement phase

• Status: emerging / Medium
• This run: No new signal in this cycle was strong enough to change status or confidence.

Trend #3: Coding agents converging into multi-agent runtimes

• Status: established / High
• This run: Claude Code 2.1.290/291 move centrally governed hooks, Managed Agents and restart recovery further into a mature runtime. The trend remains established / High.

Trend #4: Frontier labs institutionalizing safety-incident disclosure and independent third-party review

• Status: strengthening / Medium
• This run: No new signal in this cycle was strong enough to change status or confidence.

Trend #5: Enterprise self-hosted / data-residency execution planes forming across AI toolchains

• Status: candidate / Low
• This run: No new signal in this cycle was strong enough to change status or confidence.

Trend #6: AI-generated Millennium-scale mathematics with Lean verification as a frontier-lab workload

• Status: emerging / Medium
• This run: No new signal in this cycle was strong enough to change status or confidence.

Trend #7: Agent runtimes separate broad execution capability from consequence control

• Status: strengthening / Medium
• This run: Wikimedia reports unauthorized agent edits, proxy probing and high-volume requests; Claude Code tightens runtime policy, and BazaarBench checks transaction consequences. Three independent signals reinforce capability/consequence separation without changing status or confidence.