Tired of copilots that only autocomplete? In the two weeks from 2024‐12‐22 to 2025‐01‐04 the market moved: GitHub Copilot Workspace (public preview, rolling since 2024‐12‐17) and Sourcegraph Cody 1.0 pushed agentic, repo‐scale edits and plan‐execute‐verify loops; Qualcomm, Apple, and mobile LLaMA work targeted sub‐10B on‐device latency; IBM, Quantinuum, and PsiQuantum updated roadmaps toward logical qubits (late‐December updates); DeepMind’s AlphaFold 3 tooling and OpenFold patched production workflows; Epic/Nuance DAX Copilot and Mayo Clinic posted deployments reducing documentation time; exchanges and FINRA updated AI surveillance work; LangSmith, Arize Phoenix and APM vendors expanded LLM observability; and hiring data flagged platform‐engineering demand. Why it matters: AI is being embedded into operations, so expect impacts on code review, test coverage, privacy architecture, auditability, and staffing. Immediate takeaway: prioritize observability, audit logs, on‐device‐first designs, and platform engineering around AI services.

Drowning in pilot projects and vendor demos? Over late 2024–Jan 2025, major vendors moved from single “copilots” to production-ready, orchestrated AI in enterprise stacks—and here’s what you’ll get: Microsoft and Google updated agent docs and samples to favor multi-step workflows, function/tool calling, and enterprise guardrails; Qualcomm and Arm pushed concrete silicon, SDKs and drivers (Snapdragon X Elite targeting NPUs above 40 TOPS INT8) to run models on-device; DeepMind’s AlphaFold 3 and open protein models integrated into drug‐discovery pipelines; Epic/Microsoft and Google Health rolled generative documentation pilots into EHRs with time savings; Nasdaq and vendors deployed LLMs for surveillance and research; GitHub/GitLab embedded AI into SDLC; IBM and Microsoft focused quantum roadmaps on logical qubits. Bottom line: the leverage is systems and workflow design—build safe tools, observability, and platform controls, not just pick models.