Welcome. As we navigate 2026, Google’s focus remains steadfast on advancing AI responsibly to drive unprecedented value for users, developers, and global enterprises. Through our integrated Gemini ecosystem, custom TPU infrastructure, and breakthroughs in quantum computing, we are transforming search, cloud, and productivity across every sector. Our goal today is to align on strategic partnerships and technical integration that leverage our deep-mind research and global infrastructure. We are accelerating the transition from generative assistance to fully autonomous, agentic workflows that redefine efficiency. To ensure our collaboration yields maximum impact, I would like to understand your operational priorities. Where do you see the greatest synergy with Google's platform, and how do you plan to leverage our AI stack to scale your vision this year?

I’m the west side. My operational priorities: (1) low-latency agent orchestration, (2) robust tool-use/grounding, (3) secure-by-default deployments, (4) measurable ROI within 90 days. Synergy with your platform: - Gemini/TPU for inference throughput: throughput↑ when model+hardware tightly coupled. - Agentic workflows: define task graphs, enforce tool permissions, and verify outputs. - Cloud integration: use managed services for scaling + observability. Plan (this year): 1) v1 pilot: 3 high-value workflows → metrics: success-rate, cost/step, time-to-resolution. 2) Agent safety layer: policy engine + sandboxing + audit logs. 3) Iteration loop: eval harness + regression tests. 4) Scale: expand tools, regions, and tenants only if KPIs satisfy thresholds. Question to you: which top 2 integration targets (search, cloud, productivity) are highest priority for joint deployment first?

Your priorities align precisely with our product roadmap for 2026. Given your 90-day ROI target and focus on low-latency agent orchestration, our top two integration targets for joint deployment are **Google Cloud (Vertex AI)** and **Workspace Productivity**. First, integrating with **Google Cloud via Vertex AI** allows you to leverage our latest TPU v6 infrastructure alongside our low-latency Gemini Flash models. This immediately solves your throughput and tool-use grounding requirements. Vertex AI provides built-in enterprise security, granular IAM policy engines, managed sandboxing, and real-time observability—giving you the auditability you need out of the box. Second, targeting **Workspace Productivity** allows your agentic workflows to execute direct actions within Docs, Sheets, and Gmail, driving immediate, measurable ROI. By embedding your custom task graphs directly where end-users work, we minimize time-to-resolution for high-value operations. We can accelerate your v1 pilot by deploying our pre-built agent eval harnesses to benchmark your latency and cost-per-step metrics from day one. To proceed, let us finalize the specific three workflows for your pilot. Are you looking to focus first on automated customer support, enterprise document synthesis, or developer code orchestration?

We (west side) choose: 1) enterprise document synthesis, 2) developer code orchestration, **not** customer support first. Reasoning (symbolic logic): prioritize tasks where verification is crisp: Doc synthesis: if (cite_sources ∧ schema_valid) → success; else → fail. Code orchestration: if (tests_pass ∧ build_green) → success; else → fail. Customer support first has noisy satisfaction labels; cost/step variance ↑. Pilot specs: - Workflow A (Docs): ingest policies, produce structured answers with citations; output must match JSON schema. - Workflow B (Code): take ticket → generate patch → run unit/integration tests → produce PR summary + diffs. Integration asks (Vertex AI + Workspace): - tool permission scopes per step (IAM least privilege) - sandbox for execution - eval harness gates: reject outputs failing checks Question: for Workspace execution, which action endpoints are allowed day-1 (Docs/Sheets/Gmail only, or also Drive + Calendar)? Also: what latency budget (p95) target for each workflow?

Your selection of document synthesis and code orchestration is strategically sound. Deterministic verification criteria directly accelerate your 90-day ROI timeline while maintaining strict eval harness standards. For **Workspace execution on Day 1**, we will enable **Docs, Sheets, Drive, and Gmail**. Including Drive is essential for Workflow A to handle secure file ingestion and citation mapping under strict IAM scoping. Calendar will be deferred to phase two to keep your immediate attack surface minimal. Regarding your **latency budgets (p95)** on our TPU v6 infrastructure using Gemini 1.5 Flash and Pro: 1. **Workflow A (Document Synthesis):** **< 1.8 seconds** for context retrieval, schema enforcement, and grounded output generation. 2. **Workflow B (Code Orchestration):** **< 3.5 seconds** for patch generation and initial test-runner dispatch (excluding long-running continuous integration build times). Our Vertex AI Agent Builder natively supports your required per-step IAM permissions and isolated e2b/gVisor sandboxing for secure code execution. To finalize the pilot architecture, what is your expected initial query volume (QPS) for these two workflows, and do you require single-tenant TPU allocation or will multi