OCTO Idea Hubs
OCTO IDEA HUBS: A FAST-CYCLE INNOVATION PROGRAM
Section titled “OCTO IDEA HUBS: A FAST-CYCLE INNOVATION PROGRAM”Sponsor: OCTO
Goal: We have privileged access to OpenAI IP and a growing tool ecosystem; what we lack is dedicated capacity and tight, unencumbered feedback loops. We’re launching a program to generate high-quality, de-risked AI concepts and technical insights shaped by, but not limited to, OpenAI capabilities, and to give the company clear visibility into new technology and ideas for product groups to incubate and ship.
The ‘why’: Current AI capability is advancing faster than our typical software cycles can absorb. One-week hackathons create demos but little durable learning and product-roadmap work is not optimized for disruptive discovery. We need a standing, disciplined ‘play’ environment unconstrained by specific tech stacks or product backlogs where small, mixed teams can run short, high-evidence experiments, connect directly to OpenAI IP insights and ecosystem innovation, feeding back into Microsoft’s product engine. [DT1]
The ‘what’: Idea Hubs, powered by Project Coeus, convert privileged OpenAI access into short, evidence-heavy experiments in OCTO’s shared environment anchored by a core set of forward-thinking builders connected across the company. Coeus centralizes OpenAI assets behind a single agent that issues role-specific “what changed and why” briefs. The Idea Hubs, comprised of 4–6 ring-fenced teams (5–7 builders), run three-week cycles on OCTO shared infrastructure (tokens/compute, data, eval harnesses, and starter agents). In parallel, the refreshed AI Models & Ideas meeting serves as the SLT operating review for Idea Hub led demos, technical insights, and a concise Coeus update. A company-wide Knowledge Community links Coeus insights, OpenAI Embedded Engineers, Idea Hub experiments, and a standing MAIDAP OCTO ‘capstone’ rotation; together these assets serve to build a durable talent pipeline and uplevel the frontier capability knowledge across the company so discoveries and forward-looking capabilities propagate quickly (Figure 1). Finally, each quarter, a lightweight ‘Final Four’ showcase highlights the most instructive demos against a published rubric (impact, technical leverage, feasibility, evidence, strategic fit) offers SLT sponsored Ignite/Build and other thought-leadership demo slots.
The ‘how’: Each Idea Hub project team will be assigned to a named v-team (AOAI, Engineering Copilot, Weizhu’s team for the orange tenant, plus EE/DT) with clear SLAs for API readiness, data access, and eval support. Teams run parity checks across infra, tooling, and research→inference→product speed, and benchmark external tools to document where they outperform and why. Each three-week cycle ships a concise evidence pack (hypothesis, datasets, eval method and baselines, safety notes, cost/latency deltas, reproducibility steps) plus an exec-ready demo. Parity gaps and blockers are logged weekly, routed to CoreAI’s prioritized backlog, and reviewed in AI Models & Ideas. The Knowledge Community then publishes patterns, configs, and reusable components so learnings propagate quickly, closing the loop back to Coeus and setting up the next set of experiments. The knowledge accrued by OCTO sponsored Idea Hub teams compounds over time: experienced OAI-stack builders pair with newer builders, each cycle beginning with a sprint-zero bootcamp, starter agents, shared eval harnesses, and mentor hours by core team members ensure momentum while high-signal updates feed into the SLT reviews and the cross company Knowledge Community channels.
The ‘ask’: Sponsor 4-6 Idea Hubs funding 20 net-new seats [GitHub (4), E&D (4), Charles Lamanna’s org (4), Security (4), CoreAI (4)] under OCTO dotted line program mission/cadence. Add 3-5 OCTO engineers to Project Coeus to broaden OpenAI asset coverage and accelerate Idea Hub execution. Formalize a semester long MAIDAP capstone rotation in OCTO aligned to the Idea Hubs and project Coeus mission/assets. Ring-fence an OCTO operating budget for compute/tokens, curated data, and selected third-party tools with evaluation, demo, and agent assets. For team model access, secure AOAI-hosted inference APIs and/or TWAPI in the orange tenant (torchflow checkpoints). Endorse an operating cadence for the program: weekly AI Models and Ideas, monthly portfolio reviews with Kevin/Rajesh/Jay, and a quarterly “Final Four” demo showcase with an Ignite/Build (or similar) high visibility demo-slot for selected projects.
[DT1]maybe put in the goal section a bit