Microsoft / Copilot

Apple filed a trade secrets lawsuit against OpenAI last Friday, alleging misconduct up to the chief hardware officer and claiming over 400 former Apple employees now work at OpenAI. OpenAI's response has been carefully hedged, and the timing is rough with an IPO reportedly planned for later this year. The episode also covers Satya Nadella warning enterprises against handing data to AI labs, whether open source can fix the data-trust problem, and an ex-OpenAI researcher launching a $200M drug-discovery startup.

This ACM Queue piece lays out why classical ops practices break down for ML: non-deterministic outputs and data as a system driver make canary deploys, health checks, and alerting nearly useless. Azure validates new models by having LLMs judge LLM output—the SRECon audience was audibly surprised. The authors argue the field must either find a better paradigm or fix the ones we have.

This paper studies tens of thousands of Microsoft engineers during the early-2026 rollout of Anthropic’s Claude Code and GitHub Copilot CLI. Three findings stand out. First, initial adoption spread mainly through peer social networks, not top-down mandates. Second, retention correlated more with an engineer’s coding activity level than with demographics. Third, adopters merged roughly 24% more pull requests than they otherwise would have, and the lift held across the four-month window. The authors use merged PRs as a proxy for output while noting a merged PR is not the same as delivered value. They also flag that token spend at organizational scale can reach millions of dollars annually, so misjudging adoption or retention makes the rollout expensive without changing engineering velocity.

Microsoft CEO Satya Nadella argued in a personal blog post that companies using proprietary models from labs like OpenAI and Anthropic are handing over sensitive business data. Those labs could later use that insight to compete with their own customers. He calls this the 'reverse information paradox.' The post cites similar warnings from VC Jason Calacanis and Palantir CEO Alex Karp but offers no hard data or case studies. Worth noting: Nadella runs a competing model business, so this reads as positioning for Microsoft's own offerings.

Microsoft CEO Satya Nadella argues that enterprises pay for AI while leaking proprietary know-how—prompts, tool use, correction feedback—as 'intellectual exhaust' that models absorb. He calls for a trust boundary where private evaluations, organizational memory, and the right to fine-tune own models with model outputs stay under enterprise control. The post does not disclose a timeline or product specifics.

Microsoft, Amazon, and Google datacenters emitted 104 million tonnes of CO₂ in 2025—equal to 33% of France's national total. Microsoft accounted for nearly half, driven by AI infrastructure expansion. All three have walked back clean-energy pledges: Amazon and Google dropped 24/7 carbon-free targets, and Microsoft's carbon-offset contracts were found to overstate impact. These figures are self-reported, so real emissions are likely higher.

An FT investigation found OpenAI and Google sold model access via Microsoft Azure and Google Cloud to at least eight Chinese companies on the US Entity List, including Huawei, SenseTime, Yitu, and iFlytek. Sales went through overseas subsidiaries or third-party resellers. Both companies say they didn't violate export controls, but internal documents obtained by FT show some sales teams knew the customers' backgrounds and kept the deals going. The core tension: whether cloud-based model access counts as an 'export' is still a legal gray area.

At the GPT 5.6 launch, OpenAI announced the model will be the 'preferred model' for Microsoft 365 Copilot across Word, Excel, PowerPoint, and Cowork. This is a direct response to Bloomberg's earlier report that Microsoft is swapping some OpenAI software for its own MAI models to cut costs. The post doesn't spell out what 'preferred model' actually means. And the earlier report never said ChatGPT would stop powering Microsoft apps—just that Microsoft is leaning more on its own tech. This reads like a PR move that doesn't contradict the cost-cutting story.

Microsoft's 2026 sustainability report shows 2025 carbon emissions are 25% above its 2020 baseline, driven by data center construction and supply chain. The company admits current sustainability solutions aren't keeping pace with AI demand, making its 2030 carbon-negative goal harder to reach. The report doesn't lay out a concrete catch-up plan.

The FT argues Microsoft’s Copilot strategy, built on its OpenAI tie-up, hasn’t yet translated into clear revenue gains. Azure growth is slowing, enterprise willingness to pay for Copilot remains uncertain, and in-house model efforts lag. The AI premium the market gave Microsoft now hinges on hard financial delivery.

OpenAI announced GPT-5.6 as the new preferred model for Microsoft 365 Copilot, covering Word, Excel, PowerPoint, Chat, and Cowork. The model promises more useful work per token: fewer prompt rounds in Word, more token-efficient analysis in Excel, and faster idea-to-slide conversion in PowerPoint. Both Microsoft's Copilot president Nitin Agrawal and OpenAI's API product head Nikunj Handa endorsed the move. The post does not disclose a rollout date, pricing changes, or benchmark comparisons—treat this as a partnership announcement rather than a product review for now.

Microsoft is replacing OpenAI and Anthropic models with its own MAI models in Copilot products like Excel and Outlook. MAI currently handles a small share of requests, but the goal is to phase out third-party model spending over time. AI head Mustafa Suleyman said in June that Anthropic costs are too high and Microsoft aims to eliminate them. Customers may get weaker models for the same subscription price; third-party models could later become paid add-ons. Microsoft markets MAI training data as clean and commercially licensed, but its technical paper confirms use of Common Crawl, whose legal status for AI training remains unsettled.

AI companies committed $9.75B over 12 months to forward-deployed engineering—embedding engineers inside customer orgs to deploy AI. That's one quarter of Accenture's annual labor cost. Three models are emerging: Microsoft and Amazon fund FDE from existing headcount; OpenAI and Anthropic created standalone entities backed by PE firms like TPG and Blackstone, with OpenAI acquiring 150-person consultancy Tomoro; Google Cloud committed $750M to a partner fund instead of building direct. The post argues FDE creates a moat: embedded engineers train customers on one lab's stack, see proprietary workflows and failure modes that feed back into model tuning, and make switching institutionally painful—not technically hard.

TechCrunch compiled a running list of major tech companies that cited AI as a factor in 2026 layoffs. Microsoft just cut about 4,800 roles, or 2.1% of its global workforce, saying the jobs are 'not being replaced by AI' but acknowledging AI is changing how work gets done. May was the worst month for tech layoffs in years, with AI as the most-cited reason. Roughly 120,000 tech roles have been cut so far in 2026. The list covers ten companies including Microsoft, Oracle, and GitLab, with specific headcounts and official statements for each.

Microsoft created a new unit called Frontier Company with a $2.5B budget and 6,000 industry and engineering experts embedded at customer sites, targeting measurable business outcomes. Rodrigo Kede Lima leads it; Microsoft Commercial CEO Judson Althoff calls it the industry's largest results-oriented engineering org. Microsoft positions itself as platform-neutral versus OpenAI and Anthropic, which deploy only their own models—ironic coming from Microsoft. System integrators Accenture, Capgemini, EY, KPMG, and PwC will help scale globally. OpenAI's DeployCo raised over $4B and fields roughly 150 on-site engineers; Anthropic partnered with Blackstone and Goldman Sachs for a deployment firm aimed at mid-sized companies. All three now agree: real AI value requires weaving into existing business processes, data pipelines, and compliance—not just shipping a chat tool.

Microsoft formed a new operating business called Microsoft Frontier Company to deliver enterprise AI deployments using its existing AI tools. It's backed by a $2.5 billion investment and 6,000 industry and engineering experts. Commercial Business CEO Judson Althoff pushed back on the Forward-Deployed Engineer label, calling it the largest outcome-driven engineering org in the industry. The move comes two days after AWS announced a similar $1 billion internal FDE effort, following earlier moves by OpenAI and Anthropic. The post doesn't disclose specific clients or delivery timelines.

The EU is considering watering down environmental reporting rules for data centres, a direct win for Amazon, Microsoft, and Google. A draft revision would drop mandatory disclosure of energy efficiency and water usage, leaving it to voluntary corporate reporting. Green groups call it a step backward during the AI infrastructure boom, while EU officials argue the original plan was too burdensome. The final text is still under negotiation.

On June 26, the New York Times filed its third amended complaint, shifting focus from model training to the supercomputer Microsoft built for OpenAI. Citing the Supreme Court's recent Cox ruling, the NYT argues Microsoft is liable for contributory infringement because it provided compute knowing OpenAI would generate infringing outputs. The complaint also notes Microsoft internally discussed using synthetic data instead of copyrighted material but didn't follow through. The case is in the Southern District of New York; the post doesn't include Microsoft's specific response.

A coalition representing nearly 400 US local newspapers sued Microsoft and OpenAI in the Southern District of New York. The complaint alleges the companies systematically scraped publishers' websites, copied articles to their own servers to train models behind Copilot and ChatGPT, and removed copyright management information. The plaintiffs say these AI products built billions in market value on publishers' content while publishers got nothing. OpenAI responded that training uses publicly available data under fair use; Microsoft hasn't commented yet.

Chevron signed its first major power deal with Microsoft, planning over 1 GW of gas-fired plants by 2028 to directly supply Microsoft data centers. This marks an oil major's first large-scale move into power generation rather than just selling gas. The plants will include carbon capture, though the article doesn't specify capture rates or costs. Chevron also aims to build next to data centers, bypassing the 5-year average US grid interconnection queue. The signal for AI builders: cloud providers are now pulling oil companies into the power business.