Google is retiring one of Gemini’s most recognizable customization features as the company moves toward a more agent-oriented approach to artificial intelligence, folding Gems into a broader “skills” system rather than maintaining them as standalone AI assistants.

The change will take effect on November 17, 2026, according to a notice displayed in the Gemini app. Google said users will not need to recreate their custom assistants because existing Gems will be automatically migrated into skills. The current Gems will remain available until the transition.

The move comes as the consumer AI market increasingly shifts from chatbots that respond to individual prompts toward AI agents that can perform multi-step tasks with less user direction. Meta has been developing products such as Muse and Instinct around that model, raising the competitive pressure on Google to make Gemini more capable as an integrated assistant rather than a collection of separately branded features.

Gems were introduced in 2024 as a way for Gemini users to create customized assistants with persistent instructions for specific jobs. Google also offered pre-built versions, including a learning coach, brainstorming assistant, career guide, coding partner and editor.

Users could create their own versions for tasks such as fitness coaching, nutrition planning and travel. Gems could also be shared with other users, giving Google a potential mechanism for expanding Gemini through user-created AI experiences.

That model is now being absorbed into the broader skills framework.

The change suggests Google is moving away from treating customized AI personalities or assistants as individual products and toward treating them as reusable capabilities that can be invoked inside different tasks.

A standalone Gem effectively required the user to decide which assistant they wanted to use. A skill can instead function as a capability that is called when it is relevant to a particular task.

Google’s decision to migrate Gems rather than simply discontinue them also indicates that the company wants to preserve the underlying user-created instructions while changing how those instructions are accessed.

For existing users, the practical benefit is that their work should not disappear.

Therefore, the bigger issue is discoverability.

Google says users will be able to invoke skills by entering a forward slash, “/”, in a task thread and selecting the relevant skill. That creates a more structured interface, but it also introduces an additional step between the user and the AI capability.

For mainstream consumers accustomed to simply typing what they want into a chatbot, that may feel less intuitive.

The Agent Race is Changing The Interface

The change comes as the competitive focus in consumer AI is moving toward agents that can handle tasks rather than simply generate responses. A traditional chatbot requires the user to formulate a request, interpret the answer, and decide what to do next. An agent can potentially handle a larger sequence of actions, using specialized capabilities along the way.

That makes the underlying architecture more important than the branding of individual assistants.

Google’s skills approach appears designed to support that model. Instead of creating a separate interface for every specialized assistant, Google can maintain a common Gemini environment in which different capabilities are invoked as needed.

But there is a trade-off.

The simpler the underlying architecture becomes, the less visible individual features may be to users. Gems gave users a clear concept: create an assistant, give it instructions, and use it for a particular purpose. Skills are more abstract.

That could make the system more powerful while making it harder for consumers to understand what they can actually do with it.

Google’s Recurring Problem With AI Branding

The retirement of Gems also highlights a broader issue with Google’s product strategy.

Google has frequently introduced new products and features under distinct names, only to later merge, rename, or discontinue them. The company’s history with messaging and communication services is an earlier example of the difficulty of maintaining a coherent product architecture when features and services evolve rapidly.

AI has accelerated that problem.

Google has introduced a large number of Gemini-related products and capabilities as it attempts to compete across consumer applications, search, productivity software, and enterprise services.

The risk is that users end up having to understand Google’s internal product structure before they can take advantage of the technology.

Meta’s approach with products such as Muse represents a different direction. The user does not necessarily need to understand which underlying capability is being activated. The emphasis is on describing the desired outcome and allowing the AI system to determine how to accomplish it.

That approach is expected to be increasingly used as AI agents move into everyday consumer applications.

However, the end of Gems does not necessarily mean the end of the functionality users created with them. By automatically converting Gems into skills, Google is preserving the underlying customization while changing the interface through which it is accessed.

That could ultimately make the feature more useful if skills become deeply integrated across Gemini’s different task environments. The challenge is making that power accessible without forcing users to learn a new workflow.

However, Google currently appears to be betting that a common skills architecture will serve Gemini better than maintaining a separate ecosystem of custom assistants.

by EBC Financial Group?? 

Heavy demand for one-year Treasury bills at the first post-cut auction suggests appetite for longer-dated naira assets remains strong, but lower Nigerian yields and higher US rates are narrowing the cushion available to investors.

LAGOS, 29 September – Nigeria’s first Treasury-bill auction following the Central Bank of Nigeria’s 350 basis point reset of its Monetary Policy Rate from 26.5% to 23% has shifted the market debate beyond the size of the cut. The question is whether foreign and domestic demand for naira assets can remain resilient as returns on short-dated government securities narrow both domestically and relative to dollar assets. The CBN set the Monetary Policy Rate at 23%, at its 21 to 22 September meeting. It also recalibrated the Standing Facilities Corridor to +50/-300 basis points around the MPR. The CBN framed the move as a reset intended to improve the transmission of monetary policy and bring the benchmark closer to prevailing market rates.

The first auction after the decision offered an early indication of how investors were responding. The 91-day stop rate fell to 15.50% from 16.30% at the previous auction, while the 182-day rate declined to 15.80% from 16.50%. The 364-day bill cleared at 15.89%, down from 16.62%, a fall of 73 basis points.  Demand was not evenly distributed. The 91-day bill received N54.93 billion in subscriptions against N100 billion offered, while the 182-day bill attracted N82.23 billion against N100 billion offered. By contrast, investors submitted approximately N4.09 trillion for the 364-day bill against N400 billion offered, accounting for around 97% of total subscriptions across the auction. That concentration matters. Heavy demand for one-year paper may indicate continued appetite for Nigerian fixed income, but it can also reflect investors attempting to lock in current yields before further rate reductions. The auction results do not distinguish foreign demand from domestic participation, while abundant banking system liquidity provides another source of demand.

David Precious, Senior Market Analyst at EBC Financial Group, said, “The key issue is no longer whether high yields can attract money into Nigeria. They already have. The next test is whether demand remains resilient as the yield advantage narrows, because that would help show whether investors are responding increasingly to stronger external buffers and macroeconomic stability, or whether carry is still doing most of the work.”

Nigeria’s Carry Cushion Is Narrowing from Both Sides

Domestic repricing is only half the equation for international investors. On 16 September, the US Federal Reserve raised its policy rate by 25 basis points to a target range of 3.75% to 4.00%, its first increase since 2023. That raises returns the on-dollar assets even as Nigerian short-term yields decline. The result is a narrower relative cushion for investors willing to take naira currency risk. For a foreign portfolio investor, the nominal return on a Nigerian security is only one part of the calculation. Exchange-rate movements, inflation, liquidity and the ability to exit or reinvest all affect the realised return. A lower Nigerian yield therefore does not automatically lead to capital outflows, but it does leave a smaller cushion if other risks deteriorate.

Precious added, “The gap matters because investors do not assess Nigerian yields in isolation. If returns on lower-risk dollar assets rise while naira yields fall, currency stability and confidence in Nigeria’s external position become more important parts of the decision. The market therefore needs to distinguish demand driven by improving fundamentals from demand that is still primarily about locking in yield.”

From Attracting Capital to Retaining It

This extends a tension EBC highlighted in its July analysis of Nigeria’s foreign-exchange reserves: stronger reserves improve the country’s external buffer, but some incoming portfolio capital can still leave quickly if the risk-return balance changes. That issue is becoming more relevant now that easing has moved from gradual cuts to a 350-basis-point reset. The first phase of Nigeria’s adjustment involved restoring confidence, improving FX market functioning and offering sufficiently high local returns to attract capital. The next phase is harder to assess. It is about whether confidence can remain durable when investors are paid less to hold naira assets. Recent OMO activity offers another useful signal, but not a definitive answer. At the 24 September OMO auction, the CBN offered N1 trillion across three maturities and received approximately N6.1 trillion in subscriptions, with N2.3 trillion allotted. The 152-day bill cleared at 17.29%, while the 180-day bill cleared at 16.99%. However, this demand also needs context. Banking-system liquidity stood at about N5.98 trillion in the week ended 25 September, and a further N2.43 trillion of OMO maturities is expected to return to the system this week. High liquidity may support demand for fixed-income assets independently of foreign portfolio flows.

Why the Naira Becomes More Important as Yields Fall

As the carry cushion narrows, currency performance matters more. The naira closed Friday at N1,329.51 per dollar in the official market, only slightly weaker than the previous session. That relative stability is important because currency depreciation can quickly offset the return earned on a local-currency asset. A smaller yield advantage therefore places more weight on the durability of Nigeria’s external position. If inflation continues to moderate, FX liquidity remains functional and external buffers stay strong, investors may tolerate lower nominal returns. If those conditions weaken, the reduced carry cushion becomes more significant. This is why the policy reset should not be judged solely by the 350-basis-point headline.

What the Market Should Watch Next

The next test is not one auction. Future Treasury-bill and OMO operations will show whether demand remains concentrated at the long end and whether investors continue accepting lower yields. Portfolio-flow composition will be equally important, because current auction data do not identify how much demand is foreign. Liquidity conditions also deserve close attention. With large OMO maturities returning cash to the banking system, strong subscriptions may partly reflect domestic money seeking short-duration assets rather than a fresh wave of foreign capital. The question is whether Nigeria can gradually move from attracting capital through exceptional yields to retaining confidence through stronger fundamentals.

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Leveraging its FCA-regulated liquidity access, EBC has established long-term and stable partnerships with over 50 leading banks and non-bank liquidity providers globally. By integrating clearing-grade liquidity quotes, EBC provides clients with direct access to the primary liquidity market, delivering highly competitive institutional-grade liquidity depth and bank-level spreads, allowing clients to easily enjoy extremely low transaction costs. All clients within the group can enjoy top-tier liquidity access through its FCA license; even for offshore accounts, quotes and orders are ultimately processed by a UK company. Combining big data and AI algorithms to optimize order matching mechanisms, EBC achieves over 87.6% of its orders executed at more favourable prices. For high-frequency and high-volume traders, EBC offers the customized EBC Private Room, a dedicated segregated trading channel that conceals trading orders and avoids market order manipulation. EBC is also one of the few licensed brokers in the industry capable of providing qualified professional investors with FCA liquidity clearing accounts with leverage up to 100x.

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Meta Platforms is hiring MongoDB CEO Chirantan “CJ” Desai to lead a newly created business aimed at bringing the company’s artificial intelligence models, agents and software tools to corporate customers, in a move that signals a broader attempt to turn Meta’s rapidly expanding consumer AI business into an enterprise platform.

MongoDB shares have fallen about 28% on Monday after the database software company disclosed Desai’s departure, less than a year after he became chief executive. MongoDB has appointed its former CEO, Dev Ittycheria, as interim chief executive while it searches for a permanent replacement.

The reaction underpins the importance investors placed on Desai’s leadership as MongoDB seeks to compete in an increasingly crowded market for databases, cloud infrastructure and AI-enabled enterprise software.

“While the departure is disappointing, we believe MongoDB remains well-positioned strategically and view the share-price reaction as overdone,” Piper Sandler said in a note.

For Meta, however, the hire represents a significant escalation of its enterprise ambitions.

Desai will report directly to Meta CEO Mark Zuckerberg as chief enterprise platform officer, a newly created position. His mandate will be to turn Meta’s AI technology stack into products and services that businesses can deploy inside their own operations.

That puts an executive with extensive enterprise software experience at the center of Meta’s effort to move beyond its traditional advertising-driven business and establish AI as a platform used directly by companies.

Meta Takes Its AI Stack into The Enterprise

Meta said Monday that its new Meta Enterprise Platform will bring together its AI models, agents and tools for corporate customers. The offering will include Muse, Meta Business Agent and coding tools, giving businesses access to several parts of Meta’s AI portfolio through an enterprise-focused platform.

The move represents a different commercial proposition from Meta’s consumer AI strategy.

Muse was launched earlier this month as a personal AI agent designed to perform tasks for consumers, including shopping, booking travel, sending emails, and making payments. Its rapid rise in Apple’s App Store and Google Play rankings has drawn attention from analysts, who have described it as potentially the biggest U.S. app launch since OpenAI’s ChatGPT helped ignite the current AI boom in November 2022.

Meta now appears to be attempting to take some of that momentum into the corporate market.

The enterprise opportunity is considerably different from consumer AI. Companies need AI systems that can work with proprietary data, connect to existing software, meet security and compliance requirements, and operate reliably across large organizations. They also need clear controls over what an AI agent is allowed to do.

That makes Desai’s background especially relevant.

Before joining MongoDB, he led product and engineering at Cloudflare and spent almost eight years at ServiceNow, where he ultimately became president and chief operating officer. Both companies operate deeply within enterprise technology, giving Desai experience with the software infrastructure and purchasing processes that determine whether businesses adopt new technologies at scale.

His MongoDB experience adds another layer. MongoDB provides databases and related tools used by companies to build and operate applications, manage data, conduct searches and analytics, and support AI workloads.

Meta is therefore bringing in an executive whose career has largely centered on the infrastructure layer that enterprises need before they can deploy AI at scale.

Zuckerberg’s Enterprise Bet

The decision to have Desai report directly to Zuckerberg also signals the importance Meta is attaching to the new business.

Meta has spent heavily on AI infrastructure and model development, while its consumer products give it an enormous distribution network. The unresolved commercial question has been how much of that investment can be converted into direct enterprise revenue.

Advertising remains the economic foundation of Meta’s business, but selling AI products directly to companies could create another revenue stream and give the company a more diversified role in the technology stack.

The enterprise market is already crowded.

Microsoft has embedded AI across its productivity and cloud products, Google offers Gemini across its enterprise ecosystem, Amazon is integrating AI into AWS, and a large group of startups is competing to provide specialized agents and AI infrastructure.

Meta enters that market with a different set of assets. Its open model strategy has given developers access to the Llama family, while its consumer products provide a huge user base, and its growing collection of AI agents gives the company experience deploying AI at large scale.

The challenge is turning those assets into something corporations are willing to integrate deeply into their operations. That is where the Meta Enterprise Platform could become important. Rather than selling a single chatbot, Meta is positioning its AI offering as a collection of models, agents, and developer tools that businesses can use for different functions. The inclusion of coding tools and Meta Business Agent suggests the company wants to participate in both software development and business workflows.

Muse could eventually become another component of that broader platform rather than remaining primarily a consumer application.

MongoDB Faces an Unexpected Leadership Test

For MongoDB, Desai’s departure creates an immediate leadership transition at a time when the database industry is being reshaped by AI. MongoDB has built its position around helping developers manage application data, while AI is increasing demand for databases capable of handling unstructured information, vector search, and real-time workloads.

Ittycheria’s return as interim CEO provides continuity because he previously led MongoDB for almost a decade. But the board now has to find a permanent successor while investors assess whether the leadership change affects the company’s product and AI strategy.

The sharp decline in MongoDB shares shows that investors viewed the departure as material, even though Piper Sandler argued that the market reaction was excessive.

For Meta, meanwhile, the appointment is effectively an acknowledgement that building frontier AI models is only one part of the commercial battle. The next contest is over distribution, integration, and trust inside businesses.

AI companies have spent the past several years competing over model benchmarks and consumer adoption. The enterprise market requires something different: convincing companies to allow AI systems into sensitive workflows and giving those systems enough access to act on corporate data and software.

Desai’s mandate suggests Meta wants to compete directly on that layer.

If Meta can connect its models and agents to the systems businesses already use, the company could turn its AI investment into an enterprise software business rather than relying primarily on consumer engagement and advertising.

The hire also illustrates how the AI race is reshaping the broader technology industry. Following its $15 billion acqui-hire strategy that resulted in the recruitment of Scale AI CEO Alexandr Wang last year, Meta is no longer simply recruiting AI researchers and engineers. It is now recruiting executives who understand how large companies buy, deploy, and manage software.

That may ultimately prove as important as model performance as the industry moves from AI assistants that answer questions to agents that perform work.