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Last week, one of our product managers (PMs) built and shipped a feature. Not spec’d it. Not filed a ticket for it. Built it, tested it, and shipped it to production. In a day. A few days earlier, our designer noticed that the visual appearance of our IDE plugins had drifted from the design system….

Many people have tried AI tools and walked away unimpressed. I get it — many demos promise magic, but in practice, the results can feel underwhelming. That’s why I want to write this not as a futurist prediction, but from lived experience. Over the past six months, I turned my engineering organization AI-first. I’ve shared…

Processing 200,000 tokens through a large language model is expensive and slow: the longer the context, the faster the costs spiral. Researchers at Tsinghua University and Z.ai have built a technique called IndexCache that cuts up to 75% of the redundant computation in sparse attention models, delivering up to 1.82x faster time-to-first-token and 1.48x faster…

Intercom is taking an unusual gamble for a legacy software company: building its own AI model. The 15-year-old massive customer service platform announced Fin Apex 1.0 on Thursday, a small, purpose-built AI model that the company claims outperforms leading frontier models from OpenAI and Anthropic on the metrics that matter most for customer support. The…

The enterprise voice AI market is in the middle of a land grab. ElevenLabs and IBM announced a collaboration just this week to bring premium voice capabilities into IBM’s watsonx Orchestrate platform. Google Cloud has been expanding its Chirp 3 HD voices. OpenAI continues to iterate on its own speech synthesis. And the market underpinning…

Presented by OutSystems After two years of flashy AI demos, rushed agent prototypes, and breathless predictions, enterprise technology leaders are striking a more pragmatic tone in 2026. In a recent webinar hosted by OutSystems, a panel of software executives and enterprise practitioners made the case that the most consequential AI work happening now is focused…

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the “Key-Value (KV) cache bottleneck.” Every word a model processes must be stored as a high-dimensional vector in high-speed memory. For long-form tasks, this “digital cheat sheet” swells rapidly, devouring the…

Enterprise data teams moving agentic AI into production are hitting a consistent failure point at the data tier. Agents built across a vector store, a relational database, a graph store and a lakehouse require sync pipelines to keep context current. Under production load, that context goes stale.  Oracle, whose database infrastructure runs the transaction systems…

Standard RAG pipelines break when enterprises try to use them for long-term, multi-session LLM agent deployments. This is a critical limitation as demand for persistent AI assistants grows. xMemory, a new technique developed by researchers at King’s College London and The Alan Turing Institute, solves this by organizing conversations into a searchable hierarchy of semantic…

OpenAI is shuttering Sora, its stand-alone AI video generation app and social network, and the availability for developers to access the Sora 2 video model family through its application programming interface (API) to rely on it for their own products or video generation pipelines. The announcement came abruptly this afternoon with OpenAI posting a message…