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Historically, the cybersecurity conversation in banking and fintech has centered on detection: can we spot the intrusion, flag the anomaly, catch the fraud pattern before it does damage? We developed incredibly sophisticated tools that can sift through thousands of ‘signals’ every time a customer makes a payment, ranging from how
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Sponsor Posts Subquadratic: the LLM built for 12M-token reasoning — SubQ can reason across entire codebases and document sets in one pass with no RAG workarounds. Read how SubQ 1.1 Small holds near-perfect retrieval out to 12M tokens. Cloudflare Connect 2026: The Agentic Conference — Stop preparing for agents. Start running
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For the last 21 months, I have been the only engineer on TopSet, a system that trades real money. It picks a portfolio with machine-learning models, rebalances on a schedule, and executes through live broker APIs on infrastructure I own end-to-end. It is my own capital, not anyone else’s.
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If you are leading an organization today, you are probably under pressure to “embrace AI.” Competitors are making announcements, employees are asking for better tools, and senior leaders want to know how artificial intelligence can improve performance. The opportunities are real. But digital transformation is not simply about buying new
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The software industry has spent the last three years trying to make large language models behave like functions. It has not gone well. Every team that has shipped an LLM-powered feature has paid a heavy engineering tax in parsing layers, retry loops, JSON repair libraries, hallucination guards, and the quiet
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There are a plethora of ways in which you can obtain media coverage for your products and services by paying for it. This is possible across print, electronic, and digital media. You can pay for straightforward ads or go for native advertising. But that begs the question: if everybody can
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Overview LFM2.5-2.6B-Qwen3.8-Turbo-Brilliance-Power-X12-NEO-MAX-GGUF is a 2.69B-parameter text-generation model maintained by DavidAU. It combines the LFM2.5-2.6B base model’s general-purpose, tool-calling, and agentic capabilities with the Turbo Brilliance system: 12 reasoning modes, 12 instruct modes, and an embedded help system that recommends modes for a stated
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Shared context is one of the strongest ideas in HubSpot's new AI architecture. The company now describes Growth Context as a combined understanding of the business, team, and customer. Context Home can make foundational knowledge available across AI tools. Projects can add instructions, files, HubSpot content, knowledge vaults,
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For years, backend engineers have been trained to fear failed requests. 500 Internal Server Error503 Service UnavailableTimeoutConnection reset Those failures are visible. They trigger alerts. Dashboards turn red. Retries begin. Engineers investigate. AI agents introduce a more uncomfortable possibility: What if nothing fails? Imagine an enterprise agent processing a refund.
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AI agents can produce code in minutes, but generating code is only one part of software delivery. The harder question is what happens next: how the change gets the right context, how it is verified, and who decides whether it is safe to ship. Here are three handoffs worth examining
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There are still some fundamental truths that won't change. LLMs are making it dramatically easier to build software, so yes, we're going to have more applications, more agents, more workloads, and more data. But here's one thing that won't change: developers want
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By Anuj Gupta, Founder & CEO, KiteFishAI For much of the generative AI era, progress has been closely associated with scale. Bigger models, more parameters, larger training datasets, and increasingly expensive compute became the dominant measures of technological advancement. That approach has delivered remarkable results. General-purpose foundation models can write
