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The race to deploy agentic AI is on. Across the enterprise, systems that can plan, take actions and collaborate across business applications promise unprecedented efficiency. But in the rush to automate, a critical component is being overlooked: Scalable security. We are building a workforce of digital employees without giving them a secure way to log in, access data and do their jobs without creating catastrophic risk.The fundamental problem is that traditional identity and access management (IAM) designed
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In an impressive feat, Japanese startup Sakana AI’s coding agent ALE-Agent recently secured first place in the AtCoder Heuristic Contest (AHC058), a complex coding competition that involves complicated optimization problems — and a more difficult and perhaps telling challenge than benchmarks like HumanEval, which mostly test the ability to write isolated functions, and which many AI models and agents now regularly pass with ease ("benchmark saturation"). Sakana's accomplishment with ALE-Agent... Read more ›
7
Anthropic has confirmed the implementation of strict new technical safeguards preventing third-party applications from spoofing its official coding client, Claude Code, in order to access the underlying Claude AI models for more favorably pricing and limits — a move that has disrupted workflows for users of popular open source coding agent OpenCode. Simultaneously but separately, it has restricted usage of its AI models by rival labs including xAI (through the... Read more ›
3
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2
A new framework from researchers Alexander and Jacob Roman rejects the complexity of current AI tools, offering a synchronous, type-safe alternative designed for reproducibility and cost-conscious science.In the rush to build autonomous AI agents, developers have largely been forced into a binary choice: surrender control to massive, complex ecosystems like LangChain, or lock themselves into single-vendor SDKs from providers like Anthropic or OpenAI. For software engineers, this is an annoyance.... Read more ›
1
Our LLM API bill was growing 30% month-over-month. Traffic was increasing, but not that fast. When I analyzed our query logs, I found the real problem: Users ask the same questions in different ways."What's your return policy?," "How do I return something?", and "Can I get a refund?" were all hitting our LLM separately, generating nearly identical responses, each incurring full API costs.Exact-match caching, the obvious first solution, captured only... Read more ›
1
Rather than asking how AI agents can work for them, a key question in enterprise is now: Are agents playing well together? This makes orchestration across multi-agent systems and platforms a critical concern — and a key differentiator. “Agent-to-agent communications is emerging as a really big deal,” G2’s chief innovation officer Tim Sanders told VentureBeat. “Because if you don't orchestrate it, you get misunderstandings, like people speaking foreign languages to... Read more ›
1
As agentic AI moves from experiments to real production workloads, a quiet but serious infrastructure problem is coming into focus: memory. Not compute. Not models. Memory.Under the hood, today’s GPUs simply don’t have enough space to hold the Key-Value (KV) caches that modern, long-running AI agents depend on to maintain context. The result is a lot of invisible waste — GPUs redoing work they’ve already done, cloud costs climbing, and... Read more ›
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16.01.2026 08:03
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