Tag: WebDev

Observability startup Raindrop AI’s new open source, MIT Licensed "Workshop" tool, launched today, gives developers something that they've likely wanted, perhaps subconsciously, since the agentic AI era kicked off in earnest last year: a local debugger and evaluation tool specifically designed for AI agents, allowing devs to see all the traces of what their agent has been doing in a single, lightweight Structured Query Language (SQL) database file (.db)It functions as a local daemon and UI that streams every token, tool call, and decision to a local dashboard—typically hosted at localhost:5899—the moment it occurs. By visiting their localhost, developers can then see everything their agent was up to — including mistakes or errors — and identify what went wrong, when, and ideally, discern why. It's all stored in a single .db file, wh

Cerebras Systems, the Silicon Valley chipmaker that built the world's largest commercial AI processor, erupted onto the Nasdaq on Wednesday, opening at $350 per share — nearly double its $185 IPO price — and rocketing past a $100 billion market capitalization in its first hours of trading. The debut instantly crowned Cerebras as one of the most valuable semiconductor companies on Earth and validated a decade-long bet that the AI industry would eventually demand a fundamentally different kind of chip.The company sold 30 million shares at $185 apiece, raising $5.55 billion in what Bloomberg reported as

Anthony Grieco, Cisco’s SVP and chief security and trust officer, did not hesitate when VentureBeat asked whether rogue agent incidents are reaching Cisco’s customer base."A hundred percent. We see them regularly," Grieco told VentureBeat in an exclusive interview at RSAC 2026. "I've heard some that I can't repeat, but they do get to the places of, you know, agents are doing things that they think are the right things to do."The incidents Grieco described follow a consistent pattern: authentication passes, identity checks clear. The agent is exactly who it claims to be. Then it accesses data it was never scoped to touch or takes an action nobody authorized at that level of granularity. The failure is not identity; it's authorization."The business is saying things like, we're gonna have 500 agents per employee," Grieco told VentureBeat. "The security leaders are really focused on how to make sure that we

A code migration agent finishes its run, and the pipeline looks green. But several pieces were never compiled — and it took days to catch. That's not a model failure; that's an agent deciding it was done before it actually was.Many enterprises are now seeing that production AI agent pipelines fail not because of the models’ abilities but because the model behind the agent decides to stop. Several methods to prevent premature task exits are now available from LangChain, Google and OpenAI, though these often rely on separate evaluation systems. The newest method comes from Anthropic: /goals on Claude Code, which formally separates task execution and task evaluation. Coding agents work in a loop: they read files, run commands, edit code and then check whether the task is done. Claude Code /goals essentially adds a second layer to that loop. After a user defines a goal, Claude will continue

Every query an enterprise AI application processes, every correction a subject matter expert makes to its output — that interaction is training data. Most organizations are not capturing it. The production workflows companies have already built are generating a continuous signal that improves AI models, and it is disappearing.San Francisco-based Empromptu AI on Thursday launched Alchemy Models with a straightforward premise: the AI applications enterprises are already building are generating training data, and most of it is going to waste. The platform captures that signal automatically, routing validated outputs from subject matter experts back into a fine-tuning pipeline that improves the model over time. Enterprises own the resulting weights outright.It sits in different territory from both RAG and traditional fine-tuning. RAG retrieves external context at inference time without modifying model weights. Traditional fine-tuning changes weights but r

For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is applying the same metaphor to artificial intelligence, assigning estimated intelligence quotients to more than 50 of the world's most powerful language models and plotting them on a standard bell curve.The result is a set of interactive visualizations at aiiq.org that have ricocheted across social media in the past week, drawing praise from enterprise technologists who say the charts make an impossibly complex market legible — and sharp criticism from researchers and commentators who warn the entire framework is misleading."This is super useful," wrote Thibaut Mélen, a technology commentator, on X. "Much easier to understand model progress w

Good news, OpenClaw fans — you can once again use your Claude AI subscription to power the hit, open source, autonomous AI agentic harness! But, there's a big catch with how it's being enacted. A few hours ago, Anthropic announced via its official developer communications account on X, @ClaudeDevs, that it is changing its Claude paid subscription tiers, introducing a new subcategory of "Agent SDK" credits for all paid subscribers, which they can now allocate specifically for "programmatic" uses, including external, third-party agents such as OpenClaw.The move is a major reversal from the Anthropic's