AI
AI agents and agentic workflows
How AI agents differ from chat assistants, the current frameworks, what they're actually good at, and the failure modes.
AI agents extend the LLM pattern beyond single-turn answering: the model plans, takes actions through tools, observes the result, and iterates until a task is complete. The technical pieces — tool calling, planning, memory — are now standardised enough that most large engineering organisations are running internal agent pilots.
Notifire's coverage of this area is focused on what actually ships to production versus what's a demo. Agent reliability under real-world conditions is the open problem; the frameworks competing to solve it shift monthly.
Latest briefings on AI agents and agentic workflows
Infra
New AWS Agent Finds and Fixes Cloud Overspending
AWS has launched a new managed service called FinOps Agent. It automatically investigates cost spikes, finds the cause, and sends alerts to the right teams through tools like Slack and Jira to help control cloud spending.
Ashish Kale ·
Tech
AI Drones Now Hunt and Kill Autonomously
Ukraine has deployed autonomous drones that hunt and destroy enemy drones without human control. The system automates 95% of the process, a major leap in AI-driven warfare and drone countermeasures.
Navdeep Kaur Mahal ·
AI
Notion Kills Email App as Users Choose AI
Notion is shutting down its Notion Mail app, stating that users now prefer AI agents to manage their inboxes. The move highlights a major shift in how people interact with email and productivity software.
Neeraj Dhiman ·
AI
Salesforce AI Agent Only Charges for Solved Problems
Salesforce launched a new AI help agent with a novel pricing model. Companies will only pay when the AI successfully resolves a customer issue, directly linking support costs to its actual performance and value.
Neeraj Dhiman ·
AI
Simple Config Flaws Are Hurting Your AI Agent
Researchers have identified common "smells"—structural flaws in AI agent configuration files. These issues can waste tokens, bloat context, and make your coding assistants less reliable and more expensive to run.
Neeraj Dhiman ·
AI
Nvidia Reveals Its Simple Strategy for AI Agents
Nvidia defines an AI agent as simply a large language model plus a "harness" to connect it to tools. This view shapes its support for frameworks like OpenClaw, signaling a key direction for developers building autonomous AI systems.
Neeraj Dhiman ·
AI
How OpenAI's AI Agent Queries 600 Petabytes
OpenAI revealed how its internal AI agent, Kepler, analyzes over 600 petabytes of data. It uses techniques like RAG and automated code analysis to overcome context limits, offering a blueprint for building large-scale AI systems.
Neeraj Dhiman ·
Infra
Azure Adds AI Agents With No Cold Start
Azure Functions now has a serverless agents runtime in public preview. It lets developers build AI-powered automations without the usual cold start delays or extra costs on the Flex Consumption plan.
Ashish Kale ·
AI
AI Agent Flaw Lets One Page Hijack Your Server
Microsoft security researchers discovered a critical vulnerability named 'AutoJack' in AI agent frameworks like AutoGen Studio. The flaw allows an attacker to gain full control of the host server using just a single malicious web page.
Neeraj Dhiman ·
Tech
GitHub's New App Puts AI Agents to Work
GitHub launched a new desktop app for Copilot. It acts as a control center to manage AI coding agents, aiming to fix disjointed workflows and cut down on time spent reviewing AI-generated code.
Taranpreet Singh ·
AI
A Blueprint for Building AI Agents That Last
A new architectural blueprint helps engineering leaders build more reliable AI agent systems. It uses modular frameworks and event-sourcing to create agents that can handle complex, unpredictable tasks without failing.
Neeraj Dhiman ·
AI
Anthropic's Claude AI Builds Its Own Agent Managers
Anthropic's Claude AI can now generate its own custom "execution harnesses." This system allows it to coordinate teams of specialized AI agents to complete complex, multi-step tasks more effectively for developers.
Neeraj Dhiman ·
Infra
Vercel Unlocks 24-Hour Sessions for Developers
Vercel now allows its Sandboxes to run for up to 24 hours, a major increase from the previous five-hour limit. This change helps developers run complex, long-running tasks like large data processing and extensive testing.
Ashish Kale ·
AI
Your AI Assistant Can Now Shop With Visa
OpenAI and Visa are partnering to let AI agents make online purchases. This allows AI to autonomously handle e-commerce transactions, creating new opportunities and significant security challenges.
Neeraj Dhiman ·
Infra
Siemens Uses AI Agents to Modernize Factory Software
Siemens is partnering with Google Cloud to modernize its vast industrial software using AI agents. This new approach tackles the complex challenge of updating legacy code, offering a potential model for other large enterprises.
Ashish Kale ·
Security
Bad Design Is Your Biggest Security Risk
A top university CIO argues that security fails when it's hard to use. He says controls should be invisible to users, and the same principle must apply to new AI agents to keep them secure.
Neeraj Dhiman ·
AI
Why Your Team Isn't Ready for AI Agents Yet
MIT experts warn that the biggest hurdle for agentic AI isn't the technology, but human readiness. Leaders are discovering a major gap between the hype and the reality of integrating these advanced AI systems into daily workflows.
Neeraj Dhiman ·
Data
Autonomous Databases Won't Replace Your Team
Autonomous databases promise to manage themselves, but they won't eliminate the need for human experts. Percona's co-founder explains that while automation is transforming data management, human oversight and strategic input remain essential for success.
Taranpreet Singh ·
AI
Designing Reliable AI Agent Systems
Aaron Erickson outlines a shift from basic AI testing to building robust, multi-agent systems. He details architectural patterns for production-grade AI, including combining deterministic guardrails with agentic discovery, optimizing agent hierarchies, and implementing rigorous evaluation frameworks to ensure reliability and scalability.
Neeraj Dhiman ·
AI
Robinhood now lets AI agents trade stocks
Robinhood has introduced a new feature allowing users to connect AI agents to their trading accounts. These agents can analyze portfolios and execute trades, but are restricted to using a pre-loaded balance in a dedicated wallet, limiting potential financial risk from automated strategies.
Neeraj Dhiman ·
Security
AI Agents Lead New Security Threats
A recent security bulletin highlights a range of emerging threats facing organizations. These include the misuse of AI agents for malicious purposes, the availability of new command-and-control tools for attackers, deceptive social engineering tactics, and the continued use of JavaScript backdoors to compromise systems.
Neeraj Dhiman ·
Data
Stop Rebuilding Your AI Agent Data Connections
Redis has released a new tool, RedisVL MCP, that lets developers connect their Redis data to various AI agent frameworks without rewriting code for each one. This simplifies building AI applications on existing data stores.
Taranpreet Singh ·
AI
The AI Agent Integration Debate
Enterprise software vendors agree that AI agents require deep context to be useful, but they are divided on how to provide it. The key debate is whether companies should integrate AI into existing systems or undertake a risky strategy of rebuilding their entire infrastructure from scratch.
Neeraj Dhiman ·
AI
Are We Deploying AI Agents Like It's 1999?
A new opinion piece warns that the rush to build AI agents is repeating the mistakes of early software development, where deploying apps was as simple and risky as copying a .exe file.
Neeraj Dhiman ·
AI
How LinkedIn Manages Its AI Agent Workforce
LinkedIn is building a unified platform to manage its AI agents for engineering tasks like coding and UI testing. This approach moves beyond scattered AI tools, creating a scalable system for complex, multi-agent workflows.
Neeraj Dhiman ·
AI
Experts Warn Against Ungoverned AI
AI experts are warning CIOs against deploying AI agents without proper governance and observability tools. Rushing into adoption without visibility into the agents' decision-making processes creates a "time bomb" with the potential for severe negative consequences, turning a potential productivity boost into a significant business risk.
Neeraj Dhiman ·
AI
Replit partners with Visa for AI
Replit is partnering with Visa to integrate payment infrastructure into its development platform. The collaboration, which includes a strategic investment from Visa, aims to enable AI agents to transact autonomously, creating a new model for "agentic commerce" where AI can participate directly in the economy.
Neeraj Dhiman ·
AI
AI Agent Adoption Surges Among Developers
A new Stack Overflow survey reveals that 59% of software engineers now use agentic AI, nearly doubling previous adoption rates. This rapid growth shows a clear trend, though current use cases remain primarily focused on single-agent tasks that are closely monitored by developers.
Neeraj Dhiman ·
AI
Cloudflare Adds Support for Claude Agents
Cloudflare has integrated support for Claude Managed Agents, allowing developers to build, deploy, and manage AI agents directly on its global network. This enables connecting agents to private systems, choosing runtime environments, and using Cloudflare's tools for monitoring and management.
Neeraj Dhiman ·
Infra
AI Agents Need a Sandbox Before They Touch Code
As AI agents increasingly write code, the key challenge is trust. For cloud-native apps, this means verifying an agent's work in a live runtime environment before it ever becomes a pull request, ensuring the code is safe and effective.
Ashish Kale ·
Frequently asked questions
What's the difference between an agent and a chatbot?
A chatbot answers questions; an agent takes actions. Agents plan multi-step workflows, call tools (APIs, code execution, file systems), observe results, and self-correct. The line is fuzzy at the edges but production-grade agents handle real tasks like "reconcile this invoice batch" or "triage these support tickets".
What are the main AI agent frameworks in 2026?
Anthropic Claude's Computer Use, OpenAI's Agents SDK, LangGraph, AutoGen, CrewAI, and DSPy. The open-source frameworks compete on workflow expressivity; the vendor frameworks compete on tool-use reliability. Most production teams settle on one of the two vendor stacks for reliability reasons.
Where do AI agents fail in production?
Three places: brittleness on the long tail (rare inputs the model hasn't seen), unbounded cost (loops that don't terminate), and silent wrong answers (agent confidently completes the wrong task). Reliability practices — human checkpoints, budget caps, evaluator agents — are how teams mitigate.