AI Agents articles
100 articles about AI Agents, newest first.
- Zapier Next Gen Zaps: Combining Deterministic and Agentic AI — Learn how Zapier Next Gen Zaps solve AI reliability and token waste by mixing 'hardened' deterministic automation with probabilistic agentic decision-making.
- Rebuilding Food Systems: Automating Pasture Rotation with AI Agents — Cody Menefee explains how to use LLMs, Firecrawl, and GPS collars to automate rotational grazing and move livestock from feedlots back to pastures.
- Scheduling Managed Deep Agents with LangChain and LangSmith — Learn how to use cron syntax to automate recurring AI tasks and deliver proactive reports to Slack using LangChain's Managed Deep Agents and LangSmith.
- Document Intelligence: Building Robust AI Agents with Reducto — Learn how Adit Abraham of Reducto optimizes PDF parsing and document intelligence to stop compounding errors in multi-step AI agent pipelines.
- Salesforce Agentforce: The Shift to an Agent-First CRM — Explore how Salesforce Agentforce is redefining the CRM experience by allowing AI agents to execute tasks, reducing the need for manual app navigation.
- Building Agent Harnesses with Jev and TypeSafe AI — Learn how Jev, a System 1 decision model from TypeSafe AI, replaces heavy LLM calls for classification and routing in LangChain agent harnesses.
- Verified Graphs: Why AI Agent Swarms Fail in Science — Learn why natural language is a 'lossy channel' for AI agents and how neuro-symbolic auditing with deterministic solvers can fix multi-agent reasoning failures.
- OpenAI's Codex and the Rise of the AI-Native Workplace — Learn how OpenAI uses 'computer use,' ChatGPT Sites, and proactive agents to shift work from manual tasks to high-level human judgment and orchestration.
- Instinct vs GrokBot vs Muse: Which AI Agent Actually Works? — A head-to-head comparison of Instinct, GrokBot, and Muse AI agents, testing real-world tasks like Airbnb searches, browser control, and agent coordination.
- Automating Outbound Sales with GrokBot Voice AI Agents — Learn how GrokBot uses voice AI to qualify E2 visa leads and book meetings, generating $16,000 in revenue within its first two weeks of operation.
- How Unify Applies Self-Driving Eval Logic to AI Agents — Connor Heggie explains why manual review of real-world examples is the only way to truly trust an AI model before deploying it to production.
- Building an AI Voice Sales Agent with GrokBot and ElevenLabs — Learn how to build an automated AI voice agent that qualifies leads and books calls using GrokBot, ElevenLabs, Twilio, and Attio to drive revenue.
- Building Custom AI Agents with the Hermes Agent Harness — Learn how to build personalized AI agents like Tacobot and Lifebot using the Hermes agent harness to automate workflows and track personal productivity.
- From Chatbots to Agents: Exploring Modaal, Claude, and ElevenLabs — Learn how new AI tools like Modaal, Claude Slides, and ElevenLabs Reception are shifting AI from simple chat interfaces to autonomous, agentic actions.
- Measuring AI Agent Success: Clay's Quality, Throughput, and Cost Framework — Learn how Clay evaluates AI agents using a mix of deterministic matching, factual evals, and LLM-as-a-judge to balance quality, speed, and cost.
- Understanding AI Agent Memory: Short-Term vs Long-Term — Learn how AI agents use context windows for short-term memory and external storage for long-term memory to maintain continuity across multiple runs.
- ScienceBuddy and the Rise of Self-Improving Scientific AI Agents — Learn how PhAI Labs' ScienceBuddy uses recursive self-improvement and GRPO to boost scientific AI accuracy from 42.2% to 73.3% across complex research tasks.
- How Stripe is Building Infrastructure for Agentic Commerce — Explore how AI agents are becoming a new class of customers and why Stripe is developing the payment infrastructure needed to handle agentic transactions.
- Agentic Engineering with Browser Use and GPT-6 Astra — Explore how Magnus, CEO of Browser Use, leverages GPT-6 Astra and the Director framework to scale AI agents and eliminate human operational bottlenecks.
- Controlling AI Agents with LangChain Managed Deep Agents Middleware — Learn how to use LangChain's middleware for Managed Deep Agents to implement PII redaction, custom logging, and policy enforcement for secure AI agents.
- Modular AI Skills: How Vercel and Anthropic are Upgrading Agents — Explore the top 10 AI skills from GitHub, including tools from Vercel and Anthropic that transform LLMs from simple chatbots into specialized agents.
- Building Complex AI Systems with LangChain Deep Agents — Learn how LangChain's Deep Agents harness provides a secure, portable framework for building complex AI agents with sandboxing and human-in-the-loop gating.
- Exa and the Rise of the Agentic Web Search Engine — Learn how Exa is building a programmatic search engine designed for AI agents rather than humans, solving the retrieval problem for the next era of AI.
- Why Coding Agents Are Not the Blueprint for Knowledge Work — Explore Benjamin Clavié's argument on why coding agents succeed while general knowledge agents struggle, and how 'searcher agents' can bridge the gap.
- Lyft Boosts Agent Resolution by 16% with LangGraph and LangSmith — Learn how Lyft used LangGraph's meta-agent architecture and LangSmith's observability to cut agent build time from six months to two weeks.
- Building AI Agents with LangChain: Deep Agents and Agent Builder — Learn how to build AI agents using LangChain's Deep Agents for developers and Agent Builder for no-code users, plus how to monitor them with LangSmith.
- Deploying LangChain Managed Deep Agents to Slack — Learn how to move AI agents from LangSmith Studio to production using Slack as the interaction layer for team collaboration and live monitoring.
- Why Oracle's Kay Malcolm Says Your AI Agent Needs a Unified Database — Learn why fragmented databases kill AI productivity and how Kay Malcolm's anatomical approach to AI memory can turn individual speed into team success.
- Anthropic's Strategy for Giving LLM Tokens Specific Jobs — Learn how Anthropic's Katelyn Lesse and Angela Jiang optimize agent performance by assigning tokens to roles like advising, grading, and dreaming.
- Integrating Clay AI Agents with LangSmith and Vercel AI SDK — Learn how Clay used the Vercel AI SDK and LangSmith to achieve one-line observability, cost tracking, and Snowflake data exports for their AI agents.