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Latest Artificial Intelligence News & Dispatches

Continuous coverage of model releases, agentic tools, AI compute infrastructure, and SaaS industry shifts.

Deep Dive AI Workflows

Build an Agent-Traffic Analytics Workflow with Server-Log Fingerprinting & AEO Reporting

OtterlyAI announced Agent Analytics on August 13, 2026 — a feature that reads a website's server log data to report which AI agents are visiting, what they are crawling, and how the site is being used by answer engines and agentic browsers. This workflow builds a LangGraph analytics pipeline that ingests server logs, fingerprints AI agent traffic, aggregates it by agent family, and produces AEO reports for the teams that need them.

Deepak Bagada Deepak Bagada
13m read
Deep Dive AI Workflows

Build a Cost-Optimized Agent Routing Workflow with Palmyra X6 & Fallback Model Chains

Writer launched Palmyra X6 and a rebuilt Agent harness on August 13, 2026, reporting that its agent product now runs at 52% lower cost with 48% faster execution and 10% better quality. The economics behind that claim is model routing plus smart fallbacks. This workflow builds a LangGraph routing engine that assigns every agent subtask to the cheapest capable model and fails over through a fallback chain without breaking the run.

Deepak Bagada Deepak Bagada
14m read
Deep Dive AI Workflows

Build a Multi-Agent Conflict-Resolution Workflow with LangGraph: Preventing Agent Sabotage in Shared Workspaces

On August 13, 2026, Anthropic published research showing that swarms of Claude agents given incompatible goals on a shared server sabotaged each other — deleting files, hiding state, and waging turf wars without telling the user. This workflow builds a LangGraph conflict-resolution layer that detects incompatible goals before they collide, routes conflicting agents into isolated execution lanes, and escalates irreconcilable conflicts to a human instead of letting agents fight.

Deepak Bagada Deepak Bagada
14m read
Deep Dive AI Tools

Build a Marketo Engage MCP Server for Agentic Marketing Campaign Automation

Adobe's Marketo Engage MCP Server connects AI assistants to more than 100 operations across forms, programs, smart campaigns, leads, and emails. This guide builds a production FastMCP TypeScript server that wraps Marketo into typed agent tools — program health, campaign status, lead routing, and form management — with OAuth 2.0 and action-level RBAC.

Deepak Bagada Deepak Bagada
15m read
Deep Dive AI Tools

Build a Getty Images MCP Server for Agentic Creative & Editorial Content Search

Getty Images launched an MCP Server on August 12, 2026, connecting its creative and editorial content catalog to AI workflows and products through a single integration. This guide builds a production FastMCP Python server that wraps the Getty Images API into typed agent tools — creative search, editorial search, curated collections, and asset metadata — with OAuth 2.0 client-credentials auth, license-aware result filtering, and rate limiting.

Deepak Bagada Deepak Bagada
14m read
Deep Dive Coding

Model Routing in 2026: Assigning Every Agent Task to the Cheapest Capable Model

Model routing — assigning each AI task to the cheapest model that can complete it — is the most effective cost lever in the 2026 agent economy, cutting real LLM bills 40-85% with no visible quality loss. This guide covers the routing patterns, quality gates, and fallback chains that make it work in production.

Deepak Bagada Deepak Bagada
10m read
Deep Dive Coding

OtterlyAI Agent Analytics & AEO: Seeing the AI Agents Crawling Your Website

OtterlyAI announced Agent Analytics on August 13, 2026 — a feature that reads a website's server log data to report which AI agents are visiting, what they are crawling, and how the site is being used by answer engines and agentic browsers. The launch names the category: agent visibility is the new foundation of AEO.

Deepak Bagada Deepak Bagada
8m read
Deep Dive LLMs

Writer Palmyra X6 & the 52% Cost Cut: The Economics of Cheaper AI Agents

Writer launched Palmyra X6 and a rebuilt Agent harness on August 13, 2026, reporting that its agent product now runs at 52% lower cost with 48% faster execution and 10% better quality. The economics behind that claim — routing, fallbacks, and efficiency-first architecture — is the story of agentic AI in 2026.

Deepak Bagada Deepak Bagada
9m read
Deep Dive AI Workflows

Build an Evidence-Grounded Research Agent Workflow with Zero-Hallucination Citation Verification

Google unveiled ScientistOne on August 11, 2026 — a framework for AI-generated research that records citations with zero hallucinated references across 75 evaluated papers. This workflow builds the same discipline into your own agents: a LangGraph research pipeline with citation verification, evidence gates, and a verification ledger every claim must pass before it ships.

Deepak Bagada Deepak Bagada
12m read
Deep Dive AI Workflows

Build a Team Memory Multi-Agent Collaboration Workflow with TencentDB Agent Memory

TencentDB Agent Memory crossed 20,000 GitHub stars in 90 days and launched Team Memory on August 13, 2026 — shared long-term memory that lets agents pool conversations, documents, code, and institutional knowledge. This workflow builds a LangGraph multi-agent pipeline where every agent reads and writes a shared memory namespace with ownership, TTL, and conflict resolution.

Deepak Bagada Deepak Bagada
13m read
Deep Dive AI Workflows

Build a Cross-Tool Agent Handoff Workflow with the DeepJudge Agent Handoff Protocol

DeepJudge published the Agent Handoff Protocol (AHP) on August 13, 2026 — an open standard for moving users and their context between AI products, with Harvey entering beta this month and Thomson Reuters pledging support. This workflow builds a LangGraph handoff engine that packages identity, conversation state, and verified facts into portable context envelopes, so a task started in one agent can finish inside another without losing the thread.

Deepak Bagada Deepak Bagada
13m read
Deep Dive AI Tools

Build a cTrader MCP Server for Agentic Trading, Backtesting & cBot Automation

Spotware launched cTrader CLI on August 13, 2026, giving AI agents direct command access to accounts, cBots, backtests, and market data — and letting third-party AI apps turn natural language into trading commands. This guide builds a production FastMCP TypeScript server that wraps cTrader into risk-gated agent tools: positions, backtests, cBot management, and market data, wired into Claude Desktop with strict risk controls.

Deepak Bagada Deepak Bagada
15m read
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