The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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235 articles · Page 12 of 20

Fine-Tune a 7B Model for $1,500 (Not $50,000)
Full fine-tuning costs $50K in H100s. QLoRA on an RTX 4090 costs $1,500. Learn how LoRA and QLoRA let you train only 0.1-1% of parameters with nearly identical results, with working code for fine-tuning models that understand your agent's tool schemas.

The AI Agent Dashboard of 2026: What Teams Actually Need to See
Traditional dashboards tell you what went wrong yesterday. The AI agent dashboards teams actually need deliver feedback in the moment, during the call, not after it. Here's what that looks like in practice.

The Three Protocols Every AI Agent Will Speak
The AI agent protocol stack has three layers: MCP for tools, A2A for agent-to-agent communication, and WebMCP for browser interaction. A practitioner's guide to how they work together in production.

A 1B Model Just Matched the 70B. Here's How.
How to distill frontier LLMs into small, cheap models that retain 98% accuracy on agent tasks. The teacher-student pattern, NVIDIA's data flywheel, and the Plan-and-Execute architecture that cuts agent costs by 90%.

The Multi-Agent Pattern That Actually Works in Production
Gartner reports a 1,445% surge in multi-agent system inquiries. Here are the orchestration patterns that actually work when real customers call -- and why most teams pick the wrong one.

Stop Reacting to Bad Calls. Catch Problems Before Customers Do
By the time a customer complains, you've already lost. Real-time analytics lets AI agent teams catch failing conversations mid-flight, not in the post-mortem. Here's how to build a proactive monitoring stack that prevents pain instead of documenting it.

Your AI Agent Has No Guardrails
Air Canada honored a refund its chatbot hallucinated. DPD's bot cursed at customers on camera. One e-commerce agent approved $2.3M in unauthorized refunds at 2:47 AM. Here is the five-layer guardrail architecture that prevents all three.

Every Tool Is an Injection Surface
Prompt injection moved from chat to tool calls. Anthropic, OpenAI, and Arcjet shipped defenses in the same month. Here's what changed, what works, and what your agent architecture needs now.

Why Your AI Bill Is 30x Too High
Small language models match GPT-3.5 at 2% of the size and 95% less cost. Benchmarks, code, and a migration story from $13K/month to $400.

Your AI Agent Costs $13K/Month. Here's the Fix.
A production customer-service agent burned $13,247 in one month. Prompt caching, model routing, batch processing, and plan-and-execute architecture cut it to $1,100. Real pricing math for every technique.

Why Browser Agents Waste 89% of Their Tokens
Browser agents burn 1,500-2,000 tokens per screenshot. Chrome 146's navigator.modelContext API lets websites expose structured tools instead, cutting token usage by 89% and raising task accuracy to 98%. Here's how WebMCP works.

Part 1: Claude's 7 Extension Points — The Mental Model
CLAUDE.md, Skills, Hooks, MCP Servers, Connectors, Claude Apps, Plugins — Claude's extension ecosystem is powerful but confusing. Here's the mental model that makes sense of all 7.
Learn Agentic AI
Weekly. Patterns for shipping agents that work — MCP, scorecards, regression tests, prompts, model comparisons.