Claude Haiku 5.5: Cheap, Fast AI Agents in Python

Claude Haiku 5.5: Cheap, Fast AI Agents in Python – taught by José Calderón – is a practical Udemy training that shows how to build cost‑efficient AI agents with Anthropic’s latest Claude Haiku 5.5 model. The free Claude Haiku 5.5 course targets developers who need to learn Claude Haiku 5.5 online, reduce token spend, and deliver reliable support pipelines. Updated July 2026, the curriculum covers model routing, prompt caching, and real‑world cost estimation, delivering hands‑on Python code and a downloadable project. Students finish with concrete skills that translate directly into production AI services and a Udemy certificate of completion.

What You'll Learn

• Build end‑to‑end AI support back‑ends using Claude Haiku 5.5 and Opus orchestration in Python.
• Master cost‑cutting techniques such as prompt caching, the Batch API, and token‑price step management.
• Learn how to route work between Claude Haiku and Opus models based on effort and quality requirements.
• Understand the new effort and thinking settings introduced in Claude Haiku 5.5 and their impact on performance.
• Create regression test suites that validate AI output against the real Claude API.
• Implement monthly cost estimation formulas that predict AI feature spend from measured task metrics.
• Apply model‑selection strategies to decide when a smaller Claude Haiku model suffices for a given task.
• Analyze real‑world ticket‑triage data to compare accuracy and cost between Haiku and Opus models.

Course Details

• Instructor: José Calderón
• Rating: 4.6 stars (77 reviews)
• Language: English (en‑US)
• Enrolled students: 77

What This Course Covers

1. Claude Haiku 5.5 Fundamentals

• Overview of the October 2026 release, including ten‑cent‑per‑million‑token pricing and 1 M‑token context window.
• Detailed comparison of Haiku 5.5 versus Haiku 4.5, highlighting temperature, prefill, and thinking‑budget changes.
• Explanation of the new effort setting and how it influences model “thinking” time.
• Real‑world examples of classifying, routing, extracting, and summarizing high‑volume text.

2. Cost‑Optimization Strategies

• Prompt caching techniques that reuse embeddings and reduce repeated token consumption.
• Using the Batch API to submit multiple requests in a single call, lowering per‑request overhead.
• Monitoring the 100 K‑token price step and its effect on overall spend.
• Building a ledger that records model name, token count, latency, and cost for every API call.

3. Model Routing and Sub‑agents

• Designing a routing layer that decides whether Haiku or Opus handles a given task.
• Implementing Haiku sub‑agents that operate under an Opus orchestrator for complex cases.
• Configuring effort and thinking budgets per sub‑agent to balance speed and accuracy.
• Testing routing decisions with labeled support tickets to ensure quality thresholds.

4. Regression Testing Against the Real API

• Setting up automated tests that compare model output to expected results stored in a test suite.
• Measuring accuracy, latency, and cost for each test run to detect regressions early.
• Using Python’s unittest framework to integrate tests into continuous‑integration pipelines.
• Interpreting test metrics to refine prompts, caching policies, and routing rules.

5. Real‑World Project: CostCutter Backend

• Building the CostCutter support backend for the fictional PhotoShare app.
• Triaging tickets with Haiku, drafting routine replies, and summarizing weekly activity.
• Delegating hard‑case tickets to Claude Opus 5.5 for expert handling.
• Analyzing the final cost report, which shows Haiku achieving Opus‑level accuracy at 1/29 the expense.

Who Should Take This Course

• Python developers who integrate the Claude API and need to lower AI operational costs.
• Teams building high‑throughput support, triage, or document‑processing pipelines that handle large text volumes.
• AI engineers looking to decide when a small model is sufficient and how to prove its adequacy.
• Data scientists interested in cost‑aware model selection for production‑grade AI services.
• Developers transitioning from prototype work to scalable, cost‑controlled AI deployments.

Prerequisites

• Proficiency in Python programming and familiarity with basic HTTP requests.
• Access to an Anthropic Claude API key (free trial keys are acceptable).
• Recommended: prior experience with RESTful APIs and JSON data handling.

Why Enroll in This Course

The course delivers a free coupon that unlocks 100 % off the Udemy price for a limited time, making high‑quality AI training accessible without financial risk. Because the material is recorded in July 2026, every demonstration reflects the latest Claude Haiku 5.5 features and pricing structure. Compared with generic AI tutorials, this training provides measurable cost‑saving formulas, real‑world project files, and a complete regression test suite, ensuring learners can immediately apply skills in production environments.

Course Highlights

• Lifetime access to all video lessons, code examples, and downloadable project assets.
• Self‑paced learning that lets you progress through modules at your own speed.
• Certificate of completion that validates your expertise in Claude Haiku cost optimization.
• Practical, hands‑on project (CostCutter) that mirrors real‑world AI support workflows.
• Mobile‑friendly video player enables learning on tablets or smartphones.
• Comprehensive test suite teaches best practices for regression testing against live AI APIs.

Frequently Asked Questions

Q: Is this course really free?
A: Yes, the Udemy offering includes a free coupon that reduces the enrollment price to $0 for a limited period. The coupon applies automatically at checkout, granting full access to all course materials without any hidden fees.

Q: What will I learn in this Claude Haiku 5.5 course?
A: You will learn how to build AI agents with Claude Haiku 5.5, implement cost‑saving strategies like prompt caching, route tasks between Haiku and Opus, and create regression tests that validate model performance against the real API. The curriculum also covers monthly cost estimation and real‑world project construction.

**Q: Do I get a certificate after completing this course