E81: Build Better AI Agents (Part 2): The Five Building Blocks of Context Engineering

After learning why AI agents fail in Part 1 (attention budget, context rot, orchestration limits), Malcolm Werchota now reveals how to build scalable, long-running AI systems using Anthropic’s framework for Context Engineering.

This episode goes beyond prompts — it’s about architecture.

Malcolm introduces the five building blocks of Context Engineering:

1️⃣ System Prompts – Define your agent’s identity, purpose, core capabilities, and quality standards.

2️⃣ Minimal Tool Sets – Stop giving 20 tools; focus on what’s essential.

3️⃣ Just-in-Time Retrieval – Only load information when it’s needed, not everything at once.

4️⃣ Long-Horizon Strategies – Extend runtime with compaction, note-taking, and delegation.

5️⃣ Examples & Patterns – Train with diverse examples, anti-patterns, and confidence scoring.

Using practical cases from Werchota.ai — like invoice automation and large-scale feedback analysis — Malcolm demonstrates how these techniques turn fragile “demo agents” into reliable production-grade systems.

Key topics: agent architecture, context optimization, compaction, token management, orchestration patterns, Anthropic Claude Code implementation, and how to scale AI workflows in production environments.

Perfect for professionals working with Claude, GPT-5, or Gemini — and anyone ready to move from prompt engineering to system thinking.

🗒️ SHOW NOTES

Episode 81, Part 2: Build Better AI Agents Through Context Engineering

Malcolm Werchota breaks down the five practical building blocks of Context Engineering, showing how to design scalable AI systems that actually think ahead — not just follow commands.

WHAT YOU’LL LEARN

• The five key building blocks of Context Engineering
• How to write effective system prompts that guide decision-making
• Why fewer tools = better agents
• How to implement Just-in-Time data retrieval
• Extending AI lifespan through compaction and delegation
• Using examples and anti-patterns to improve agent reasoning
• Confidence scoring and note-taking for long-running tasks

KEY TAKEAWAYS

• System Prompts: Define identity, purpose, and quality — short and structured (600–800 tokens).
• Minimal Tool Sets: Reduce decision complexity; fewer, focused tools improve speed and reliability.
• Just-in-Time Retrieval: Load only what’s needed in context; one file or task at a time.
• Long-Horizon Strategies: Use compaction, external note-taking, and delegation to prevent context overload.
• Examples & Patterns: Teach your agents from both successes and failures — diversity beats volume.

REAL-WORLD USE CASES

• Invoice automation using Claude Code orchestration
• Customer feedback summarization (10,000 → 5,000 words)
• Parallel sub-agent processing (reading 10 invoices simultaneously)
• Long-running report generation using compaction & note-taking

TOOLS & PLATFORMS

• Claude Code (Anthropic)
• Claude Sonnet 4.5 (1M-token context window)
• Gemini 2.5 (1M-token context window)
• ChatGPT-5 (200k-token context window)
• Werchota.ai Cloud Dashboard (Episode Notes)

RESOURCES

• Anthropic Research: Effective Context Engineering for AI Agents
• Previous Episode: Build Better AI Agents – Part 1 (Context Engineering Basics)
• Claude Code Documentation
• Werchota.ai Blog: “Context Engineering in Real Workflows”

MALCOLM’S KEY INSIGHTS

“Don’t give your agent 20 tools — it will spend half its energy deciding which one to use.”

“The future of AI isn’t about bigger models. It’s about better architecture and context engineering.”

“System prompts are not messages — they’re thinking frameworks.”

“Context engineering turns fragile demos into production systems.”

🔗 WHERE TO FIND MALCOLM WERCHOTA

LinkedIn → linkedin.com/in/malcolmwerchota

Website → werchota.ai

YouTube → youtube.com/@werchota

X → x.com/malcolmwerchota

Facebook → AI Cookbook by Malcolm Werchota

Instagram → @malcolmwerchotaai

TikTok → @malcolmwerchota

📧 Get in touch:

Questions, feedback, or transformation stories → malcolm@werchota.ai

Episode ideas → social@werchota.ai

🎓 Upgrade your AI skills:

Join the AI Fit Academy — Malcolm’s hands-on program that helps professionals and teams ship real AI workflows by Week 2 — or your money back.

Learn more → werchota.ai/ai-fit-academy