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Building Python Flask Web Apps That Last
A personal reflection on building Flask applications that are maintainable, secure, and enjoyable to work with over time.
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Three Agentic Patterns Every Python Developer Should Have in Their Back Pocket
"AI agent" has become one of those phrases that means everything and nothing. Marketing decks throw it at every LLM that calls a function. Vendor pages promise autonomous workforces. Meanwhile, the de...
AI and Job Risks in London
A fifth of London's jobs face significant AI exposure according to a Greater London Authority report by economist Jeff Dwan-O'Reilly. The numbers deserve more scrutiny than the headline — and the 54% ...
AI Security & Chips: OpenClaw's Flaw and a US First
Two of the most consequential AI infrastructure stories of April 2026: Resonac formally opened the first US center dedicated to advanced semiconductor packaging in Union City, CA — while open-source a...
Key Concepts & Glossary
Quick-reference guide to all major technologies and concepts on the CCA exam: Agent SDK, MCP, Claude Code, Claude API, Message Batches API, JSON Schema, and built-in tools.
Hands-On Preparation Exercises
Four hands-on labs mapping to CCA exam domains: build a multi-tool agent, configure Claude Code for a team, implement a structured extraction pipeline, and design a multi-agent research system.
Sample Questions & Distractor Analysis
12 worked exam questions with full distractor analysis. Each question covers a realistic production scenario with correct answer explanation and analysis of why each wrong answer fails.
Scenario: Structured Data Extraction
Build a reliable data extraction pipeline with JSON schema design, validation-retry loops, few-shot examples for varied document formats, and confidence-based human review routing.
Scenario: Claude Code for Continuous Integration
Integrating Claude Code into CI/CD pipelines using non-interactive mode, JSON output formatting, and the Batch API for cost-optimized asynchronous review.
Scenario: Developer Productivity with Claude
Applying Claude Code to developer workflows: iterative refinement, context management in large codebases, and team-scoped configuration patterns.
Scenario: Multi-Agent Research System
Design a coordinator-subagent research pipeline with parallel execution, structured output, error propagation, and provenance tracking across sources.
Scenario: Code Generation with Claude Code
Using Claude Code for code generation workflows: plan mode for complex refactors, CLAUDE.md hierarchies, and slash commands for team automation.
Scenario: Customer Support Resolution Agent
Build a customer support agent with get_customer, lookup_order, process_refund, and escalate_to_human tools. Covers prerequisite gates, escalation criteria, and structured handoff protocols.
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