From Starter to Production: Where to Go Next
What this small LangGraph starter leaves out, a concrete list of next steps, and what I learned and would do differently.
4 min read
Writing
Notes from building AI systems, Python services and the tooling around them.
AI & Machine Learning
Field Log: What Went Wrong and How I Fixed It
Every failure from building a local LangGraph agent: a stale ChromeDriver that made the model say a site was down, invented dates, and more.
10 min read
Making the Terminal Usable
Replace pretty_print with a compact streaming display and silence noisy MCP server logs with a small wrapper, without touching the servers.
8 min read
Persistent Memory with SQLite, and Trimming What the Model Sees
Swap LangGraph's in-memory checkpointer for SQLite so a local agent remembers across restarts, then trim old tool results so a 7B model keeps up.
9 min read
Human Approval Before Write Tools with interrupt()
Pause a LangGraph agent before it writes files: interrupt(), Command(resume=...), a real approve and deny run, and the bugs I hit along the way.
12 min read
Testing the Router with a Small Eval
A 21-case eval for a small-model router: how it works, what a 100% score does and does not prove, and a sanity check that shows it can fail.
10 min read
Routing: One Agent per Tool Group
Add a router node and one agent per tool group in LangGraph so a 7B model sees only the tools it needs. Covers conditional edges and what still goes wrong.
10 min read
From Prebuilt Agent to a Hand-Built StateGraph
Rebuild the prebuilt create_agent loop with LangGraph's StateGraph: state, reducer, nodes, edges, ToolNode, a checkpointer, and what the prebuilt hid.
8 min read
Why Your Small Model Picks the Wrong Tool
A 7B model with many tools invents dates, miscounts and misreports errors. What I cut, what the system prompt says line by line, and what stayed broken.
10 min read
A Local Tool-Using Agent in About 100 Lines
Wire a 7B model in LM Studio to three MCP servers with LangChain's create_agent, and read the tool calls it makes on a real run.
9 min read
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...
5 min read
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...
9 min read
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...
11 min read
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...
13 min read
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...
15 min read
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...
4 min read
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.
4 min read
Scenario: Developer Productivity with Claude
Applying Claude Code to developer workflows: iterative refinement, context management in large codebases, and team-scoped configuration patterns.
4 min read
Scenario: Multi-Agent Research System
Design a coordinator-subagent research pipeline with parallel execution, structured output, error propagation, and provenance tracking across sources.
4 min read
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.
3 min read
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,...
3 min read
Domain 5: Context Management & Reliability (15%)
Managing conversation context across long interactions, error propagation in multi-agent systems, human review workflows, and provenance tracking during synthesis.
10 min read
Domain 2: Tool Design & MCP Integration (18%)
Designing effective tool interfaces, structured error responses, tool distribution across agents, MCP server configuration, and built-in Claude Code tools.
9 min read
Domain 4: Prompt Engineering & Structured Output (20%)
JSON schema design, tool_use and tool_choice, few-shot examples, validation-retry loops, and multi-pass review architectures for the CCA exam.
9 min read
Domain 3: Claude Code Configuration & Workflows (20%)
Complete coverage of CLAUDE.md hierarchies, .claude/rules/ glob patterns, slash commands, skills, plan mode, CI/CD integration, and the Batch API.
9 min read
Domain 1: Agentic Architecture & Orchestration (27%)
The largest CCA exam domain. Master agentic loops, multi-agent coordination, subagent configuration, workflow enforcement, SDK hooks, task decomposition,...
12 min read
CCA Exam Reference: Technologies & Core Themes
A high-level meta-reference covering all core technologies tested on the CCA exam — Agent SDK, MCP, Claude Code CLI, and key cross-domain themes.
2 min read
Study Dashboard & Exam Overview
Your starting point for the CCA Foundations exam: domain weights, scenario overview, study strategy, and progress tracker.
3 min read
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