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Syllabus
LDB-001 · LLM Fundamentals in Python
Kickstart your repo and ship a minimal tech-support assistant using pure Python and the OpenAI SDK (no third-party libs). Understand tokenization, context windows, and how cost/latency affect quality.
You’ll build: a CLI/web script that answers support questions and preserves short conversational context.
LDB-002 · Prompt Engineering
Design prompts that clarify, summarize, and adapt to user preferences. Add lightweight telemetry to track token usage and spot regressions.
You’ll build: reusable system/user prompt templates + a small “prompt budget” dashboard.
LDB-003 · Retrieval-Augmented Generation (RAG)
Ground answers in your own documents and fail gracefully with fallbacks and “I don’t know (but here’s what to try)” patterns.
You’ll build: a simple RAG pipeline (ingest → chunk → embed → retrieve) and an eval script to compare answer quality.
LDB-004 · Guardrails for LLM Apps
Align behavior with business rules, safety, and compliance. Filter risky queries, enforce tone/policy, and log moderation events.
You’ll build: a guardrail layer (policy checks + moderation hooks) that runs before/after model calls.
LDB-005 · From Assistant to Agent
Go beyond chat: add actions and escalation. Trigger webhooks, post to Slack, and hand off to humans when confidence is low—prioritizing critical cases.
You’ll build: Slack alerts + webhook actions with a scoring system that routes issues faster.
LDB-006 · Tool Use with Reasoning Loops & MCP
Implement plan-act-observe loops so your assistant can call tools, analyze results, and iterate toward a solution. Use Model Context Protocol (MCP) to register tools via a common interface.
You’ll build: a reasoning loop that chains multiple tool calls and an MCP tool registry your agent can query at runtime.
By the end, you’ll have
- A working agent repo (prompts, RAG, guardrails, tools, evals).
- Ops basics: cost/latency tracking, safety logs, and smoke tests.
- Integrations: Slack + webhook-based actions you can extend.
- A shareable demo and README for your portfolio.
About TechEmpower
TechEmpower is a software consulting and development firm in Los Angeles. For more than 25 years, we’ve built platforms and products for startups, nonprofits, and enterprises. Today, we focus on bringing AI into real-world development, helping developers build the skills to innovate with impact.
