Agent Engineering
The core of modern AI engineering. Build agents from first principles.
Цена: 5 896 ₽
Длительность: 43 ч
Автор: John Jackson
Программа курса
- The Agent Loop: Observe, Think, Act
- ReWOO and Plan-and-Execute: Decoupled Planning
- Reflexion: Verbal Reinforcement Learning
- Tree of Thoughts and LATS: Deliberate Search
- Self-Refine and CRITIC: Iterative Output Improvement
- Tool Use and Function Calling
- Agent Memory — Virtual Context and Memory Paging
- Memory Blocks and Sleep-Time Compute
- Hybrid Memory: Vector + Graph + KV
- Skill Libraries and Lifelong Learning (Voyager)
- Planning with HTN and Evolutionary Search
- Anthropic's Workflow Patterns: Simple Over Complex
- Stateful Graph Orchestration — Durable Execution and Checkpoints
- The Actor Model for Agents — Async Messages and Typed Runtimes
- Role-Based Agent Teams — Roles, Tasks, Processes
- OpenAI Agents SDK: Handoffs, Guardrails, Tracing
- The Harness as a Library — Subagents and Session Store
- Production Agent Runtimes — Fast Instantiation and Typed Workflows
- Benchmarks: SWE-bench, GAIA, AgentBench
- Benchmarks: WebArena and OSWorld
- Computer Use: Claude, OpenAI CUA, Gemini
- Voice Agents: Pipecat and LiveKit
- OpenTelemetry GenAI Semantic Conventions
- Agent Observability: Langfuse, Phoenix, Opik
- Multi-Agent Debate and Collaboration
- Failure Modes: Why Agents Break
- Prompt Injection and the PVE Defense
- Orchestration Patterns: Supervisor, Swarm, Hierarchical
- Production Runtimes: Queue, Event, Cron
- Eval-Driven Agent Development
- Agent Workbench Engineering: Why Capable Models Still Fail
- The Minimal Agent Workbench
- Agent Instructions as Executable Constraints
- Repo Memory and Durable State
- Initialization Scripts for Agents
- Scope Contracts and Task Boundaries
- Runtime Feedback Loops
- Verification Gates
- Reviewer Agent: Separate Builder from Marker
- Multi-Session Handoff
- The Workbench on a Real Repo
- Capstone: Ship a Reusable Agent Workbench Pack
- Frame the Task Before the Agent Writes Code
- Build an Evidence-Backed Execution Plan
- Delegate Agent Work with Isolation and Merge Contracts
- Turn Every Agent Correction into a System Improvement
- Define the Outcome Before You Choose the Output
- Discover the Workflow People Actually Perform
- Map Assumptions and Resolve the Riskiest One First
- Choose the Smallest Slice That Can Change the Decision
- Write Specifications That Preserve Judgment
- Design Success Metrics Before the Result Exists
- Choose Prototype, Pilot, or Production Deliberately
- Build a Feedback Ratchet with Ownership and Retirement
- Итоговое задание