My Claude Journey
Shachaf Aviv
0
My Claude Journey is a course-style podcast about understanding and working effectively with Anthropic's Claude. Each short episode covers one core lesson, explaining concepts such as AI context windows, prompt design, tool usage, and common failure modes. The show turns complex technical ideas into practical habits for real-world use. It is aimed at builders, analysts, developers, and power users who want to get more done with Claude.
Epizode
-
Episode 10: Digital Workspaces 14.10.2026 22minHow do Claude Projects turn reference files and standing instructions into custom AI workspaces? In this episode, we examine how project knowledge reaches a chat—comparing full context loading in small projects against RAG semantic search in massive document libraries. We cover project instructions, isolated memory spaces, and the trade-offs of uploading file copies versus linking local desktop folders. -
Episode 9: System Steering 14.10.2026 21minhere should you place your AI instructions so they actually stick? In this episode, we evaluate the different instruction surfaces—from account-wide settings and project instructions to CLAUDE.md files and single-chat prompts. Learn how to run the sorting test to determine where rules belong, write instructions that are specific, short, and testable, and resolve conflicting guidelines across layers. -
Episode 8: Precision Prompting 14.10.2026 23minStop getting generic AI responses by mastering the core components of effective prompting. This episode walks you through rebuilding weak prompts piece by piece using four key elements: Goal, Context, Limits, and Output Shape. Learn how to leverage concrete examples, XML tags, and document ordering to guide Claude's focus. We also cover constructive feedback loops, editing messages versus branching, and knowing when to start fresh with a handoff note. -
Episode 7: Failure Modes 14.10.2026 22minWhy do AI models hallucinate, drift, or produce generic answers? In this episode, we analyze the 9 distinct failure modes—including fabrications, invented citations, confident approximations, stale knowledge, instruction decay, sycophantic drift, and averaging. We explain why text prediction creates plausible errors and share practical verification habits, such as demanding exact source quotes, testing across fresh chats, and running pushback tests without new evidence. -
Episode 6: Costs & Control 14.10.2026 21minHow do Pro subscription limits work, and why do long chats drain your allowance so quickly? This episode demystifies Claude's resource management, covering 5-hour session limits, weekly usage caps, and pay-as-you-go usage credits. We break down per-token API pricing—explaining why output tokens cost five times as much as input tokens and how prompt caching saves money. Plus, gain actionable habits to split long tasks and stretch your compute budget. -
Episode 5: Tiers & Reasoning 14.10.2026 20minHow do you choose the right model tier for a complex job? In this episode, we compare Claude's model family—from lightweight Haiku to Sonnet, Opus, and Fable. We explore adaptive thinking, showing how forcing the model to write out its internal step-by-step reasoning catches multi-step traps and logic errors. Discover how to adjust effort levels (from Low to Max) in both the app and Claude Code to strike the perfect balance between reasoning depth, speed, and token usage. -
Episode 4: External Reach 14.10.2026 21minHow does Claude step outside its fixed training data to interact with the world? In this episode, we trace the step-by-step tool loop—the ask, act, return cycle that lets Claude search the live web, read pages, and manipulate local files. We examine the fixed knowledge cutoff date and explain why stale training facts sound just as confident as fresh ones. Finally, learn how to enforce exact quotes, verify citations, and write standing rules that ensure online searches remain accurate. -
Episode 3: Layers of Context 14.10.2026 28minWhen you type a simple message, Claude reads far more than just your text. This episode dissects the hidden prompt stack built into every turn—from Anthropic's system prompts and tool descriptions to account preferences, project instructions, memory, and tool results. Learn how prompt caching significantly cuts processing costs for unchanged setup layers. We also explore instruction decay, explaining why certain guidelines fade over time and which layers automatically reload after a long chat is summarised. -
Episode 2: Tokens & Context Windows 14.10.2026 19minHow do AI models measure text, and why do long chats start losing quality? In this episode, we unpack the mechanics of tokens and context windows—the foundational units behind AI memory, platform limits, and usage costs. We explore why Claude forgets everything between messages and must re-read the entire conversation history on every single turn. Discover why long conversations suffer from "context rot", how automatic compaction works when limits are reached, and how handoff notes can preserve your usage allowance. -
Episode 1: The Landscape 14.10.2026 19minWhat is the difference between "Claude" the AI model and the software products built around it? In this debut episode, we break down how the same underlying model runs across various surfaces—from web and desktop apps to Claude Code, browser extensions, and Microsoft Office add-ins. We examine the three levers that define every AI surface: tools, reach, and context. You'll also learn how model tiers work, how subscription allowances function across surfaces, and where each topic sits on our 23-lesson course map.
Popularan u
Ovaj podcast se pojavljuje i u podcast listama ovih zemalja.