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Free AI literacy for everyday users. Bite-size narrated lessons that turn fear into fluency, one topic at a time.
Unknown Host hosts Clawdemy Lessons.
The two anxieties of the first week with Clawless. CostGuard is the spending safety net that watches your BYOK usage against a monthly cap. The data path is your computer, the AI provider, your computer, with no Clawless
Show notesHow Clawless connects to AI providers. What an API key actually is, where yours lives once you save it, the BYOK billing model with no Clawless markup, and the OAuth path that lets ChatGPT subscribers skip per-token char
Show notesA tour of the memory system. The distinction between conversation history and memory, the four tiers (Pinned, Insights, General, Decayed), the three pathways memories get in, the Memory panel where you control them, and
Show notesThe first hands-on Clawless lesson. Send your first message, find the model picker in the dock row, switch models mid-conversation without losing your place, and use the provider-prefixed pattern to reach off-list models
Show notesEditorial brief for Lesson 14 of Track 18. The first of two offline-RL lessons. Defines the setting (fixed dataset, no further interaction), names the failure mode (extrapolation error compounded by Bellman propagation),
Show notesEditorial brief for Lesson 15 of Track 18. Second of two offline-RL lessons. Three algorithm families that fix the L14 failure by different mechanisms. Decision rubric for which to pick when. BC sanity check as universal
Show notesLesson 13 of Track 19 (Generative Models and Diffusion). DDPM from L12 sampled in a thousand Markov-chain steps; that is too slow for production. This lesson covers the two moves that made diffusion practical: DDIM (a de
Show notesLesson 15 of Track 19 (Generative Models and Diffusion), the capstone of the track. Returns to the four-paradigm map from lesson 1 with every paradigm's training objective, sampling procedure, and trade-off characterized
Show notesLesson 14 of Track 19 (Generative Models and Diffusion). L11 derived denoising score matching, L12 derived the DDPM Markov chain, L13 derived DDIM, and they all converged on the same noise-prediction loss with the same t
Show notesLesson 9 of Track 23, the track's closing lesson. Hendrycks Ch 8 brings governance as the layer outside any individual AI system. Four-layer taxonomy: corporate, national, international, compute. Each layer with its mech
Show notesOpener of Track 23 (AI Safety and Alignment). Frames AI safety as a field with a subject (catastrophic AI risks), a vocabulary (the four-bucket typology, the specification-vs-proxy-gaming distinctions), a method (descrip
Show notesLesson 7 of Track 23, opener of Phase 3 (ethics and governance). Hendrycks Ch 6 turns from 'what fails' to 'what are we trying to do?' Moral uncertainty as the foundational concept: the field does not have a single corre
Show notesLesson 8 of Track 23. Hendrycks Ch 7 takes the multi-stakeholder framing L7 introduced and works it at the formal level. Game theory as the analytic tool: Nash equilibria that are Pareto inefficient, prisoner's dilemmas.
Show notesLesson 6 of Track 23, the lesson that closes Phase 2. Hendrycks Ch 5 brings in the complex-systems framing: a system assembled from individually-correct components can still produce behavior the designers did not predict
Show notesLesson 2 of Track 23 (AI Safety and Alignment). Takes the four buckets named in L1 and works each in detail: malicious use, AI race, organizational risks, rogue AIs. Each bucket comes with its sub-mechanisms, the histori
Show notesLesson 3 of Track 23 (AI Safety and Alignment), opener of Phase 2. Hendrycks Ch 3.2 + 3.3 split the deployment-time safety surface into two halves. Robustness covers system-side failures (the model breaks under condition
Show notesLesson 5 of Track 23. Hendrycks Ch 4 reaches into safety engineering (the field that grew up around nuclear plants, aviation, chemical processing) and asks what tools transfer to AI. Nines of reliability as the quantitat
Show notesLesson 4 of Track 23. Hendrycks Ch 3.4 takes the substrate under L3 head-on: even a perfectly robust and perfectly monitored system can be pursuing the wrong objective. Three named failure modes (specification gaming, pr
Show notesLesson 12 of Track 22 (Building with Claude), the track closer. The five production disciplines (cost monitoring with the Usage and Cost Admin API; latency budgets per surface; eval-set discipline; rollout via feature fl
Show notesLesson 11 of Track 22 (Building with Claude). Two Anthropic-specific primitives for lesson 9's patterns 4 (orchestrator-workers) and 6 (autonomous agent). Subagents are separate agent instances your main agent can spawn
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