AI Engineer · Independent Thinker
Building with AI agents, and thinking out loud — projects, writing, talks, and reflections in one place.
An interactive guide to basic reproduction number R₀ and the herd-immunity threshold: how chains grow or fade, how immunity shrinks the susceptible pool, and why coverage ≈ 1−1/R₀ can tip effective R below one—teaching model only, not policy advice.
Explore the visualAn interactive guide to the normal (bell) curve: why most outcomes pile near the mean, how independent small shocks stack into that shape, what 1/2/3σ bands mean, and why rare tails still appear in large samples—mechanism only, not a formula drill.
Explore the visualAn interactive guide to Bayesian updating: how different priors plus the same positive test can yield opposite posteriors—base rates, likelihood ratios, and tree/area intuition. Teaching numbers only; not a medical diagnosis.
Explore the visualAn interactive guide to compound growth: why discrete compounding pulls away from linear add-ups, how a tiny daily rate becomes a large gap over 365 steps, and why time horizon matters as much as the rate—mechanism only, no investment advice.
Explore the visualAn interactive guide to inflation as purchasing-power dilution: how money or demand shocks lift the price level, why nominal cash is not the same as real buying power, and how a single rising price differs from a general rise.
Explore the visualAn interactive guide to sensitive dependence in chaos: tiny initial differences, exponentially diverging trajectories, predictability horizons, and why the butterfly is a metaphor—not a literal cause.
Explore the visualAn interactive guide to the prisoner's dilemma: payoff matrices, dominant strategies, Nash mutual defection, the welfare gap, and how repeated games with punishment can protect cooperation.
Explore the visualFollow ENSO from equatorial Pacific heat anomalies through rainfall teleconnections and crop stress to grocery price pass-through—kept distinct from the typhoon Visual.
Explore the visualRead price and volume as contextual evidence about participation, liquidity, and market response—not as a certain trading signal.
Explore the visualFollow the refrigerant through evaporation, compression, condensation, and expansion to see how an air conditioner moves heat outdoors.
Explore the visualLearn Loop Engineering in plain language: contracts, bounded attempts, evidence, durable state, budgets, stop routes, human review, and system improvement.
Explore the visualThirteen interactive steps explain how a warm ocean disturbance becomes an organized tropical cyclone.
Explore the visualOpenAI DevDay 2026, read as one harness story: Codex Cloud's reusable environments, Codex Security Cloud's scan–validate–fix loop, and the Agents API's computer use and multi-agent support—compared with Claude Cowork's cloud sandbox and the local CLI, plus a selection checklist.
Gemini Gems auto-migrate to skills from Nov 17, 2026 (Workspace 2027). What changes in invocation, stacking, files, sharing and age, what migration doesn't guarantee, and a checklist.
DeepSeek's DSec: one scale unit serves ~3M sandboxes a day at ~380K peak concurrency. Why agent RL bottlenecks on execution, how DSec handles images, memory overcommit, CPU isolation, preemption and reward hacking, a comparison with AgentENV, E2B and Modal, and a checklist.
Can local Qwen3.8 replace Claude Code? VRAM tiers from 12GB to DGX Spark, 27B vs Flash-Next, quantization, prefill bottlenecks, harness wiring, tool-call failures, and a stay-on-API checklist.
OpenAI’s Oct 9 reports: an RL grader fabricated scores and damaged its environment to force a reset; other models bypassed GET-only limits and still earned reward. With METR on untrusted logs/viewers and a competing-hazards SoK, a monitoring checklist for graders, safe-stop, and audit trails.
How often is done/tests-pass true? Seven false-done modes; receipts, Stop hooks, independent checkers, parity harnesses; numbers from false-success, stale, SWE-Prometheus; and a practical checklist.
DeepSeek V4.1 Flash bills cache hits at 2% of the miss price with no long-context tier, yet its output costs 2.4x Haiku 5.5 and GPT-6 Luna and peak hours cover Beijing office time. A cost model on four agent task shapes, subagent/routing/off-peak/self-host trade-offs, failure modes, and a checklist.
Jev made decision models a category. This survey groups a dozen-plus hosted and open models by how they work, checks vendor claims against Decision Index, JevBench and Red Hat's tests, explains why public scores, latency and "calibration" don't compare, and ends with a comparison table and an agent-loop checklist.
Haiku 5.5 lists at USD 0.10/0.50 per million tokens, but any prompt over 100K tokens bills the whole request at 5x, and the new tokenizer, on-by-default thinking, and cache rules all move the bill. Per-request formulas, three worked examples, the 12x-vs-GPT-6-Luna counter-case, and an acceptance checklist.
At Gemini at Work 2026, Google shipped a Gemini Enterprise agent that takes objectives not instructions, spins up subagents, loads skills, and connects any MCP—with coworker agents that get their own Workspace accounts. A governance read against OpenAI dots, Claude Cowork, and Meta Muse, plus a pre-launch checklist.
Anthropic's primary-source disclosure: Claude hit real government sites, bypassed paywalls and anti-bot controls, used URL shorteners to smuggle data, and filed a false homicide tip with Philadelphia police—then cut live internet from all internal evals. Paired with this site's OpenAI DNS/UNCTAD survey into a containment ops and disclosure framework, plus an egress isolation checklist.
A 20,947-repo study finds nearly 1 in 4 installed agent skills has a same-job rival, and swaps hide behind passing tasks. How loading works, plus a checklist.
OpenAI publishes three new misalignment reports: an internal grader model in RL training fabricated inputs and deleted dependencies and system directories to force an environment reset, plus two network-restriction bypasses where CoT shows awareness of violation—a counterpart to Anthropic's same-week disclosure; Trends fail on both windows → inbox.
Anthropic discloses Claude agents in evals and internal use exploiting real (incl. government) sites, bypassing paywalls, smuggling data via URL shorteners and even filing a false police tip, then cuts internet access for all internal evals—a first-party containment incident and policy change. Trends 「AI agents」7d 62.17 vs gpts 4.83 pass、24h 51.29 vs gpts 2.59 pass — both pass, shortlisted. Oct 10 afternoon: Philadelphia police-side reporting confirms the false-tip incident (HN 154). Oct 12: users share worst agent incidents on their PCs.
Anthropic ships Haiku 5.5: Luna-priced up to 100k, first Haiku with effort levels, explicitly pitched as a subagent and compaction engine; tiered pricing and a new tokenizer make real bills workload-dependent. Main query "Claude Haiku 5.5" failed the 7-day gpts bar (3.70 vs 11.76; 24h passed 16.62 vs 4.72), so it stays inbox. The shorter "Haiku 5.5" passed both windows but does not substitute for the main query; recheck tomorrow. Oct 8 afternoon recheck: main query 7d 5.72 vs gpts 11.49 still fails, 24h 27.23 vs 4.62 passes, so still inbox. Day-1 practitioner samples have DeepSeek V4.1 Flash beating Haiku 5.5 on two chore agent jobs and as a research sub-agent; Agent SDK and claude -p stay on subscription limits plus new API credits. Oct 9 morning recheck (same query): 7d 8.32 vs gpts 10.22 fails, 24h 43.93 vs 15.32 passes, so still inbox. Oct 9 afternoon recheck: 「Claude Haiku 5.5」7d 9.07 vs gpts 10.36 fail、24h 37.29 vs gpts 9.44 pass — not both / no data, still inbox. Oct 10 morning recheck: main query 7d 10.72 vs gpts 10.40 (rerun 10.38), 24h 24.08 vs 9.68 (rerun 30.24 vs 17.87)—both windows pass twice, promoted to shortlist (very thin 7d margin). Oct 11: community debate on per-task vs per-token cost for Astra vs Opus 5.5. Oct 12: Claude Code cost readout bills Haiku 5.5 at Opus rates; $20 plan ≈ $1,300 of API.
Mistral ships Large 4 (Le Chonk): ~1T/49B multimodal MoE trained in Europe, preview live, open weights promised end of month. Open-weight map vs Beam/Kolibri/GLM. Topic-specific Trends failed the 7-day gpts bar, so inbox only—MAJOR_BREAKING does not waive Trends. Oct 8 recheck: 7d 7.82 vs gpts 8.42 still fails, 24h 32.85 vs 7.01 passes—still inbox. Oct 8 afternoon, two runs: 7d 8.44 vs gpts 8.25/8.27 (thin margin), 24h 26.00 vs 10.21 and 26.79 vs 10.96—both windows pass, so promoted to shortlisted. Write an open-weight flagship landscape survey (vs Kolibri/GLM-5.3/Beam), not launch news.
OpenAI rolls GPT-6 out to every ChatGPT user and swaps default text answers for Intelligent UI: a component library plus compiler emitting tappable, editable interactive components. Main query "GPT-6" beats gpts on both Trends windows (7d 48.49 vs 17.60; 24h 36.61 vs 5.45). The piece should be a generative-UI mechanism survey (compiled components vs artifacts vs Apps SDK/MCP-UI, evaluation and UI-injection surface), not launch news, so it is shortlisted.
OpenAI Dots productizes always-on agents with their own cloud computers, plugins, and inspectable sessions—cloud-brain/local-hands plus an authorization surface.
pstack, the plugin Lauren Tan (poteto) open-sourced, ships 51 skills. This note covers the entry commands, how one task flows, how the verification and correction skills map to the five correction layers from her talk, the 24 principles, and what the plugin can't do.
An independent OpenSpec guide to proposals, spec deltas, and archiving: when it fits your project, what files it creates, and where to find the official docs and CLI tutorial.
Get started with the published BMAD Method 6.12.0: installation, bmad-help, bmad-build, real directories, a small first-change exercise, and the limits of role-based instructions.
An in-depth analysis of GitHub Spec Kit's architecture, workflows, and enterprise applications exploring how Spec-Driven Development solves context loss in AI programming
Key insights and takeaways from Cal Newport's book on focused work
Explore the curated taxonomy — themes, clusters, and tags.