Method · MoneyBuild the golden dataset in Phoenix by finding every report with a human label, making each an example where the input is the report and the expected output is the human's label, sorted by span ID. Use a 75/25 split: 75% of labels in the tuning set and 25% in the test set. Sort examples by span ID before splitting so a report always lands in the same split however many times you run it, and span ID links each example back to its original trace. Put every fourth example into the test split and the rest into dev.
Method, not a verified protocol.
AI Engineer · How to Know If Your AI Agent Is Any Good: Evals With Phoenix & Claude — Laurie Voss, Arize AI
Method · MoneyMeasure your judge by comparing its predictions against the truth of what a human expert would say. Create human annotations in Phoenix by opening a trace, clicking the pencil button, and adding an annotation (e.g., 'human actionable' set to actionable or not actionable) for each trace. Involve a domain expert by having them read trace outputs and produce a golden dataset of correct labels (e.g., 10, 20, or 50 traces).
Method, not a verified protocol.
AI Engineer · How to Know If Your AI Agent Is Any Good: Evals With Phoenix & Claude — Laurie Voss, Arize AI
Method · MoneyThe eval improvement loop: trace your agent, read what it did, write evals for what matters, check the evals can be trusted, change the agent, prove the change worked, then lock it in with CI.
Method, not a verified protocol.
AI Engineer · How to Know If Your AI Agent Is Any Good: Evals With Phoenix & Claude — Laurie Voss, Arize AI
Method · BodyZoom out of the 162-game season to find long stretches without off days (10, 13, or 17 games in a row), map time zone, surface, and elevation changes, factor in turf vs grass and stadium dimensions (e.g., Rockies' big outfield, Fenway's short porch), then plan with baseball and performance staff how to mitigate stress through tough streaks — including skipping early work on high-distance days and managing sleep as a performance team.
Method, not a verified protocol.
Garage Strength · How The Best Pro Baseball Players Actually Train w/ MLB Strength Coach Stephanie Grubbs
Method · BodyUse traditional periodization for starting pitchers since they pitch once every five to six days. Work backwards from the start date: schedule the upper body lift on bullpen throwing day to marry stress, give a recovery day (spa day) after the start followed by the lower body lift, schedule sprinting the day before the start as a neuromuscular primer, and add other conditioning work in addition to lifting and sprinting.
Method, not a verified protocol.
Garage Strength · How The Best Pro Baseball Players Actually Train w/ MLB Strength Coach Stephanie Grubbs
Method · BodySet up a testing profile with a global view: rotational power (Proteus), explosive countermovement jump on force plates, lower body strength (belt squat ISO, BBT force-velocity profiling), sprint assessment (1080, Velo), and site/tissue-specific measures (Nordics for hamstrings, Force Frame for groin and shoulder internal/external rotation). Collaborate with sports med, ATs, and PTs, and apply the approach to any sport.
Consequential creator advice requires independent verification before Today can promote it.
Method, not a verified protocol.
Garage Strength · How The Best Pro Baseball Players Actually Train w/ MLB Strength Coach Stephanie Grubbs
Method · BodyStarters pitch every 5-6 days, so work backwards from the start date: upper body lift on bullpen day, lower body lift after a recovery 'spa day' following the start, sprint the day before the start as a neuromuscular primer, plus other conditioning.
Method, not a verified protocol.
Garage Strength · How The Best Pro Baseball Players Actually Train w/ MLB Strength Coach Stephanie Grubbs
MethodUse Lean as a theorem-proving system that checks every step and doesn't let you make a mistake — what you need in high assurance situations. Rewrite programs in a common intermediate language, compile to verification conditions in Lean, and prove Lean theorems to show the code is correct. Lean SMT can prove many Lean theorems in milliseconds on a CPU. With VerisForge, you enter a specification in English and it builds the code and does the formal proof.
Method, not a verified protocol.
Y Combinator · AI Safety Fact vs. Fiction | YC Paper Club
MethodWhen simulating safety scenarios, don't waste time on non-hazardous situations (e.g., aircraft separated by five miles); simulate critical scenarios representative of the airspace. If falsification reveals failures that give you a bad feeling, either don't deploy the system or implement mitigations to prevent those critical scenarios. Simulated inferences about safety are only as good as the simulator, so real-world testing is also needed. There is no one silver bullet — it requires a number of different kinds of approaches. Continue validation after deployment via runtime monitoring or runtime assurance: validate sensor inputs going into the decision system, monitor the internals, and model and monitor the outputs.
Method, not a verified protocol.
Y Combinator · AI Safety Fact vs. Fiction | YC Paper Club
Method · MoneyGuideline questions to start asking: who/team spends what? What must you test to use a cheaper model? What's your base load? What's the default model for each team? Which workload has a person waiting that needs something faster? And how much of what we generate is useful?
Method, not a verified protocol.
AI Engineer · The AI Bill Is Too Damn High: Tokenomics 101 — Eugene Cheah, Featherless AI
MethodBug Hunter is a very effective flow and pattern for closing loops and making systems run more autonomously, available as a template and in Claude Code. Instead of a single agent reviewing a PR, it uses a multi-phase flow: (1) code is split into slices, each handed to an individual context/agent that reviews only that slice and writes down potential problems; (2) a reviewer agent gets the slice plus the flagged problems and can agree or disagree with each; (3) a final phase picks candidates that might actually be real problems needing verification. In a prover phase, an agent can download the repo, try to reproduce the bug or verify it's a legit problem, and surface results in a report. In practice the report is added as comments to the actual PR, raising issues in line (e.g., a change to a
described/endorsed
Method, not a verified protocol.
AI Engineer · Why One AI Agent Isn’t Enough (And How to Run 1,000) - CJ Avilla & Harrison Stall, Anthropic
MethodBug Hunter splits code under review into slices, each reviewed by an agent that writes down potential problems; a second-phase reviewer agrees or disagrees with each problem; a final phase picks candidates that might be real; a prover phase downloads the repo and tries to reproduce the bug; findings are added as inline PR comments with severity priorities.
Method, not a verified protocol.
AI Engineer · Why One AI Agent Isn’t Enough (And How to Run 1,000) - CJ Avilla & Harrison Stall, Anthropic
Method · MoneyThey split the answer into parts: the agent streams markdown prose token by token with the frontend styling it live, and the source card — a real UI component that holds nothing you'd click before reading the answer — is appended as one piece after the full answer arrives.
Method, not a verified protocol.
AI Engineer · Your Fridge Is a Valid Payment Device — Eleonora Drykina & Nina Žižakić, In The Pocket
Method · MoneyInstead of fixed retrieve-then-generate, the agent has four tools ordered narrow to wide: search rulebooks (the 10 hybrid-retrieval chunks), retrieve rulebook sections (whole section by section path), retrieve full rulebook (small rulebooks only), and list available rulebooks.
Method, not a verified protocol.
AI Engineer · Your Fridge Is a Valid Payment Device — Eleonora Drykina & Nina Žižakić, In The Pocket
Method · MoneySearch rulebooks always comes first — that is the 10-chunk hybrid search. If search is not enough, the retrieve rulebook sections tool pulls the whole section in order by section path, fetching every chunk with that path sorted by chunk index. The retrieve full rulebook tool works for small rulebooks only, and list available rulebooks is for when the agent needs to know what exists at all. Guardrails: if a rulebook is too big (over roughly 100K tokens), the full rulebook tool refuses to dump its content into the context and hands back the available section list with a warning; if a section name doesn't match, the tool hands back the available sections so the agent can retry rather than give up or invent the name.
Method, not a verified protocol.
AI Engineer · Your Fridge Is a Valid Payment Device — Eleonora Drykina & Nina Žižakić, In The Pocket
Method · MoneyThe indexing pipeline starts with PDFs, pulls text from every page, splits it into paragraphs, and packs paragraphs into chunks of about 2,000 characters, never splitting a table over two chunks. Section headers are detected with regular expressions (e.g. 'chapter 3', '4.2.1'), giving every chunk a section path used for citations and for fetching whole sections. Chunks are not overlapped, so a section is just an ordered collection of chunks that can be reassembled into the original document. Metadata added per chunk includes rulebook name, page, and chunk index (letting the agent reassemble sections or whole rulebooks), plus business logic fields like rulebook type, applicable roles, and whether it contains a table. Two types of embeddings are generated: dense and BM25. The indexing yields
Method, not a verified protocol.
AI Engineer · Your Fridge Is a Valid Payment Device — Eleonora Drykina & Nina Žižakić, In The Pocket
MethodOpen the variables panel to watch typography adjust as values change, group related variables (right-click, new group, e.g. 'Joey P'), create a number variable for letter spacing (e.g. zero), add a paragraph-spacing variable (a key variable, e.g. set to 12 for serif mode), then with text selected click apply styles (four dots) and plus to create a composite style that composites all the decisions and applies variables at scale.
Method, not a verified protocol.
Figma · Figma for Edu: Working with typography systems
MethodCreate a new variable in Figma to start building a typography system. Name a string variable (e.g., 'my font base') directly in the creation field. Set a string variable's value to the exact font name you are working with. Add a second string variable for the serif font and set it to the chosen serif (e.g., Instrument Serif). Create a number variable named font size to hold the base font size for a given track (declared as 16 in the demo). Create a number variable for line height — the third key variable in a type system. Create a string (or number) variable for font weight and set its value (e.g., 400). Give variables proper names (e.g., rename the weight variable to 'font weights'). Make sure letter spacing is zero on the type scale text. Break existing variables on the text before ap
Method, not a verified protocol.
Figma · Figma for Edu: Working with typography systems
MethodA step-by-step method for building a type system in Figma: create variables for font name, size, weight, line height, letter spacing, paragraph spacing, and indent; bind them to text; group them; and composite them into a reusable style.
Method, not a verified protocol.
Figma · Figma for Edu: Working with typography systems
MethodCreate a variable collection (e.g., named 'Type Scale') and organize variables into groups within it. Codify each typography property — font family, font weight, font size, line height, letter spacing — associated to a specific brand within the variable collection. Rename variable modes to brand names (e.g., Serif brand, Sans Serif brand, MOSF for Museum of Speculative Futures). The brand mode is set at the frame level (e.g., 'Type Scale MOSF'), which drives all the designs in that frame. Switch a frame's mode (e.g., to Sans Serif or Serif) to see a different layout, which helps test the design. When switching modes, type sizes can vary greatly between brands (e.g., H3 differs), so readjust sizes and apply the changes.
Method, not a verified protocol.
Figma · Figma for Edu: Working with typography systems