The whole catalogue
In ChatGPT, any chat can search every other chat, send work into them, and collect the results. How to find a lost conversation by asking, delegate work between chats, publish a result to a shareable page, and reach it all from your phone.
08/05/26 delegationcost controlCodexNearly everyone gets anxious before a job interview, and practicing out loud is what lowers it. Give an agent the real documents, a skeptical interviewer to play, and your voice, then have it break character and coach you.
08/04/26 careerA new agent should not run your inbox on day one. Give it one job with read-and-draft access only, check its work until your corrections stop, then add the next tool, and let it run unattended only after it has earned that.
08/04/26 delegationagent safetyBuzz is an open-source team chat from Jack Dorsey's Block where AI agents are members of the channel. What that buys you (swap the model, keep the context), what it can already do, and whether your team should try it yet.
08/04/26 teamsmodel choiceAn agent sent a discount code to 150,000 people because a to-do item looked like an instruction. A rule in the prompt is a suggestion; a rule built into the tools is a restriction. Scope every key to the least the task needs.
08/04/26 agent safetydelegationOne successful run proves an agent worked once. Collect real examples with answers a person already judged good, grade each run with a script or a judging model, and rerun the set after every change so you know whether it helped.
08/04/26 verificationOne big question in one chat makes the model decide, research, write, and grade itself in a single pass. Map the work instead: parallel research jobs, a checker that did not write the answer, a merge, and your approval before anything expensive.
08/03/26 planningdelegationverificationWhen a model can finish the task in minutes, what people will pay you for changes: choosing the task well, doing things others do not know AI can do, feeding your results back into your tools, and proving you can deliver.
08/03/26 careerAnything your agent reads (a web page, a resume, a calendar invite) can carry hidden instructions it will follow. Why the attack has no clean fix, and the five defense layers that shrink what a successful one can do.
08/03/26 agent safetyModels got good where the work grades itself, and they aim at the most likely answer, which in design and writing is the average one. The fix: break your quality standard into checkable rules and keep human judgment for taste.
07/31/26 model behaviorverificationAnthropic removed over 80 percent of Claude Code's system prompt for the Claude 5 models and measured no loss on its coding evaluations. How to give your own instruction files the same trim: goals instead of rule lists, context loaded on demand, and a /doctor audit.
07/28/26 instruction filesClaude CodeA rerun loop makes the agent redo its own work until a check passes. Script the repetitive half of a skill, end it with a pass or fail verdict, wrap both in a loop, and keep a human at the checkpoints where errors are expensive.
07/23/26 automationverificationWrong agent answers usually trace to the files the agent reads. The four ways a growing knowledge base drifts from reality, and the habits (a router file, read-only audits, scheduled pulls, backtracking) that catch the drift.
07/23/26 knowledge basesverificationAn enhance-prompt skill turns a rough request into the full prompt the model will actually run, and shows it to you first. Reading that rewrite catches misunderstandings before any work starts.
07/22/26 writing promptsplanningWhen an agent hits the same problem twice, encode the fix as a lint rule, CI check, or steering-file instruction that every future session inherits.
07/21/26 instruction filesautomationClaude CodeA routine is a saved instruction Claude runs on its own, on a schedule or an incoming signal. What it replaces, and why an unattended run has to be written tighter than one you watch.
07/19/26 automationTwo ways to start an AI task: deepen a rough prompt when you know the goal, or brainstorm first when the goal or the tradeoffs are still open. A quick test for which one you are in.
07/19/26 writing promptsplanningRetrieval augmented generation in plain terms: put the relevant facts in front of the question. How to feed the chat, docs, and code your team already uses into a knowledge base anyone can ask, and why weighting beats volume.
07/19/26 knowledge basesteamsWhen a new model family ships, treat your routing as expired. Re-measure which size and effort give the most score per dollar, spot the size you can skip, and drop the speed modes that do not pay.
07/19/26 model choicecost controlCodexWhether AI can have original ideas is a debate that keeps moving the goalposts. A way to judge it honestly: read the trend line, and see why learning to predict text can build real understanding.
07/19/26 model behaviorYour limit is a compute budget: tokens consumed times the model that reads them. Audit where a session spends, trim the context every chat preloads, and send grunt work to cheaper models so the budget lasts the day.
07/18/26 cost controlClaude CodeThe prompt and the reusable skill file behind the about page on this site, with the reason each part earns its place.
07/18/26 skillsAutomating the bottleneck means finding the constraint that sets your pace and pointing Claude at it: four working rules distilled from Anthropic's own engineers.
07/18/26 automationverificationClaude CodeOpenAI and Anthropic prompting guides are one playbook when read side by side: lean out the prompt. Where they converge, where they diverge, which habits to drop.
07/17/26 writing promptsA memory store is a workspace-scoped directory your agent reads and writes with normal file tools, carrying preferences and prior mistakes across sessions.
07/17/26 memoryGuardrails are the support structure that keeps an hours-long agent run honest: an audit instruction, a memory that survives resets, and fresh-eyed verifiers.
07/17/26 verificationmemoryagent safetyThe newest Claude models are highly responsive to system prompts, so shouting backfires: soften trigger language, migrate deprecated levers, keep the model in bounds.
07/17/26 writing promptsClaude is a brilliant new hire with no context on your job. Brief it like one: explicit instructions with motivation, examples, XML tags, roles, and context ordering.
07/17/26 writing promptsClaude's July 2026 lineup is four models: Fable 5, Glasswing-gated Mythos 5, Sonnet 5 at intro pricing, and Opus 4.8, plus the three migration changes that bite.
07/17/26 model choicemodel behaviorAI Firmware is a boot layer of kernel rules, installable skills, and committed memory that makes every new agent repo start senior instead of relearning old lessons.
07/17/26 instruction filesskillsClaude CodeCodexReasoning tokens are billed at the output rate and re-read every turn after. How to compress what a model says without compressing what it knows.
07/17/26 cost controlA skill file is career-long judgment packaged as instructions your agent can run. How to adopt someone's method, and why you scan it like untrusted input first.
07/17/26 skillsagent safetyModels get repriced, capped, and retired; their way of working can be kept. Extract the top model's discipline into skill files, routing tables, and planner-and-worker setups any model can run.
07/17/26 skillsmodel choice