WRS AI · Technology / Practice / Entrepreneurship
Choose an AI, understand what changed, and make one useful thing.
Checked 2026-10-28 · Original event dates below.
Frontier radar · original announcement dates
OpenAI released GPT-6.1 Terra on 26 October for Work, Codex and the API. Learn what a lower token rate means, then check a tiny fictional invoice before trusting an automated workflow. The earlier developments below keep their original dates; the practical learning library remains separate.
Original announcement dates appear on each item. The practical library remains available below.
TECHNOLOGY · · Recent development
GPT-6.1 Terra brings a new option for visual and computer work. Start with a tiny invoice: extracting the numbers is one step; checking them is what makes the result usable.
Lower usage prices can make small repetitive tasks worth trying. A useful comparison includes the result you can accept, the repairs you make and the product you can actually access.
EVIDENCE · · Recent development
OpenAI released an aggregated view of work-related ChatGPT messages. Learn how to read the categories without confusing a popular request with a completed job.
A list of real requests can suggest a useful small project. It cannot, by itself, tell you that an assistant completed the work or saved its user time.
USE · · Recent development
Agent Skills is moving to a vendor-neutral foundation. Try a small portable notice-checking kit, with examples that reveal when an assistant guesses a missing fact.
A reusable method can save you from explaining the same job each time you change tools. The useful next step is a small kit someone else can inspect and test.
USE · · Recent development
Ollama has added local speech generation with Phonon. Build a tiny spoken-notice check: approved words, a playable result and a listening pass that catches a plausible mistake.
A short audio notice could help a club, a small event or a personal reading tool. The useful deliverable includes a correct script and a way to inspect what the voice actually says.
USE · · Recent development
Moonshot's new launch brings another option for coding and creative work. Before choosing a plan, sketch a weekend planner, give it three awkward events and work out what a useful result would cost.
A new model becomes useful when it can finish your particular task. A tiny project with known answers helps you compare outputs without needing to understand a benchmark leaderboard.
EVIDENCE · · Recent development
Anthropic and Theorem report machine-checked security properties across 123 software libraries. A tiny ticket-counter puzzle explains why this is exciting, and why a proven rule still needs to be the right rule.
A checkable guarantee could make AI-built tools more dependable. Understanding its exact scope helps you ask for useful evidence instead of accepting an assistant's confident claim that everything works.
TECHNOLOGY · · Earlier development
OpenAI made Decisions generally available on 22 October, following its 20 October longer-cache update. Try a three-row sorting exercise, then work out when paying to reuse a fixed beginning makes sense.
A small AI tool often needs a clear category or a few checked fields. Knowing the unit of work helps you compare the interface, the bill and the human checking it still needs.
BUSINESS · · Recent development
Google is rolling out a small-business hub in Gemini. Start with a three-product writing pack: supplied facts, consistent style and a check before anything reaches a customer.
A repeatable, checked deliverable gives a small creative project something concrete to test. More generated content alone does not show that a business saves money or wins customers.
Practical learning library
About 74 minutes · 14,716 words of core reading
You do not need to know how to train a model or start a company to begin here. You need a question, a few public or invented inputs, and a way to recognise a useful answer. This guide takes you from choosing a model to delivering a small result that another person can actually use. Each chapter leaves you with something concrete: a comparison sheet, a permissions brief, a checked summary, a prototype specification, an interview plan or a cost calculation.
Choose one small project before committing to the complete path. The interactive story, FAQ helper, prompt organiser and booking mockup each leave a useful small artifact. This edition makes the recovery rehearsal ready to try: copy ten fictional bookings, predict three permitted changes and catch outputs that have the right row count but wrong contents. Historical studies and founder accounts keep their original dates; observed reports and invented practice budgets remain separate. Exercises use public or invented inputs and your own tools; reading does not start an agent or submit anything to WRS.
Understand AI
Choose for the job you need finished, including the mistakes you will have to repair.
About 5 minUnderstand AI
Understand tools and agents by planning one task with a clear boundary between reading and acting.
About 5 minUse AI
Make sources visible, catch a contradiction, and produce an answer someone can check.
About 5 minUse AI
Turn an unclear idea into a prototype with inputs, outputs and tests that a real person can understand.
About 5 minUse AI
A Chinese creator’s interactive literature project becomes a three-scene beginner exercise, with a clear brief, a small budget and checks that go beyond appearance.
About 4 minUse AI
Copy a ten-row fictional event sheet, test fifteen questions, and compare the time spent answering and reviewing. A real customer case explains the idea; the practice numbers are clearly separate.
About 7 minUse AI
Use a real experiment and a later survey to build your own four-job scorecard: finished work, checking time, failed attempts and cost.
About 8 minBuild with AI
Start an AI business investigation with the last time a problem happened, not a promise of future customers.
About 5 minBuild with AI
Work through one fictional delivery budget, including retries, checking and finding customers.
About 5 minBuild with AI
Why applause did not finish the job: turn Lovable’s early setbacks into a three-state first-use test, a small budget and a clear decision about what to build next.
About 8 minBuild with AI
Turn a founder’s real sales story into a five-card local prototype: copy a prompt, test missing facts and approved changes, then check whether support consumes the margin.
About 8 minBuild with AI
Copy ten fictional bookings, check three permitted corrections and catch wrong results that still contain ten rows. The historical Replit incident explains why reopening the original matters.
About 7 minPut it together
Bring the technical, practical and business lessons together in a project another person can continue.
About 5 minEstimated at 200 words per minute. Navigation, summaries, source notes, glossaries and optional answers are excluded from the core count. Exercises take extra time.
The recovery case now includes a complete fictional table, a copyable cleanup brief and three expected cell changes. Test a duplicated ID, an invented date and an instruction-like note, then compare the preserved original. The historical incident’s eventual recovery stays in the account.
Lovable’s early setbacks become a camera-booking exercise with three clear states, four checks and a 90-minute cap. A Chinese design essay adds the first-visitor question. Learn what a local mockup and a simulated user can actually tell you before spending on more automation.
The TypingMind case now includes a complete announcement template, fictional test inputs, missing-fact and version-change checks, and a worked support budget. Start with manual copying before adding a model connection.
A four-job event-checking scorecard makes the METR case practical. Keep failed attempts, calculate cost per accepted result and identify the next workflow change. A newer historical survey adds the difference between perceived speed and useful output.
A ready-to-copy fictional event sheet now turns the Hospitable case into a small practical exercise. Check unsupported requests, an approved update and whether reviewing AI drafts actually saves time.
Qwen Code’s 9 October update describes voice interaction, work in already logged-in browser sessions and email-triggered tasks. Those capabilities make permission boundaries more important. The browser feature is described for Mac and Linux; the update says Windows is not yet supported. Other capabilities depend on setup.
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Original teaching examples are fictional. Provider reports, founder advice and WRS explanations are identified separately. Business exercises do not promise income or activate paid services.