Weekly AI briefs and practical guides. Newest first.
Four practical clusters: AI career transition, job search proof, AI tools for work, and role-specific workflows.
Use the roadmap, timeline, no-code path, portfolio examples, interview prep, and market signals to make a credible AI career change.
AI career transition roadmap
30-60-90 day timeline
No-code AI career path
Build artifacts, resume bullets, and interview stories that prove AI skill without inflated claims.
AI career artifacts
AI portfolio examples
AI skills on a resume
AI interview prep
Pick the right model and workflow for research, reasoning, and daily execution.
Compare AI tools
Copilot Work IQ on/off
Change your AI model
AI salary and market signals
Prompts and quality checks for marketers, analysts, PMs, writers, and data scientists.
Same menu as the Auto / Think deeper post, different switch. Work IQ is not a smarter model — it decides whether Copilot may pull your mail, files, chats, and meetings into the answer.
Read full post →What shipped from OpenAI, Anthropic, Google, and Microsoft, and one thing to do with it.
ReadSeptember 7, 2026 weekly AI brief: Claude Fable 5.1, Gemini 3.8 Flash, GPT-6 Astra, and Microsoft Copilot plus Foundry. One in-role action each.
ReadWhat shipped from OpenAI, Anthropic, Google, and Microsoft, and one thing to do with it.
ReadOpenAI's ChatGPT-and-review study, Gemini Notebook source binding, a Codex workplace story, and Copilot agents. Official sources and one action each.
ReadGPT-5.6 Sol dropped more than 20% for three months, Gemini landed in Chrome on Android, eligible students get a year of Google AI, and Copilot Agent Builder is still the workplace agent path. One action for each.
ReadIt cannot see every tab, and it does not follow formulas that pull from other sheets. Nine issues, and the human checks that keep a bad number off a slide.
ReadChatGPT moved to GPT-5.6, Claude’s current models are agent-first, and Copilot Agent Builder is how workplace agents ship. What to do this week.
Read full post →A short summary of what changed in AI this week, with links to the official sources and one thing to do about it. Part of This Week in AI.
Read full post →Coordinate researcher, analyst, drafter, and reviewer agents into one supervised workflow — with clean handoffs, approval gates, and a proof artifact. Current with AgentKit, A2A, Copilot Agent 365, and Gemini Enterprise Agent Platform.
Read full post →How persistent memory, connectors (Connector Registry, MCP, Work IQ), computer use, and governance (Agent 365, agent identity) turn into trustworthy, career-grade AI workflows.
Read full post →How analysts, marketers, PMs, and operators can brief, supervise, and verify AI agents without pretending to be software engineers.
Read full post →A plain-English guide to tool-connected AI, approval points, audit trails, and the artifact that proves workflow fluency.
Read full post →Evaluation checklists, human review loops, and quality rubrics for people using AI in real workplace outputs.
Read full post →How marketers, trainers, and product teams should brief, review, and disclose AI-generated video and multimodal drafts.
Read full post →A living workbench picker that focuses on workflow, context, integrations, and review effort instead of memorizing model names.
Read full post →A practical roadmap for choosing a lane, learning only what matters, building proof-of-work, and turning AI skill into a credible career story.
Read full post →Six proof-of-work examples for analysts, marketers, PMs, writers, operators, and non-technical professionals moving into AI-adjacent work.
Read full post →What to learn, build, package, and practice across the first 90 days of a focused AI career transition.
Read full post →A practical path for non-engineers using prompts, workflows, review systems, automation tools, and portfolio proof.
Read full post →How to explain AI workflows, verification steps, mistakes, and business impact in interviews without sounding fake.
Read full post →How to read AI salary claims, job descriptions, and skill demand signals before you rebuild your career around a headline.
Read full post →Kept for context only. For current guidance, read the May 2026 agentic workflow brief above.
Read archive →Before/after resume bullets, honest AI keywords, verification steps, and a proof-of-work formula for job seekers who want credibility instead of buzzwords.
Read full post →A real screenshot sequence from a live website showing how to summarize pages, find offers, evaluate policy risks, and use follow-up prompts to make faster decisions.
Read full post →A practical weekly format: what changed in AI, what it means for your role, and one 60-minute action plan to improve career outcomes now.
Read full post →Treat the model like an editor: give it rough bullets and a job description, then verify every metric and phrase. Plus where to find ready-made career prompts for cover letters and interview prep.
Read full post →Tutorial hoarding, the wrong lane, resume inflation, ignoring reasoning models, fake-looking portfolios, and waiting until you feel ready. Each section points to something concrete on this site.
Read full post →Most people never open the model menu. Copilot defaults to Auto; under More you'll find Think deeper and builds like current reasoning builds — better for anything that needs real reasoning, not just speed. Screenshot walkthrough.
Read full post →Not all AI models think the same way. ChatGPT's Thinking mode (and Claude's extended thinking) work step-by-step — they're slower but make far fewer logic errors on hard problems. Here's when to use them vs. the standard fast mode, with examples from real work tasks.
Read full post →GEO (Generative Engine Optimization) is about getting AI engines to cite your content when they answer questions. It's different from SEO — you're optimizing for being quoted inside the answer, not just ranking. Simple tactics: lead with the answer, use lists, add summaries, target how people ask AI.
Read full post →A simple workflow: paste your weekly data table into ChatGPT and ask it what changed, what didn't, and what your boss will ask next. The key prompt trick that stops AI from inventing insights out of noise — and how to get slide-ready bullets in one pass.
Read full post →Plain-language steps for where the model control lives in Copilot, ChatGPT, Claude, and Gemini. No schematic “fake browser” images; for a real Copilot screen capture, we link to the dedicated Copilot post.
Read full post →Context matters more than most people realise. Adding who you are and who the output is for changes results more than almost any other prompt tweak. Plus: how to set output format, break big asks into steps, and treat your first prompt as a draft not a final answer.
Read full post →All posts shown · Browse the Prompt Library →
Bite-sized AI advice you can apply today.
Works best when you tell ChatGPT who you're writing for. I use "Write for [audience] in a [tone] voice" — e.g. "small business owners, casual but expert" — and skip the generic corporate-speak.
When I need to iterate on a doc or chart, I use artifacts. It opens a side panel so you can see the output while chatting. Beats copy-pasting back and forth.
For messy asks, I use: Role (who you are), Instructions (what to do), Steps (in what order), End goal (what success looks like), Narrowing (constraints). Keeps the AI on track.
This week: replace one manual task with AI. Summarizing notes, drafting an email, or pulling insights from a spreadsheet. Just one. See how much time you save.
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