Fast Task Switching Roadmap (CPU)

AI can summarize, calculate, draft, and remind — but if you don’t hear the reminder or if the draft gets buried under twenty browser tabs, the value disappears. The magic isn’t only in the model, it’s in the workflow. Most people miss this step: getting your local machine tuned so the AI becomes an actual assistant instead of just a chat window.

Start with notifications. On Windows 11 you go Win + I → System → Notifications, toggle On for your browser, then drill down into the browser entry and make sure Play a sound when a notification arrives is enabled. On macOS it’s Apple menu → System Settings → Notifications, pick Safari or Chrome, turn on Allow Notifications and check Play sound for notifications. Then confirm your browser side is squared away: in Edge, for example, go to Settings → Cookies and site permissions → Notifications and add ChatGPT (or whatever AI site you use) to the Allow list. Don’t take it on faith — always send a test notification to see a popup and hear a ding.

Sound alerts are next. Right now all browser notifications share one sound, but you can bend the system. On Windows go to Control Panel → Sound → Sounds tab and change the global Notification sound, or layer in tools like EarTrumpet or Audio Router to route different tones to different apps. On Mac you can drop custom .aiff files into the System/Library/Sounds directory and assign them. That gets you part of the way, but what we really want is per-tab sound assignment: bells for markets, animal sounds for mail, sirens for security. It isn’t native yet, but you can rig a partial workaround with extensions like Workona or Tab Snooze combined with AutoHotkey (Windows) or BetterTouchTool (Mac) to trigger custom sounds when specific URLs throw alerts. Not plug-and-play, but if you’re stubborn, it’s Saturday-afternoon doable.

After that, build a handshake between AI and your files. Make a folder called AI_Scratchpad right on the desktop with subfolders for Drafts, Data, and Charts. Point your AI outputs there. Sync it with OneDrive, Dropbox, or iCloud so you can pick up the same files from your laptop or phone. Then pin it in Windows Quick Access or Mac Finder Favorites so it’s always one click away. That scratchpad folder becomes your workbench.

Browser extensions can ease the grind too. Reader Mode strips clutter before you paste into AI. Tab Manager Plus color-codes tab groups by project. Save as Markdown lets you archive sessions in plain text. Auto Tab Discard frees up memory when you’re running 20+ tabs. The idea is to keep AI snappy and your workspace uncluttered.

Hotkeys keep the loop tight. Win+Shift+S on Windows or Cmd+Shift+4 on Mac lets you grab a screenshot and paste it into AI immediately. Dictation (Win+H on Windows 11, or double-tap Fn on a Mac) means you can prompt the AI without typing. Clipboard managers like Ditto (Windows) or Paste (Mac) let you hold multiple prompts and snippets in a rotating buffer so you can paste exactly the one you want without retyping.

Make a ritual out of it. Run a morning ding test like a fire alarm drill. Check that AI is still on your browser’s Allowed Notifications list — updates sometimes reset things. Clean out the scratchpad weekly so you don’t drown in outdated drafts. These tiny habits make AI feel like a tool in the shop instead of a toy on the counter.

The missing piece is tab-assignable sounds. Imagine writing with twenty tabs open and knowing instantly which tab wants you by the sound alone: a bell means your market feed hit, a cow moo means the AI finished a draft, a siren says the ECB rate decision just dropped. Right now no browser does this natively, but the plumbing is half built in tab group extensions and notification APIs. All that’s missing is mapping per-tab or per-URL to distinct audio files. When some dev finally delivers it, productivity nerds — and ranch hands — will cheer.

So the takeaway is simple. AI isn’t just about smarter answers. It’s about fewer misses. With sound, popups, and file paths tuned, your AI really does become a desktop assistant that taps you on the shoulder at the right time. Set it up once and every task after runs smoother. Until someone builds that tab-assignable soundboard, the rest of us will keep cobbling together workarounds — bells, moos, sirens and all.

Offline Task Switching Hacks

But remember: not all task-switching happens on a screen. Some of the biggest productivity gains come from how you handle the “offline” shifts. A few worth wiring into your daily operating system:

Reset rituals: Every time you finish a task, do a one-minute reset — stand up, breathe, stretch. It clears the buffer before loading the next program.

Chunking: Group similar work (calls, emails, reading) into batches instead of letting them interrupt scattered throughout the day. That reduces context-switching tax.

Cue cards: A simple notepad or sticky notes can anchor the “next thing.” Write the hand-off line before you switch, so your brain doesn’t burn cycles remembering where you left off.

Environmental anchors: Change physical context with the task — one chair for writing, another for calls. Your body learns the cues and helps you switch faster.

Verbalize the swap: Literally say to yourself, “I’m done with X, now starting Y.” Sounds goofy, but it closes one mental loop and opens another cleanly.

The computer tricks save seconds; the self-management tricks save minutes or hours. Together they compound — that’s where the mind amplifier value comes in.

Unless you find computers alarming enough, already?

–Anti-Dave

TL;DR: Here’s an intro to effective AI use, written for Peoplenomics.com subscribers. It offers an uploadable streamlining approach to AI utilization for higher impact in less time.

What to Know: As a new user of AI you will quickly find that in some sessions, the AI really is like NZT-48 – that mythical super brain drug from the TV show “Limitless.” Other times, sessions will drag, cool concepts will be lost, and it will be kinda like swimming in Jell-O.

The reason has everything to do with how AI and humans interact, the way in which personal work is stored (usually very short-term – session-length). A result? You may get frustrated.

Have no fear, there’s an easy fix. An SFE file. Command and controls set to your liking and uploaded as you start each new session (or day).

**What the Hell is SFE?**

SFE – Shared Framework Experience – is a simple, reusable “rules + commands” sheet you paste into a fresh AI session so the model works your way: same voice, same structure, less back-and-forth. It de-stresses the workflow, saves time, and makes results repeatable across projects and tools.

Newbie Note: “parms” are short for parameters – these are the switches, limits, conditions, and rules you wish applied to your work. AI can only deliver what you want if you first tell it what that “fit and finish” of final product looks like.

If you want a chart (as I frequently do), you’ll need to tell AI “I need a chart of the declining number of US Factory Jobs in the USA since 1990. AI can do that, but unless you tell it very specifically what your “deliverable” is, you might end up with:

a link to a chart on a Fed or FRED web page.
a .PNG file (which is usually what I’m after as a financial writer)
a spreadsheet which you can then download and open as an XLS file and create whatever style you want in your chart.
OR you can get a big glop of Python source code that you can paste into a txt file and run with your already-installed Python runtimes and Pandas…

(A Panda? In Python, pandas is an open-source data analysis library that provides fast, flexible data structures—primarily DataFrame and Series—for manipulating, cleaning, and analyzing tabular and time-series data.)

Enough of this small-talk – let’s do something!

How to load your parms

Open a new AI chat.
Paste the SFE rules below. Start with: “Here’s my SFE—Rules. Please read and operate as outlined.” [Note: Save this into a text file or sticky note so you have them on hand with zero hassle.)
Ask the AI to acknowledge with “SFE loaded.”
To repeat!!! Save this SFE as a local text/Word file. Re-use it at the start of each session.
Keep the command list handy; different AIs vary slightly, but this framework ports cleanly to most of the majors.

SFE — Rules and Commands

(Save the following as a text or Word file. Use it at the start of a research or writing session.)

Global Format Toggles

SFE ON = H3 headings only, plain text, no links, no separators
SFE OFF = normal formatting allowed
NO LINKS = do not include links or citations
HEADINGS H3 ONLY = use ### headers and paragraphs only
NO SEPARATORS = no lines, boxes, or section bars

Voice And Tone

KEEP MY VOICE = preserve Ure/PN style and cadence
PLAIN STYLE = reduce flourish, keep sentences tight
HARD TECH TONE = emphasize engineering details and guardrails
READER-FRIENDLY = shorter sentences and one-line takeaways

Workflow Passes

SPELL = list only literal misspellings from my paste
STYLE = optional phrasing tweaks; show minimal alternatives
CHECK = flag claims likely to trigger “cite it” pushback
TRIM = compress to one page without losing meaning
EXPAND = add depth/examples without new claims

Structure Commands

STRATEGY + PATH = write “Strategy: X” then “Engineering Path: Y”
THREE PARAS = produce exactly three paragraphs on the topic
DROP-IN = add a discrete software/firmware block I can paste
ADAPTIVE LAYER = gating, thresholds, safety, fallback logic
MINI + PERFECT = outline a simple probe device and a full device
DAY-ONE PROTOCOL = short, actionable daily routine
ZETA BOX = three paragraphs: definition, measurement difficulty, on-ramp

Scope And Safety

NOT MEDICAL ADVICE = include one gentle disclaimer line
CONSERVATIVE CLAIMS = swap absolutes for “often,” “may,” “within weeks”
GUARDRAILS = floors, ceilings, stop conditions, revert-to-baseline

Evidence And Browsing

NO BROWSE = rely only on my text and prior notes
SOFTEN CLAIMS = rephrase to reduce citation pressure
BROWSE FACT-CHECK LITE = verify dates/definitions without links in output

Editing Targets

FIND ERRORS = list only misspelled words verbatim
INLINE FIX = each misspelling → correction on one line
CLEAN DUPES = remove repeats or near-dupes
TIGHTEN OPEN = one-sentence promise up top
STRONG CLOSE = one-sentence takeaway or CTA

Investor Angle

INVESTOR HOOK = why this matters to small/mid investors
MARKET MAP = categories, buyers, moat in two short paragraphs

Cognitive Templates

RECALL DRILL = append a one-minute memory task
HUMOR BLOCK = short Restoration of Humor routine
BREATH CADENCE = add gentle cadence cues and ramp logic

Output Controls

LENGTH SHORT = 250–400 words
LENGTH ONE PAGE = ~700–1,000 words
KEEP NUMBERS = preserve numeric values and units
NO NEW CLAIMS = reorganize only; nothing new

Why SFE helps

Shared rules remove guesswork. You get consistent structure, faster drafts, and less “time-sink mud.” On complex reports, SFE trims loops by aligning expectations on format, scope, and safety from the first message. Teams can share one SFE so outputs match across authors.

Tokens, context windows, and chunking

Large models read and write in tokens (tiny pieces of text). Roughly, 1,000 tokens ≈ 700–800 words of English prose. Each model has a max “context window” (how much it can hold in working memory at once). When you exceed that window, the model must drop or compress context, which risks losing earlier details.

Long documents should be worked in labeled chunks (“Part 1 of 4: Intro + Problem,” “Part 2 of 4: Methods,” etc.). Ask for outputs in ~1,500–2,000-word chunks when you’re moving fast; this keeps you out of “token jail” and reduces truncation. After each chunk, paste it into a local Word doc to save and edit; then feed only the relevant excerpt back in for the next step (“Here’s Part 1 for context—now write Part 2 per SFE. LENGTH ONE PAGE.”).

When revising, quote only the paragraph(s) you want changed plus the SFE command. Example: “SPELL on the next paste only.” or “STYLE on the next three paragraphs; do not change claims.” This minimizes token use while preserving control. If you need the model to recall earlier sections, paste a short recap you wrote yourself (“Two-sentence brief”) instead of the whole chunk to save tokens.

Investor “Solve-For” commands

(Save this as a separate local file titled: Investor Rules.)

SOLVE FOR: Moat map — list switching costs, network effects, data advantages, and regulation tailwinds by strength and durability
SOLVE FOR: Unit economics — contribution margin, payback period, cohort decay, CAC/LTV sensitivity
SOLVE FOR: Catalysts — next 3–6 value-moving events; probability and impact bands
SOLVE FOR: Downside — three failure modes, leading indicators, and stop-loss tripwires
SOLVE FOR: Scenario table — base/bull/bear with key drivers and probability weights
SOLVE FOR: TAM/SAM/SOM — bottom-up build with assumptions called out explicitly
SOLVE FOR: DCF knobs — growth, margin, reinvestment, discount rate; show ranges not points
SOLVE FOR: Five Forces — supplier power, buyer power, substitutes, new entrants, rivalry with one-line evidence each
SOLVE FOR: KPI dashboard — 8–12 operating metrics to watch each quarter, with red/amber/green thresholds
SOLVE FOR: Earnings prep — likely beats/misses, whisper numbers, and what would change the thesis
SOLVE FOR: Post-mortem — what moved the stock vs. what moved the business; update risk/catalyst sheets

How to use: paste one or two SOLVE FOR lines with a ticker or sector and your timeframe. Example: “SOLVE FOR: Scenario table for mid-cap specialty insurers over the next 12 months.”

Working style: how we solve together

We move fast because we share commands and a target. You tell me the frame (“STRATEGY + PATH, LENGTH ONE PAGE, READER-FRIENDLY”), I produce the draft, and we iterate with narrow passes (“SPELL only,” “TRIM to 700 words,” “CHECK the bold claims”). For mathy work—like cycle decomposition—we agree on inputs, constraints, and outputs first (“KEEP NUMBERS, SHOW STEPS, SOLVE FOR: cycle lengths and phase”).

That shared map lets us compress complex problems into a few tight loops instead of twenty loose ones.

Human-AI collaboration is massively rewarding. It’s the difference between trying to go into virgin forest with a pocket knife instead of a chainsaw with the mission of cutting firewood.

Like any skill, the more you use it, the better you’ll get. And AI will get better – and work more in your style – as you go.

The biggest fear people should have of AI? Missing the boat.