πΏοΈ Miffed

Hello {{first_name|Motivated and Miffed Community}},
The hype machine is loud; the useful bits whisper. Hereβs the part worth your caffeine.
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TL;DR
π€ GPT-5 backlash: OpenAI made GPT-5 the default, users complained, older models were restored with promises of better control/transparency.
π§° Recovery tweaks: Raised Plus limits, smarter auto-routing, optional βthinking modeβ controls after outages/error spikes.
π Safety watch: New jailbreak and βzero-clickβ agent risks surfacedβtighten sandboxes, allow-lists, and tool scopes.
πΌ Productivity pulse: Egnyte ships an internal Agent Builder; AWS rolls out agentic-AI tooling/marketplace.
π Tool: Endex (Excel AI agent) automates data cleaning, models, and memos inside spreadsheets.
π§ Top 3 AI Stories
OpenAI just lifted the ceiling: anyone can generate 15s clips; Pro users get 25s, on app or web. Translation: fewer jump cuts, cleaner beats, and better pacing for quick explainers or hooks.
Creator move: Write a 25-second script (β60β70 words), then add a 1-line CTA.
Google rolled out Veo 3.1 with Flow upgrades: lighting/shadow edits, object removal coming, βFramesβVideoβ (first/last frame to a full transition), βIngredientsβVideoβ (build with refs + audio), and Scene Extension (extend clips up to a minute). Itβs available via Geminiβs paid preview. Net: more control; fewer βAI tells.β
Also noted: Veo 3.1 Standard/Fast in the Gemini API.
Creator move: Recut one old clip: generate a transition between two frames and add AI audioβpublish a before/after.
Googleβs Secure AI Framework 2.0 explicitly targets agent risks (prompt injection, over-permissioning, runaway loops). Theyβre also shipping agent examples (like CodeMender) + a vulnerability reward program. Treat SAIF 2.0 like your free checklist.
Creator move (15 min): Add a manual-review gate, trim tool scopes, set a step/time cap, and log actions for one agentic workflow.
π Bonus backdrop
Sora growth: crossed 1M downloads < 5 days last week; expect more creator scrutiny around rights/likeness.
EU βAI in Scienceβ push: more grants/standards shaping research tooling.
Compute megadeal: OpenAIΓNVIDIA targeting 10 GW with up to $100B investmentβfaster model cadence ahead.
π οΈ Creator Prompt of the Week
βTurn [story above] into: (1) a 25-second script, (2) a 3-bullet LinkedIn post (what happened / why it matters / what to do), and (3) a YouTube description with one clear CTA.β
Here is an optimized versionπ
Developer: # Role and Objective
Generate three targeted outputs from the provided [story above].
# Instructions
- Transform the given [story above] into:
1. A concise script approximately 25 seconds in length, returned as a string.
2. Three concise LinkedIn post bullets (list of strings), each covering:
- (a) What happened
- (b) Why it matters
- (c) What to do next
3. A YouTube description (string) that clearly ends with a single call to action (CTA).
- If [story above] is missing or unavailable, return an error message indicating this.
# Context
- Input: [story above] (required for successful output)
# Plan First
Begin with a concise checklist (3-7 bullets) of what you will do; keep items conceptual, not implementation-level.
# Output Format
Return a single JSON object with the following fields:
- `script`: string The 25-second script.
- `linkedin_bullets`: array of 3 strings Each is one LinkedIn bullet, following the instructions above.
- `youtube_description`: string YouTube description clearly finishing with a CTA.
- `error` (optional): string Only include if [story above] is missing.
## Example
```json
{
"script": "Once upon a time...",
"linkedin_bullets": [
"A new framework was launched today.",
"It simplifies API integrations for devs.",
"Try it out to save development time."
],
"youtube_description": "Learn how the new framework helps developers work faster and more efficiently. Dont forget to subscribe for more updates!"
}
```
# Reasoning Steps
- Parse input, verify [story above] is present
- Structure outputs per requirements
- Return error field as described if input missing
# Post-action Validation
After producing output, validate that all required fields are present and correctly structured. If validation fails, self-correct before returning.
# Verbosity
- Keep outputs concise and clear.
# Stop Conditions
- Complete when the JSON object is returned as specified, or when an error field is produced due to missing input.π Thatβs All!
You donβt need every headlineβyou need one small win. Pick one workflow, add a human-review step + a backup model, and ship a tiny demo before the weekend.
Stay MOTIVATED,
Gio


