“There was a paper that Google DeepMind put out a couple of years ago, the the camel paper”
Google DeepMind
By Google
0 recommend/use · 4 sourced episodes
Every sourced reference
Short attributed excerpts only. Timestamps are approximate.
“Demis had this really interesting interview recently from deep mind Google”
“we work very closely with our partners at DeepMind and the Google DeepMind.”
“they came from Google deepmind and they did this for Google Data Centers before”
Related frameworks
Clarity Over Cleverness
Lean into understood standards instead of reinventing them, and you get leverage for free
Complementary Format Integration
Bring a proven new format into a mature product so it expands, not contorts, the core
Conviction-Gated Team Scaling
Start tiny to earn conviction, then staff up enough to actually ship the best version
Design Your Day (Calendar as Canvas + Groundhog Day Iteration)
Draw the day you want on the calendar, run it, see what actually happened, adjust, repeat
Hoard What You Know How To Do
Keep a searchable backlog of verified, working experiments so agents can recombine them into new solutions.
Instrument-and-Improve S-Curve Prioritization
Let retention curves and diminishing returns tell you when to optimize and when to bet on something new
Jobs-to-Be-Done Interrogation (The Big Hire)
Interrogate the moment someone first hired your product to find the real cause of usage
Laser Mode: Engineering Speed Bumps Against Distraction
Willpower never wins. Move the candy further away than the sandwich.
Make Time: Highlight, Laser, Energize, Reflect
A daily four-step loop that changes your defaults instead of making you faster at the wrong things
Mission-Over-Minutiae Opportunity Choice
Choose your next big move by passion, mission, and team — not by optimizing every minor variable.
Northstar Problem Commitment
Pick one foundational building-block problem and commit years to it, not a scatter of trendy ones.
Objective-Data Alignment Test
Before betting on an AI capability, check that your training data is the same shape as your desired output.
Physical-System Reality Check
For anything embodied, budget for three things — a brain, a body, and real application scenarios.
Query Fan-Out Content Strategy (AEO/GEO)
Win AI answers by understanding that a machine, not a person, is doing the searching behind every response
Red/Green TDD for Coding Agents
Force agents to write the test first, watch it fail, then pass — the compressed prompt is just 'red/green TDD'.
Reflect: The Daily Experiment Loop
Treat each day as an experiment you ran, not a gravestone of success or failure
Reset Expectations + Slow Your Inbox
Announce a slower response cadence with a 'because', then actually slow the hamster wheel
The Daily Highlight
Pick the one thing you want to name as today's highlight, size it to 60-90 minutes, write it down
The Dark Factory Software Model
Ship production software no human writes or reads — replace review with simulated-user QA swarms.
The Five-Day Design Sprint
Go from zero to a tested prototype in five days — decide with customer reactions, not hunches
The Golden Recipe of Modern AI
Every AI breakthrough sits on three legs: big data, the right neural architecture, and enough compute.
The Lethal Trifecta
Any AI agent that combines three capabilities can be tricked into stealing your data — cut one leg.
The Thin Skeleton Template
Start every project from a minimal template — agents copy its style far better than they follow prose instructions.
The Vibe-Coding Blast-Radius Rule
Vibe-code freely when only you get hurt by bugs; stop and take responsibility the moment others could.
Three-Prototype Ideation
Since prototypes are now free, build a feature three ways and let real use pick the winner.
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