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Claude Opus 4.6

By Anthropic

2 recommend/use · 4 sourced episodes

Every sourced reference

Short attributed excerpts only. Timestamps are approximate.

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Best-Model-First Agent Workflow

Use the most capable model on max effort, start in plan mode, then auto-accept — counterintuitively cheaper.

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Build for the Current Model, Prototype for the Next

Elicit max capability from today's model while pre-building the products the next model will unlock

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Build for the Model Six Months Out

Design your AI product for the model that ships in six months, not the one you have today.

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Clear-Goal Ambiguity Cut

Because general LLMs can do anything, a sharp key-user + problem + use-case triad is what rules approaches out

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Don't Box the Model In

Give the model tools and a goal, not a rigid workflow — scaffolding gains get wiped out by the next model.

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Exponential Bet Allocation

If AI is your core value, shift the growth portfolio from micro-optimizations to large bets

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Hoard What You Know How To Do

Keep a searchable backlog of verified, working experiments so agents can recombine them into new solutions.

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Latent Demand Product Discovery

Find your next product by watching people misuse your current one for something it wasn't designed to do.

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Self-Mastery5 steps

Lean Into Your Spike

In the AI era, double down on your unfair advantage and stack disciplines to become a unicorn

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Leadership3 steps

Mission-Above-Product Prioritization

Route every cross-org tradeoff through a single shared mission so decisions are fast and everyone stands behind them

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Innovation4 steps

Model Introspection Harness Repair

When an AI agent misbehaves, ask it why — its explanation reveals the harness gap to fix

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Productivity4 steps

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'.

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Innovation4 steps

Ship-in-Research-Preview Speed Loop

Cut idea-to-user time from months to a week by branding launches as previews and pre-wiring the launch chain

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Marketing4 steps

Strategic Friction

Add friction that helps a user understand why the product is for them; cut friction that doesn't

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The 100%-or-Nothing Automation Rule

An automation that works 95% of the time isn't an automation — push it to 100% or don't rely on it

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The Automatable Growth Loop (CACHE)

Break growth experimentation into four evaluable stages an AI can hill-climb, keeping humans on alignment

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Sales4 steps

The Conversion-Funnel Cold Email

Treat a cold email like a growth funnel: open, then read, then reply — optimize each stage separately

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Innovation4 steps

The Dark Factory Software Model

Ship production software no human writes or reads — replace review with simulated-user QA swarms.

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Communication4 steps

The Fast-Feedback Flywheel

Fix every piece of user feedback within minutes so people feel heard and give you even more.

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Strategy4 steps

The Lethal Trifecta

Any AI agent that combines three capabilities can be tricked into stealing your data — cut one leg.

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Productivity5 steps

The Scheduled AI Chief of Staff

Put proactive agents on a schedule to watch your metrics, surface misalignment, and coach you weekly

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Productivity3 steps

The Thin Skeleton Template

Start every project from a minimal template — agents copy its style far better than they follow prose instructions.

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Strategy4 steps

The Two-Bucket Controversial-Test Triage

Sort every risky experiment into a red-line 'never run' bucket or a 'run it if the return justifies the cringe' bucket

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Leadership5 steps

The Two-Week Deputization Rule

Under two engineering weeks, the engineer is the PM; over two weeks, the PM owns it

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Mindset4 steps

The Vibe-Coding Blast-Radius Rule

Vibe-code freely when only you get hurt by bugs; stop and take responsibility the moment others could.

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Productivity3 steps

Three-Legged Model Evaluation

Judge a model-harness combo with heavy usage, a trusted five-person taste panel, and ~10 sharp evals

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Three-Prototype Ideation

Since prototypes are now free, build a feature three ways and let real use pick the winner.

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Leadership4 steps

Under-Resource to Force Automation

Deliberately under-staff projects and hand out unlimited tokens so people are forced to automate with AI.

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