Harvey

Best-Rep Email Cloning

Feed the agent your single best rep's best email, then let it AB-test variants—that's how AI beats your mid-pack.

Build Only at the Magic Intersection

Don't ship what anyone could build off the shelf — build only where model and product uniquely meet.

Productivity5 steps

Context Is All You Need Prompting

Treat the model as a brilliant stranger with zero context, and supply what a colleague would already know.

Entrepreneurship4 steps

Defensible Moats for AI Startups

Four durable places to build in AI where foundation-model labs are least likely to squash you.

Peak Performance3 steps

Exposure Hours

Build taste as a trainable skill by quantifying time spent watching real people use products

Mindset3 steps

Extract the Chain-of-Thought, Not the Recommendation

Treat every advisor as an LLM: mine their reasoning, not their verdict, because their answer is trained on a different corpus.

Fast-Thinking / Slow-Thinking Org Split

Split product org into a weekly-shipping AI group and a deliberate-infrastructure group so both speeds coexist.

Productivity3 steps

Greedy-but-Smart Compute Allocation

Throw hundreds of dollars of inference at high-value problems — the value-to-cost ratio is absurd in your favor.

High Agency, High Urgency Hiring Filter

Hire for two traits only — people who see a problem and go, and people who go now.

Productivity5 steps

Hunting New Bottlenecks When AI Writes the Code

When AI removes the coding bottleneck, constraints shift up and downstream — go find them.

Self-Mastery3 steps

Learn the Tokens, Not the Depth

In the AI era, master the symbolic vocabulary of a domain rather than its exhaustive depth

Communication4 steps

Make the Other Mistake (Prompting for Brutal Feedback)

To get honest AI critique, over-correct toward brutal — the model won't actually overshoot.

Mindset3 steps

Measure in Hundreds

If your unit of measurement is one hundred attempts, five failures means you have effectively tried zero times.

Strategy3 steps

Nine Nos For Every Yes

Guard product quality with creative restraint — every feature you say yes to is a puppy you must care for forever

Innovation4 steps

Play-First AI Fluency

Build real AI intuition by playing — invent fun side projects, use everything, and share the artifact not the doc.

Productivity4 steps

Product-First AI Prompting

Steer AI builders by describing the end-user experience ambitiously, then iterate like you're coaching a collaborator

The 10-to-1 Input/Output Kill Test

When you pour 10 units of effort in for 1 unit of output, the project has run its course.

The 30-Day Agent Training Loop

Ingest your docs, then correct the agent an hour a day for 30 days until it performs like your best rep.

Innovation4 steps

The Better Tool, Same Problems Lens

Every model leap gets normalised within months — build for the boring future, not the euphoric one.

Entrepreneurship4 steps

The Chief Agentic GTM Officer Play

Pick one painful problem, one leading vendor, and deploy an agent yourself—50 hours later you're hyper-employable.

The Constrained-Resource Headcount Test

When the bottleneck isn't people, each new hire is a net productivity loss unless they uplevel everyone.

Innovation3 steps

The Escape Hatch Principle

Abstractions should let power users drop to raw control when the model doesn't fit their problem

The Forward-Deployed Engineer Vendor Column

Don't buy AI GTM tools on features—buy on who will actually get on the phone and deploy it with you.

The Full-Stack Role Collapse

In the AI era every role needs a minimum baseline in the adjacent two — deep in one, dangerous in the rest.

The GTM Agent Deployment Sequence

Roll out AI sales agents in the order of lowest effort and highest ROI: start with support, end with reactivation.

The Incognito Cry Test

Go through your own product as an anonymous customer, find what makes you cry, and buy an agent to fix that.

Entrepreneurship3 steps

The In-Product Feedback Loop

Stream user reactions straight into your team's consciousness by building feedback into the product itself

The Lead-Rich Audit

You don't need SaaStr's scale—count your website visitors and untouched CRM leads to see you're already lead-rich.

Strategy5 steps

The Platform Encroachment Test

Build where the platform's mission says it will never go — the general layer is not yours to own.

The Proxy Goal Ladder

Every metric you chase is a proxy — climb the ladder to the mission before you optimise it.

The Refounding Test

Ask how you'd rebuild AI-native from scratch — then decide whether your legacy asset helps or you should sell.

Innovation4 steps

The Three-Part AI Product Utility Equation

A useful AI product needs model intelligence, context/memory, and application/UI to all converge.

Innovation3 steps

Vibes Before Evals

For a genuinely new AI feature, start with open-ended vibes testing; add evals only once the use-case cluster is clear.