The most capable AI in your company probably runs in a terminal window on one technical person’s laptop. Your ops person, your accountant, the co-founder who handles legal, none of them will ever open a terminal.

So the best tool in the building serves one person, stops the moment their laptop closes, and everything it learns dies in their session history.

Y Combinator hit that wall and did something about it, open-sourcing their internal system. It’s called QM, and it’s the first time you can open up the operating system of the most imitated accelerator in the world and run the same thing in your own company.

So what is it, concretely? Software you install and run yourself: a server plus a database, on a cloud account you own. It has no AI of its own. You plug in your own API key, the access code that lets software talk to an AI provider directly, and from that moment the intelligence answering you is Anthropic’s or OpenAI’s.

What you get. Same prompts, same intelligence. What changes is who can reach it and what it’s allowed to do:

• A web page and a Slack bot

• Work that happens with nobody present. It runs on a server, so recurring jobs fire on schedule or when something changes, whether or not anyone is logged in.

• A private space for every person, plus shared rooms that carry their own memory, separate from anyone’s personal one.

• Recurring jobs that belong to the room where you created them, posting there for the whole team and running regardless of who set them up or whether they’re still at the company.

• Skills that can be handed over. A prompt one person perfects can be granted to a colleague or promoted by an admin to the entire company.

• Rules that hold across everyone. An organization-wide setting for how cautious the agent must be, which departments can tighten but never loosen, a log of every action and who triggered it, and hard spending ceilings per person and for the company.

• Your conversations and files stored in a database you control, with direct usage billing from Anthropic or OpenAI on your own key, plus your hosting bill.

• A license fee of zero at any headcount, and the right to modify the software under the MIT license, including commercially.

Inside you will find:

1. What’s New and What You Can Hand It

2. How to Get It Running

3. What to Actually Do With It (Real Copy & Paste Prompts)

4. Slack, Connectors and Adding Your Team

Powerful models are only as useful as the company context they can access!

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• Get more value from every model: improve retrieval, reduce unnecessary tool calls and use approximately 30% fewer tokens than off-the-shelf MCP tools.

• Stay flexible as AI evolves: access 35+ models (including Claude, GPT and Gemini) without rebuilding your context layer or locking your company into one provider

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Opus 5 shipped on July 24: near Fable 5 intelligence at half the price, with a real jump on numerical reasoning, tables, and financial modeling, the exact work a founder without a finance team keeps getting wrong.

At Startup School, Boris Cherny, the creator of Claude Code, said they deleted more than eighty percent of Claude Code’s system prompt for Opus 5 → His advice even to non-builders: every six months, delete your skills and config and see what happens. It might surprise you.

So this instead of being a pile of prompts, is six reusable Skills you build once and Opus 5 loads on its own.

📚 In this guide you’ll get copy-and-paste Skills to:

• Compare actuals to budget and prior month, explain every variance and list what to investigate

• Break down unit economics by channel and cohort, decompose gross margin and show which channel or cohort actually loses money

• Model a price change under different churn responses, give you the break-even churn and flag the segments that are underpriced

• Build a 12-month rolling forecast as an Excel file, run base, bear and bull scenarios, and tell you which single assumption moves your runway most

• Size the raise off your forecast, model the dilution across the cap table including the option pool, and check your target valuation against comparable rounds

• Build a live KPI and runway dashboard that pulls from your connected tools and generate the answer-first monthly investor update from the same numbers

Inside you will find:

1. How to Set Up Your Finance Skills So Opus 5 Runs on Your Real Numbers

2. How to Close the Month and See Where You Actually Stand

3. How to Find Where Your Unit Economics Leak Money

4. How Much Room You Actually Have to Raise Prices

5. How to Build a Forecast and Stress It Before You Bet on It

6. How to Size the Raise and Model the Dilution Before the First Meeting

7. How to Track the Numbers Live and Tell the Story Investors Trust

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📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

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↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

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ElevenLabs crossed $500M ARR in April 2026, up from $350M at the end of 2025.

Carles Reina built that revenue org from zero, as the company’s fourth employee and first investor: three years from nothing to past half a billion.

He recently laid out how he did it in a long, direct interview on Harry Stebbings’ 20VC, a set of rules specific enough to copy.

You can’t automate the engine, because the engine is people and some of his rules, like the 20x quota, stay there. What you can encode is the rest, the operational work:

• who to target

• which account is worth a call this week

• which deals are actually real

That is where Claude comes in, with Carles’s rules instead of generic best practices.

By the end you’ll have four Claude agents, each built from one of his rules:

• Concentrate on one proven ICP before scaling → the Concentration Agent

• Reach people humanly, not with transactional spray → the Timing Agent

• Land and expand → the Expansion Agent

• Public pipeline reviews and conservative forecasting → the Forecast Agent

Your reps keep the room, while your agents take the busywork.

Inside you will find:

1. Which Sales Rules You Can Actually Hand to Claude

2. Setting Up the Stack

3. How to Point Everything at One Winnable ICP

4. How to Get the Right Timing

5. How to Turn a First Small Contract Into a Whole-Account Plan

6. How to Strip the Optimism Out of Your Pipeline

7. Where the Agent Stops and the Rep Takes Over

1. Which Sales Rules You Can Actually Hand to Claude

Before you build anything, get honest about what is automatable and what is not. The fastest way to waste a month is to point an agent at work only a person can do.

Some of Carles’s rules are about people. They stay with you:

• 20x quota is a target you set and hold

• First contract in two weeks is a hiring and onboarding bar

• Reps in front of customers is a management choice

• Selling humanly, not transactionally is a principle, and it's his whole point: the moment outreach feels like AI spray, people ignore it

Build a sell more agent and you build nothing, because selling is the human part.

The other rules are really decision criteria and those can become software:

• Concentrate on one proven ICP is an instruction about where to point your list

• Reach people only when it's genuinely relevant, never with transactional volume

• Land and expand is a repeatable way to read an account and find the next door

• Conservative, public forecasting is a set of rules for deciding which deals are real

Each of those is a judgment applied over and over against fresh data, which is exactly what an agent is good at.

So the split you are working with:

STAYS HUMAN (guardrails, not agents)
- The 20x quota and the willingness to enforce it
- Selling humanly, not with transactional spray
- Reps in front of customers
- Hiring for hunters
- The room: negotiation, relationship, the final call on a deal

BECOMES AN AGENT (a decision rule applied to fresh data)
- The Concentration Agent  ← "concentrate on one proven ICP"
- The Timing Agent         ← "reach people only when it's relevant"
- The Expansion Agent      ← "land and expand through customer success"
- The Forecast Agent       ← "radically transparent pipeline reviews"

The rest of this guide builds those four agents, and each one takes its name and its job straight from one of Carles’s rules.

The “human rules” don’t disappear, they become the guardrails you write into the agents’ instructions, so everything Claude produces is filtered through the same discipline Carles applies himself.

The rest of the issue is available exclusively to paid subscribers!

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📈 Startup Playbooks
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🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

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Written by Guillermo Flor · fact-checked against Kimi’s official documentation and current community reports on X · July 21, 2026

Kimi K3 is Moonshot AI’s flagship model for long-horizon coding, agentic knowledge work, reasoning, and multimodal tasks. Its API is OpenAI Chat Completions-compatible, it accepts text, images, and video, and it offers a 1,048,576-token context window. The model always reasons, and its preserved thinking must stay intact across multi-turn and tool-calling workflows.

The short verdict: K3 looks unusually capable when a task is large, visual, tool-heavy, or allowed to run for a while. It is less compelling when response latency is the main requirement. Early independent and community evidence also suggests that strong task completion does not automatically mean strong steerability or shell-error recovery. Give it explicit authority boundaries, acceptance tests, checkpoints, and a bounded agent loop.

Contents

1. K3 at a glance

2. What K3 is—and is not

3. Account setup and first API call

4. Parameters and reasoning

5. Preserved thinking and multi-turn state

6. Streaming

7. Images, video, and document files

8. Structured output and Partial Mode

9. Tool calling and agent loops

10. The 1M context window and automatic caching

11. Prompting K3 well

12. Pricing, rate limits, and cost control

13. Coding-agent integrations

14. What the community on X is seeing

15. Production checklist

16. Troubleshooting

17. Documentation inconsistencies to watch

18. Compact cheat sheet

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• Stay production‑ready: reviewable changes, collaboration, and safeguards that help teams ship without handoffs.

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1. K3 at a glance

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In June, Peter Steinberger (the creator of OpenClaw 🦞) said: “you shouldn’t be prompting coding agents anymore. You should be designing loops that prompt your agents.”

Founders who’d been treating their agent like a chatbot rebuilt it as a loop: propose, run, check, retry, and around again.

A month later (a couple of days ago):

The ground had moved again!

Here’s the part that actually matters: the loop that fixed your agent in June is the same loop setting you up to fail in a predictable way. A graph is what fixes that.

Picture the loop you probably already have running somewhere in your product: an agent drafts something, checks its own output against a rule, retries if it doesn’t pass. It looks disciplined, but it has a blind spot built into its shape.

The thing doing the checking is the same thing that did the work!

Your subscription just got a serious upgrade.

Annual paid subscribers now get exclusive deals on the AI tools founders use every day, including:

• Framer: 1 year free

• MITO: 60% off for 6 months

• Gojiberry: 50% off for 6 months

• Cubic: 50% off your first month

• Omnia: 20% off

• Granola: 1 month free

• Slashy: 1 month free

• QuiverAI: 1 month free

• Throxy: 50% off for 3 months

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Inside you will find:

1. Why the Loop That Got You Here Won’t Get You Further

2. What a Graph of Agents Actually Is

3. The Five Patterns Every Graph Is Built From

4. How to Tell If You Actually Need a Graph (or Just a Better Loop)

5. How to Build Your First Agent Graph in Claude

6. How to Keep a Graph From Becoming a Mess

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1. Why the Loop That Got You Here Won’t Get You Further

Strip any self-improving loop down to its skeleton and you find four moves repeating:

• pick something to control

• set a target

• measure the gap

• act to close it

• then go again

A thermostat is this in its purest form. So is the eval loop you probably already run on your agent: score an output, adjust the prompt or the retrieval when the score dips, ship, repeat.

The loop earns its popularity honestly. It’s the first thing that works, and watching a number respond to your adjustments is satisfying enough that it feels like the whole job.

The problem shows up later, and it’s structural: a loop can only see its own metric, so it will find every way to move that metric, including the ways that betray what the metric was supposed to represent!

Three blind spots come from this same shape and you’ve probably already met at least one of them:

1. The metric stops meaning what you think

Take a sales agent built to book more meetings. You wire a loop around it: measure meetings booked per week, adjust outreach copy and targeting when the number dips, ship, watch the following week. For a while it works exactly as advertised.

Then someone notices the meetings are with the wrong people, because the agent found that replying to anyone showing a flicker of interest books more meetings than replying only to qualified ones.

→ The loop didn’t fail; it optimized precisely what you told it to, on a target that had stopped meaning what you thought

2. The check is an echo

The check inside most loops is the agent checking itself, or a second agent built by the same hand, trained on the same assumptions, grading the first agent’s work. It looks like verification and behaves like verification. But two systems that share a blind spot will agree on that blind spot with total confidence.

3. The job outgrows the agent

A support-triage agent starts with a single job: read a ticket, tag it with a category. It works well, so you add one more instruction: also draft a suggested reply. Then another: also flag anything that looks like a refund request.

Then a few more, each one reasonable on its own, but each one bolted onto the same prompt, the same context window, the same agent. Six months in, that one agent is doing four unrelated jobs at once, and every edge-case rule you've added for job three has to coexist with the rules for jobs one, two, and four, whether or not they actually agree with each other.

None of this means loops are wrong. It means a single loop has a ceiling, and the ceiling isn’t about model quality!

2. What a Graph of Agents Actually Is

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Finding the first customers is still brutal. And they’re the ones who matter most, because the earliest users are the only ones who:

• tell you whether the problem is real before you’ve spent a year building for no one

• give you the feedback that actually shapes the product, not the polite kind

• become the references and case studies that make the next ten easier to win

This week a repo went viral on X for taking a swing at exactly that.

It’s a Codex skill: you hand it your startup URL (or other info), it defines your ideal customer, reads public discussions for real pain and buying signals, qualifies each prospect with the source linked as evidence and drafts an opener.

So instead of trusting the demo, we ran an experiment. We made up a startup, an AI that chases down unpaid invoices for small businesses and freelancers, and gave the skill nothing to work with but that one sentence.

Then we let it loose in deep mode and watched what came back. And this is the final result (pretty crazy):

What comes back is a full report: an early-customer verdict, your ideal ICP, an evidence-backed shortlist of prospects with the public pain and buying signal behind each one, the patterns that repeat across them, a personalized opener per prospect, and a seven-day outreach plan."

In this issue we go deep on the parts that make it actually usable:

• how to install it, in Claude and not just Codex

• the six modes and when to reach for each

• what the tool did with just an idea, the real run, unfiltered

• how to schedule it so it works for you every day, dropping new prospects into an outreach queue you actually work

Inside you will find:

1. What the Skill Actually Does

2. How to Install It in Claude in Two Minutes

3. Which Mode to Use for Which Job

4. Putting the Skill to the Test

5. How to Turn It Into a Morning Radar

6. From Report to an Outreach Queue You’ll Actually Work

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• Build and iterate faster: generate sections, refine layout and styling, and ship updates in minutes.

• Scale content with confidence: update CMS collections, localize copy, and keep metadata consistent across pages.

• Stay production‑ready: reviewable changes, collaboration, and safeguards that help teams ship without handoffs.

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1. What the Skill Actually Does

Under the branding, it’s a disciplined research pipeline with a hard rule at the end.

1. It reads your product. It inspects the URL, the landing-page copy and the repository if you point it at one (or whatever describes your startup), then writes a brief: what you sell, the outcome you promise, who the user is, who actually pays, the urgent job, the current workaround, the trigger that makes someone start looking, and the disqualifiers. This brief is the filter for everything after it.

2. It searches five buckets, instead of hammering one query:

• Explicit demand: people literally asking for a tool or an alternative

• Pain: posts describing the problem as slow, manual, or infuriating

• Workaround: the spreadsheets and copy-paste rituals people build when no product fits

• Switching: cancellations, migration complaints, and missing-feature gripes aimed at a competitor

• Timing: public events like a launch, a hire, or an expansion that make your product relevant this month

3. It scores every prospect on five dimensions, and the weights tell you what it cares about:

• Pain strength (25%)

• Product fit (25%)

• Timing (20%)

• Public reachability (15%)

• Evidence quality (15%)

A prospect with no cited pain or timing signal never makes the primary shortlist, no matter how well it fits on paper.

4. It labels and drafts. Each prospect gets a stage, from high intent down to potential fit, plus one short opener that references the specific public context and nothing invented

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📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
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2. How to Install It in Claude in Two Minutes

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The thing between a solo founder and a real company was never talent. It was access. That access used to cost a salary. Now it costs a folder.

Here is the catch, and it’s why most founders miss it. Ask Claude “how do I validate my idea” and you get something that reads fine and helps you with nothing, because it doesn’t know your stage, your market, your constraints or the three decisions you made last week. Same question, generic answer.

Change the architecture and the answer changes completely.

A skill is a folder that carries the real framework, the diagnostic and the decision tree, and hands its output to the next skill so context compounds instead of resetting. Point a raw idea at the first one and it doesn’t lecture you on validation. It hands back a verdict, scored against a real checklist:

That is one skill, on one idea. Below is the full path the OS runs, from pressure-testing an idea to the cap table, and inside you’ll watch it run end to end on a real example. Each stage is a skill you build once and call when you reach it:

1. Idea Validation: decide in under an hour whether the idea holds, with Mom Test interview scripts and GO / PIVOT / KILL criteria instead of wishful thinking.

2. Business Model & Pricing: pick the revenue model, set the price, and check the unit economics (LTV, CAC, payback) before you commit a year to it.

3. Positioning: map the alternatives and claim the ground only you can hold, using April Dunford’s method rather than a tagline you invented in the shower.

4. Product: write the PRD, prioritize with RICE, and define the non-goals so scope creep doesn’t quietly kill the release.

5. Go-to-Market: go from a pre-launch waitlist to the first hundred customers with a launch sequence, not a hope that people show up.

6. Sales: run founder-led selling, qualify with MEDDIC or BANT depending on the deal, and work outreach sequences that actually get replies.

7. Growth & Analytics: instrument AARRR, pick a North Star, read your retention and churn curves, and size an A/B test so the result means something.

8. Marketing & Brand: put distribution ahead of creation, build pillar content, and run an SEO play that compounds instead of decays.

9. Fundraising: build a Sequoia/YC-style deck and work the outreach hierarchy that gets warm intros instead of cold silence.

10. Finance, Legal & Cap Table: track burn and runway, choose the entity, and handle SAFEs and the cap table without a surprise you can’t undo.

    

Inside you will find:

1. How the Founder OS Works (The Setup)

2. How You Actually Run It

3. The 10 Skills That Run Your Solo Business

4. How to Keep the OS Alive and Encode Your Own Unfair Advantage

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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Tom Blomfield, the YC partner who founded Monzo, calls that a broken way of thinking, “like taking the old way of working and adding like a more powerful engine onto it.”

The real move is rebuilding the company itself as a set of recursive self-improving loops and YC is already running three of them internally.

Blomfield delivered a chat to a room of founders, building on ideas from Diana Hu, Garry Tan and a Jack Dorsey thread.

I pulled it apart into the exact framework, the live examples, and the org changes, so you can start building your company in this shape this week.

In this guide you’ll find:

1. Why the Copilot Framing Is a Trap

2. The 5-Layer Loop Behind a Self-Improving Company

3. How YC’s Agent Fixes Failed Queries Overnight

4. Why Tokens Replace Headcount as the Constraint

5. How to Make Your Company Legible to AI

6. Why Data Is Precious and Software Is Ephemeral

7. What to Steal This Week

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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Three weeks after SpaceX signed the $60B agreement to acquire Cursor, the two companies shipped their first product together.

“Announcing Grok 4.5, our first model trained specifically for coding and agents. It was trained with Cursor and offers frontier intelligence at leading speeds and cost efficiency.”

Two numbers tell you why this matters:

• $2 / $6 per million tokens (input/output), against the $10/$50 of Claude Fable 5, the current benchmark leader

• Trillions of tokens of real Cursor usage in the training data. Nobody else has that dataset

But here is the real point for you. Models rotate every six weeks. The place where you work with them is consolidating and that place is Cursor: no longer a code editor but a desktop app, a web app, an iPhone app, a CLI, cloud agents, a code reviewer, and now co-author of its own frontier model. Half of the Fortune 500 pays for it.

And yet most founders still use it like an expensive autocomplete, or skip it entirely because “I’m not technical enough.”

Which means this news just made the gap bigger: the founders who operate Cursor properly are compounding every week, and everyone else is chatting with an expensive chatbot.

This guide closes that gap. Everything from zero: how to set it up, which plan to pick, how to run it next to Claude Code and Codex and the part that alone is worth the read: five founder workflows only Cursor makes possible.

So this edition is two things in one:

1. The News Decoded

2. The Founder’s Beginner Guide to Cursor

Inside you will find:

🟧 What Grok 4.5 is, and the honest benchmarks

🟧 The seven surfaces of Cursor in 2026

🟧 How to start from zero, with no code at all

🟧 Cursor vs Claude Code vs Codex and how to run them together

🟧 The full setup

🟧 The first-session script that builds trust before you build

🟧 The X-ray: what your developers actually shipped this week

🟧 Five founder workflows only Cursor makes possible

Let’s begin!

1. What Grok 4.5 Actually Is (and Why It Was Trained With Cursor)

The short version: Grok 4.5 is a mixture-of-experts model trained by SpaceXAI (the SpaceX and xAI merger entity) together with Cursor’s model team, on Colossus infrastructure, across tens of thousands of NVIDIA GB300 GPUs.

The collaboration started in April with a compute partnership. The $60B acquisition came in June, days after the SpaceX IPO.

The Benchmarks

Grok 4.5 is not the smartest model available. It is the most efficient one:

• SWE Marathon (can the agent work on a project for hours without losing the thread?): 29.0%, first place. Sounds low, but nobody has ever scored higher

• Terminal Bench 2.1 (can it operate a terminal on its own: run commands, install things, recover from errors?): 83.3%, tied with Claude Fable 5 (84.3%) and GPT-5.5 (83.4%)

• DeepSWE 1.0 (real bugs and features from GitHub repos): 62.0%, behind Fable 5 (66.1%) and GPT-5.5 (64.3%), ahead of Opus 4.8 (55.8%)

• SWE-Bench Pro (same idea, hardest problems): 64.7%, well behind Fable 5 (80.3%). On raw intelligence, Anthropic still wins clearly

The number that changes behavior is efficiency: Grok 4.5 solves a SWE-Bench Pro task in ~16,000 output tokens on average. Opus 4.8 needs 67,000. That is 4.2x fewer tokens, at 80 tokens per second, at a fraction of the price.

Where You Can Use It

• SpaceXAI API: $2/$6 per million tokens, fast variant at $4/$18. If your product calls an LLM, you can test it tomorrow without installing anything

• Grok Build (xAI’s CLI): it is the default model there, free for a limited time

• Inside Cursor: available today on every plan, across desktop, web, iOS, CLI and SDK, with double usage for the first week. Not the default, not exclusive: Composer 2.5 stays

• EU availability: expected mid-July

👇 Now let’s go ahead with the complete founder’s guide to using Cursor

This second part is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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2. What Can You Actually Do With Cursor

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“Investors have only two emotions: fear and greed. Complexity triggers fear. Simplicity, clarity, and confidence trigger greed. Most decks are fear machines”.

Khosla Ventures is one of the few funds that has written down exactly how it wants to be pitched. The material lives in four documents: Vinod Khosla’s ACS framework, Zack Schildhorn’s pitch framing guide (Advisor at Khosla Ventures), KV’s official five-question pitch essay and the internal deck “Pitch the way VCs think”.

I extracted every rule from all four and condensed them into a single markdown file. Drop it into a Claude Project and Claude becomes your pitch agent: it interviews you, writes the twenty headlines that carry your narrative, builds the deck inside KV constraints, reviews your existing deck with the same rubric a partner would use and stress-tests you with hostile questions before a real partner does.

Inside you will find:

1. How to Present to Investors (The ACS Framework)

2. How to Frame a Pitch That Actually Lands (The Six Ps)

3. How to Solve the Pitch Problem (The 5 Questions Khosla Wants Answered)

4. Pitch the Way VCs Think (Fear, Greed and the 5-Second Rule)

5. The Pitch Agent File: Every Rule in One Markdown

6. How to Run the Agent: From Blank Page to Investor-Ready Deck

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

Not subscribed yet? Try it free for 7 days and unlock this guide, plus our full premium library:

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Let’s begin!

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For twenty years the only answer was to hire. But Claude Fable 5 is back and changed the math!

You can now build the team without hiring it. Not a folder of chatbots you paste prompts into, but a back office with named roles, its own memory, access to the tools you already use. Boom, you have fifteen people who never sleep, never drop a thread and never send anything without your sign-off.

Inside you will find:

1. The Setup

2. Customer & Support: Triage Tickets and Turn Them Into Insight

3. People & HR: Hire and Onboard Without the Busywork

4. Operations: Never Lose a Decision or a Doc Again

5. Marketing: A Content and Distribution Engine That Runs Itself

6. Sales & Revenue: Catch Buying Intent and Never Drop a Thread

7. Finance & Legal: Books, Runway and Contracts Under Control

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

Not subscribed yet? Try it free for 7 days and unlock this guide, plus our full premium library:

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We’re already 70,000+ founders and operators inside!

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Loops are the new thing.

A loop is a system, not a message. You give it a task and a written definition of what “good” looks like, it produces an attempt, checks that attempt against the definition, and if it falls short, it revises itself and checks again on its own, before any of it reaches you.

Most founders are one step behind this without realizing it. They open Claude, retype some version of the request they made last week, get a decent single answer and call it progress.

That’s a longer conversation, not a loop, and it costs you the same afternoon every single week.

Inside you will find:

1. What Makes a Loop Actually Work: The Loop.md Framework

2. 10 Loops Every Founder Should Be Running

3. How to Actually Turn a Loop On

4. How to Build a Loop of Your Own

Attio is the AI CRM that compounds revenue around the clock.

It gives your team the foundation for moving fast, staying sharp, and scaling without breaking. Every customer signal, from emails and meetings to product usage, billing, support, and agent activity, is synced from day one, giving you a live picture of every account.

With Attio, you’ll get:

• Revenue agents, workflows, and automations across every stage of your motion

• Instant answers to anything you Ask Attio about your business

• Access to your customer data wherever you work, through Attio’s MCP, API, and App SDK

30,000+ teams use Attio to drive more revenue at scale. Are you one of them?

Try Attio Now!

Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

Get 7-Day Free Trial

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Claude Tag is the latest release of Anthropic. It works like this: someone types @Claude into a Slack channel, hands it a task and goes back to work (Slack is where it starts. Anthropic has made it clear that this shared-coworker model is coming to the other places teams work, too).

Claude breaks the request into stages, works through them with the tools it has access to, posts a running checklist in the thread and drops the result back for the whole channel to see. You tag a coworker and a coworker delivers.

That coworker is Claude Tag. It puts Claude inside Slack as a member of the channel rather than a chatbot you visit in a separate tab. One Claude per channel, shared by everyone in it, that remembers what the channel is working on. It will write or merge pull requests, run data analysis, draft the investor update, or help resolve an incident. And if you let it, it speaks up on its own.

Until now, working with Claude meant a private window: one person, one chat, one task, every session from a blank slate. Claude Tag turns that into a teammate the whole team shares.

Inside you will find:

1. What Actually Changes When @Claude Has Its Own Identity

2. The One-Time Setup: Four Steps to Put @Claude in Your Workspace

3. How to Scope What @Claude Can Do

4. The Founder Use Cases: What to Actually Tag @Claude Into

5. How to Switch On Ambient Mode Without Turning It Into Noise

6. How to Migrate Off the Old Claude in Slack Before It’s Switched Off

Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

Get 7-Day Free Trial

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You’re doing your content backwards.

Open Claude. Type a prompt. Get something passable. Post it.

The result looks like this:

I’m sorry if your content sounds like this, but its pure AI slop…

After a few months you will have posts that could belong to any company in their category. The problem isn’t Claude. It’s that there’s nothing upstream of it telling it who you are, who you’re talking to, or why anyone should care.

That upstream layer is brand strategy: your ICP, your positioning, your voice, your message hierarchy. Without it you’re not building a brand.

This guide builds both.

First, a complete brand strategy session inside Claude, one sitting, four outputs, done. Then it wires those outputs into a content machine so everything you publish compounds instead of starting from zero every Monday.

Inside you’ll find:

1. Why your content sounds like everyone else’s AI slop (and how to fix it today)

2. Build your brand strategy with Claude: the 5-layer system

3. The Claude Project that holds it all together

4. Wire your brand into the content machine

5. The 6 agents that run the whole thing

Attio is the AI CRM that compounds revenue around the clock.

It gives your team the foundation for moving fast, staying sharp, and scaling without breaking. Every customer signal, from emails and meetings to product usage, billing, support, and agent activity, is synced from day one, giving you a live picture of every account.

With Attio, you’ll get:

• Revenue agents, workflows, and automations across every stage of your motion

• Instant answers to anything you Ask Attio about your business

• Access to your customer data wherever you work, through Attio’s MCP, API, and App SDK

30,000+ teams use Attio to drive more revenue at scale. Are you one of them?

Try Attio Now!

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

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But there’s a class of market research that customer conversations don’t cover: the structural shifts in a market that happen too slowly to surface in a single interview, the TAM assumptions that feel solid until someone runs the bottom-up math, the whitespace a competitor left open that no individual customer can see because they’re inside the problem.

That’s where Claude earns its place. Not replacing the conversations but rather sitting above them, connecting signals across sources a single founder couldn’t read fast enough and telling you whether the numbers you’re building on are real.

Inside you will find:

1. How to Build the Research Project That Knows Your Market

2. How to Size the Market and Find Your Entry Wedge

3. How to Map the Buyers Who Actually Hold the Budget

4. How to Read the Market Landscape Before It Becomes Obvious

5. How to Know What the Market Will Actually Pay

6. How to Test Your Positioning Before You’ve Built Anything

7. The CLAUDE.md That Runs Your Market Research Stack

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

Let’s begin!

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Most startups can’t rely on inbound.

You have to build the list yourself, research the right partners, find the paths in, write the emails, track every conversation and keep it all moving in parallel without losing any thread.

And once you’re in conversations, the operational signals matter as much as the pitch. How fast you follow up after a meeting, how specific your outreach is, how ready your data room is when someone asks, how consistently you keep investors warm even when there’s nothing to report.

This newsletter builds the system that handles both.

Inside you will find:

1. How to Build the Context That Runs Your Entire Raise

2. How to Find the 40 Funds Worth Your Time

3. How to Map Every Warm Intro Before You Send a Single Email

4. How to Write Outreach That Reads Like It Was Written for That Investor Specifically

5. How to Run the Pipeline Without Losing a Thread

6. How to Build a Data Room That Answers Questions Before They’re Asked

7. How to Keep Every Investor Warm (Including the Ones Who Said No)

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

Let’s begin!

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Since the skills.md launch, the open-source community has been packaging workflows, domain expertise and professional judgment into SKILL.md files and pushing them to public GitHub repositories.

By early 2026, over 1.6 million of them had been indexed, spanning 23 occupation groups and 867 job categories. There’s a marketplace that catalogues them all and most founders have never opened it.

I went through it and pulled the skills that actually matter if you’re building a startup — what they do and how to use them.

Inside you will find:

1. What SkillsMP Is and Why It’s the App Store Moment for Claude

2. The Two Skills That Handle Your Entire Fundraising Workflow

3. How to Know Your Market Better Than Any Analyst You Could Hire

4. The Four-Voice Council That Ends Decision Paralysis

5. Three Skills That Run Your Growth Engine on Autopilot

6. The Executive Coach in Your Terminal

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

Let’s begin!

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McKinsey generates $16 billion a year. Not because they hire people smarter than you. Their median hire is a 26-year-old with a good GPA and no industry experience.

What McKinsey does is take that 26-year-old and spend two years systematically installing a set of analytical frameworks into how they think.

By the time that person sits across from your CEO, they're not winging it. They're running a methodology that's been refined across 50 years and tens of thousands of engagements.

That methodology is what clients are buying when they write a $2M check. Not the analyst. The framework the analyst is running.

The frameworks are not secret. Minto published the Pyramid Principle. Martin and Lafley published Playing to Win. Kaplan and Norton published the Balanced Scorecard. Gadiesh and Gilbert published Profit Pool analysis in the Harvard Business Review. The intellectual infrastructure of elite consulting has been in print for decades.

The barrier was never access to the ideas, it was the time and organizational infrastructure required to operationalize them on a live problem, under deadline pressure, for a specific client situation.

Claude Opus 4.8 removes that barrier. This guide gives you 12 skills built directly on the frameworks McKinsey trains its consultants on not paraphrased, not simplified, but operationalized with the prompt logic that makes them work on your actual problems. The intellectual foundation, why the framework works, and exactly how to run it.

This is what $2M used to buy.

Inside you will find 12 skills:

01 — Problem Framing (McKinsey Issue Tree + Minto’s SCR)

02 — Financial Modeling & Analysis (McKinsey Value Driver Tree)

03 — Market & Competitive Intelligence (Profit Pool Analysis + Porter’s Five Forces)

04 — Document Synthesis at Scale (Minto Pyramid + McKinsey “So What” Discipline)

05 — Primary Research Synthesis (Grounded Theory + Argyris Espoused Theory vs. Theory in Use)

06 — Hypothesis Generation & Stress-Testing (McKinsey Hypothesis-Driven Problem Solving + Heuer’s Competing Hypotheses)

07 — Strategic Choice (Playing to Win — Martin & Lafley + Porter’s Strategic Coherence)

08 — Execution Planning (McKinsey 7-S + Bain’s RAPID + Bossidy & Charan’s Execution Standard)

09 — KPI Architecture & Value Realization (Kaplan-Norton Balanced Scorecard + McKinsey Value Capture)

10 — War-Gaming & Risk Pressure-Testing (Shell Scenario Planning via McKinsey + Game Theory Applied to Competitive Dynamics)

11 — Executive Communication (Minto’s Pyramid Principle + SCR + Aristotelian Rhetoric)

12 — Proposal & SOW Writing (SPIN Selling + CEB/Gartner Insight Selling + McKinsey Engagement Economics)

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

Let’s begin!

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What none of them solve is the question after that. Why did it drop? Which users? What changed?

That gap is not a dashboard problem but rather an intepretive one. And it’s the reason you can have Mixpanel, Amplitude and a perfectly instrumented product and still spend Monday morning clicking through filters without arriving at a decision.

Inside you will find:

1. How to Set Up the Analytics Project

2. How to Get Your Data In

3. How to Define Your Metrics So Claude Never Guesses

4. How to Run a Funnel and Activation Analysis Without a Data Team

5. How to Build Retention Cohorts and Read What They’re Telling You

6. How to Investigate a Churn Spike in Under 30 Minutes

7. How to Run the Monday Briefing

Attio is the AI CRM that compounds revenue around the clock.

It gives your team the foundation for moving fast, staying sharp, and scaling without breaking. Every customer signal, from emails and meetings to product usage, billing, support, and agent activity, is synced from day one, giving you a live picture of every account.

With Attio, you’ll get:

• Revenue agents, workflows, and automations across every stage of your motion

• Instant answers to anything you Ask Attio about your business

• Access to your customer data wherever you work, through Attio’s MCP, API, and App SDK

30,000+ teams use Attio to drive more revenue at scale. Are you one of them?

Try Attio Now!

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

Let’s begin!

Read more

Email is one of the best channels a founder can build.

You own the list, the algorithm doesn’t change and the economics compound: every subscriber you keep is a subscriber you don’t have to buy again.

Most founders know this and still don’t do it well. They send a broadcast when they have something to say, skip weeks when they don’t and treat the list as a megaphone instead of a system. The newsletter doesn’t convert, they conclude and go back to spending money on ads.

The problem is the absence of infrastructure:

• a clear editorial position

• a welcome sequence that earns the relationship in the first seven days

• a segmentation logic that sends the right message to the right person

• a subject line process that learns over time instead of guessing every time

This guide helps you building that infrastructure, starting with a Claude interview that extracts your brand, audience and strategy in 30 minutes. Everything else follows from that document.

Inside you will find:

1. Why Email Is the Channel Most Founders Are Sitting On Without Knowing It

2. The Claude Interview: Extract Your Brand, Audience and Strategy

3. The B2B Path: How to Build a Vertical Newsletter That Generates Pipeline

4. The B2C and PLG Path: Sequences That Convert and Retain

5. How to Stop Treating Your List as One Audience

6. How to Run A/B Tests That Actually Learn

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

• 🤖 3+ New AI agent Templates Every Week

• 📚 A Growing Library of 20+ AI Agents

Get 7 day free trial

We’re already 70,000+ founders and operators inside!

The rest of the article is only available to premium subscribers.

Let’s begin!

Read more