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Orca is the next-gen IDE for building with coding agents.

MOATS DON'T WORK WHEN BRIDGES ARE FREE

Software that only sells code will not survive the AI wave. There's no moat when anyone can use AI to recreate the software. Only companies with a two-sided market, a proprietary dataset, a hardware component, or a messy real-world integration layer have a real moat. The software industry is about to be re-sorted, and a lot of companies that look like category leaders won't make it.

NUCLEUS NOUNS

Most apps revolve around one or two nouns, like 'Channel' and 'Message' in Slack and 'Project' and 'Issue' in Linear. These are nucleus nouns, and every other noun is a 'satellite'. Thinking about apps in terms of their nucleus nouns allows developers to cut to the core of what an app is supposed to do. Customers feel it when a company loses sight of its nucleus nouns. Companies with a firm understanding of their nucleus nouns can use them as a weapon by making them part of their brand.

YOUTUBE IS THE NEXT NEOBANK

The next wave of neobanks probably won't look like banks at all. Every past winner found the spot where incumbents overcharged, SoFi on income-based underwriting, and Nubank on no-fee cards in Brazil. Now, stablecoins have made the deposit layer so cheap that accounts alone don't get you anywhere. What matters is owning the income relationship. YouTube has paid creators $100B+ since 2021 and just turned on stablecoin payouts.

TOTALIS TAKES $500K IN STABLECOINS FROM YC

Totalis just became the first company to receive YC's $500K entirely in USDC, settled on Solana in three transactions, including a $1 test.

TASTY

Everyone says they're "taste-led" now, but ask them to define it, and you get nothing.

WHEN MOVING FAST, TALKING IS THE FIRST THING TO BREAK

Talking takes time, and consensus is expensive and slow, so it is the first thing to break down when moving fast becomes the biggest priority.

CANNON FODDER: PRE-SEED INVESTING IN THE AGE OF AI

Pre-seed investing faces challenges as AI lowers startup barriers, flooding the space with new ventures.

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ORG DESIGN IN THE AGE OF AI

Competitive moats change. The moat used to be who could ship the fastest. It is now learning speed: how quickly an organization can absorb what AI makes newly possible and restructure around it. The companies that will pull ahead are the ones that can build as if they were designing their organizations from scratch, knowing what AI can do.

THE SAAS RECKONING: STOCK-BASED COMPENSATION WAS NEVER FREE

For a decade, SaaS companies added stock-based comp back on the way to "adjusted" EBITDA and pretended that 5-8% annual dilution was a footnote. Employees never bought it. They sell RSUs on vest day, budget the income like salary, and experience a stock decline as a pay cut. Now AI is repricing the entire SaaS universe, and companies that rode the add-back face an ugly choice: grant more shares to keep talent (brutal dilution when the stock recovers) or hold the line and watch people leave.

HOW TO NAME YOUR COMPANY: THE COMPLETE PLAYBOOK

Nothing in your brand gets used more often or for longer than your name. It shows up on every invoice, every pitch deck, and every email signature. Most founders still pick theirs by committee brainstorm or by whatever .com happens to be available. This post walks through what separates names that stick from names that get changed in two years, and why "safe" names that try to please everyone end up saying nothing at all.

HOW GTM-AS-PRODUCT CHANGES THE GAME

Product teams compound every sprint, but marketing blows up and starts over every time a new CMO or agency walks in. The ICP gets rewritten, the positioning deck gets shelved, and four months of messaging work vanishes. AI makes it possible to finally close that gap. One marketing leader with the right setup can build a living system where content draws from validated frameworks, new hires inherit full strategic context on day one, and this quarter's learnings actually feed into next quarter's campaigns instead of being forgotten.

FOUNDERS, EQUIP YOUR AGENTS

AI now initiates most sales conversations, shifting the buyer journey. Companies are reorganizing their go-to-market strategies to adapt to AI's influence, with marketing teams building tools in-house to drive growth. While AI handles small-value purchases autonomously, complex enterprise decisions remain human-led, necessitating equipping AI as effectively as internal teams.

INSTANT

Real-time database and backend built for AI-coded apps.

APERTURE

Conduct AI-led interviews and rank candidates based on performance instead of resumes.

VEQUIL

Deploy and manage AI agents to analyze and trade on prediction markets.

CONQUERORS OF WORLDS

Out of ~15,000 seed-funded startups per fund cycle, maybe one produces a $10B+ revenue company. The people who build those aren't a better version of great founders, they're a different species entirely. A 2 sigma founder builds a $10-100M business. A 3 sigma founder builds a unicorn. A 4 sigma founder doesn't adjust their ambition to match reality, they adjust reality. Each level is a 10x jump, not incremental.

THE "MISMANAGED GENIUSES" HYPOTHESIS

For the last decade, progress in AI came from making a single model bigger and feeding it more data. This post argues that the next leap won't come from scaling further. Current models are already good enough. The real bottleneck is how we organize and coordinate them. Better systems wrapping existing models will outperform one monolithic model trained on everything, and the field is only starting to figure out what that looks like.

EVERY FEATURE SHOULD EARN ITS PLACE

Building a feature has never been cheaper. Carrying one is just as expensive as it's ever been. Every addition makes the product harder to learn, harder to maintain, and harder to evolve, and products rarely fail for lack of features. They fail because they accumulated too many that nobody had the discipline to kill. When execution gets cheap, the right response isn't to ship more, it's to raise the bar for what gets to stay.

THE AI LOCK-IN IS BEGINNING!

Enterprises making an AI architecture decision today are deciding who gets to own the state that builds around it.

ACT 2

By the time a startup needs a second product, it's perfectly set up to fail at building one.

KNOW THYSELF

Stop borrowing someone else's compass.

HOW I BECAME TECHNICAL AF

A non-technical founder went from a few college CS classes to shipping production features daily with AI coding tools, now ranked top 1% of engineers at small startups.

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SF IS BACK - AND THE TECH SOCIAL SCENE IS BEING RUN BY THE TERMINALLY ONLINE

SF's tech social scene is driven by the "terminally online," with connections and events organized through platforms like X and Partiful. Traditional social proof is replaced by mutual online interactions, impacting how relationships and trust are formed. This shift suggests a potential broader trend where online social dynamics shape real-world interactions globally.

THE SAAS ROUT OF 2026 IS EVEN WORSE THAN YOU THINK

For the first time in the modern era, software stocks now trade at a discount to the S&P 500. The iShares Software ETF (IGV) is down over 21% YTD and roughly 30% from its September 2025 peak, wiping out about $2 trillion in market cap. The structural problem: AI is breaking the link between headcount growth and revenue growth. If agents replace seats rather than complement them, the per-seat recurring revenue model that justified premium software valuations could unwind entirely.

VENTURE CAPITAL HAS A STARTING LINE PROBLEM

Venture capital often favors well-networked founders who start with advantages like connections and financial runway, leaving others at a disadvantage from the start. This disparity isn't about in-room investor bias, but rather the different starting lines shaped by existing networks and resources. Underrepresented founders must proactively build credibility within these ecosystems to secure funding, despite systemic inequities.

ANTHROPIC SEES THE MOAT. DO YOU?

Legacy enterprise software won by storing records. The next generation of companies will win by building enough trust with enterprises to work with the workflows where important actions actually happen. Trust converts capability into permission to work in enterprise. Anthropic is not the only company pursuing that position, but it is one of the clearest examples of it.

HOW TO USE AI WITHOUT LOSING YOUR MIND

Most people are failing the basic test of whether their AI use cases are even big enough to matter. This essay splits work into execution (automate it) vs exploration (use AI as a thought partner, not an answer machine) and argues that most people should ignore 90% of new AI tools and focus on a small set of mature ones applied to their hardest problems. Good antidote to the anxiety-driven "you must use every new tool" narrative flooding tech Twitter.

ADVICE AND LESSONS FOR FOUNDERS

Online startup narratives often distort reality through selective success stories and misleading exit optics that hide weak or zero-return outcomes. Cofounder misalignment, role overlap, and shifting contribution levels create common failure modes that surface as resentment or functional redundancy. Recurring friction from legal threats, employee apathy, and relationship-driven sales increases founder workload and emotional strain.

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XPACK

Connect Your Agent to Any API/MCP.

ROCKET

Decide what to build, build it, and track competitors in one place.

BRILA

Generate one-page websites using content from Google Maps reviews.

⚠️ WARNING FOR FOUNDERS: THE CURRENT DANGER ZONE IN VC

The market can stay irrational longer than most founders can stay solvent. Improving your financial profile should be your top priority. It could take a couple of years. Either get profitable, or ensure that you have enough funds to last for a very long time.

“BIG AI", AND THE VALUE OF A BUSINESS

Over 70% of mid-market B2B distribution businesses are expected to change hands in the next decade. This monthly update from the CEO of a B2B logistics software company explores how making operations more systemized and "Amazon-good" can double a business's value before exit. He also makes the case for "one to many" distribution through channels and partnerships over traditional direct sales, arguing the old SaaS playbook is losing steam.

DEMAND MIX, SHAPING, AND AI AS (DYS)FUNCTION MULTIPLIER

AI will not fix broken product orgs. It will accelerate whatever dynamics already exist. If your team treats engineering as a bottleneck and optimizes around feeding it work, AI just speeds up that dysfunction. If your team is oriented around learning and shaping demand toward real outcomes, AI makes that more effective. Most orgs never examine their "demand mix," meaning where work actually comes from and how it gets shaped, and that gap is about to get a lot more expensive.

THE AI PROBLEM MATRIX

There's only a certain amount of venture capital dollars entering the ecosystem every year.

WE BUILT EVERY EMPLOYEE AT RAMP THEIR OWN AI COWORKER

Ramp's employees were stuck using AI because of their environment setup, so the company built its own AI productivity suite to make every employee an AI power-user.

WHY MOST INVESTORS WASTE TIME ON BAD IDEAS

Most investors don't have an analysis problem, they have a filtering problem.

THE GOLDEN RULES OF AGENT-FIRST PRODUCT ENGINEERING

PostHog overhauled its AI architecture twice before landing on these five principles.

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AGENT SKILLS ARE THE NEW SDK (AND YOU SHOULD BE BUILDING ONE)

Developer infrastructure companies need to adjust their product for AI coding agents as a competitive necessity. Agent skills make it possible to have a 10x solutions engineer for every single customer account. The value of many infrastructure products scales with coverage, and that was previously bottlenecked by developer memory and discipline. Skills dislodge the bottleneck of developer bandwidth.

THE GROWTH METRIC SILICON VALLEY LOVES MOST IS ALSO ITS LEAST TRUSTED

Cluely's CEO admitted to inflating their ARR figures, highlighting a common issue among AI startups. ARR, a key growth metric, lacks standardization, allowing for manipulation and misuse. This challenge raises trust concerns among investors, though experts caution against imposing heavy auditing on startups, advocating for transparency instead.