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PUBLIC MARKETS HAVEN'T FIGURED OUT HOW TO BAKE IN AI PRODUCTIVITY GAINS

AI market gains currently favor vendors like Nvidia, while broader productivity benefits remain underpriced.

LOCKED, STOCKED, AND LOSING BUDGET: AI VENDOR LOCK-IN BITES BACK

We're headed to a token-based pricing structure and the end of fixed-price tiers.

THE AI-DRIVEN EMPLOYMENT EXPLOSION

There's a difference between a job and a task that most AI coverage misses. A software engineer's job is not "type code into an IDE." That is one task. The job is to build useful software, make tradeoffs, debug edge cases, and ship something that works. Once you separate the two, the employment debate gets sharper. ATMs reduced tellers per branch but also reduced the cost of operating branches, so banks opened more, and total teller employment rose. Where in your own market are buyers tolerating less of something they actually want, just because it's too expensive to deliver?

THE WIDE PATH: WHY MOST CURRENT VALUATION DYNAMICS ARE NOT HERE TO STAY (AND WHAT WILL)

The current sky-high valuations in the artificial intelligence sector are a temporary bubble driven by supply and demand. While developer and prosumer AI tools can achieve unprecedented rapid revenue growth right now, this window will likely close in one to two years as the market saturates and competition intensifies.

IF YOU ARE AT SCALE, YOU NOW HAVE 2 FULL-TIME JOBS

Founders now have two roles: keep the installed base genuinely happy while simultaneously building the best agent in their category, managing internal resistance, and not letting customers trap them in their past. CEO resignations are up significantly at the moment as a lot of founders and CEOs have decided this two-job reality is not something they want to do. The rule in B2B has always been to grow or die. Right now, there is less margin for error than ever before.

I REDESIGNED MY LANDING PAGE SO AI AGENTS CAN READ IT

Landing pages are input materials for agents. Businesses can either choose to make their information easily readable by agents or let every tool scrape and guess. This post discusses how to create landing pages that can persuade humans yet still have a structure that makes it easily readable by agents.

HOW TO BUILD AN AI ACCOUNT QUALIFIER THAT THINKS LIKE YOUR BEST REP

MedScout put one of its best AEs on a projector and recorded everything. Which tabs he opened. Where he paused. What made him say "this one is interesting" versus "this one is not." That tacit knowledge usually lives in someone's head as pattern recognition and never gets documented, which is why most AI account qualifiers fail. The next time someone on your team says "we should automate qualification," the right first question isn't which model to use. It's whether anyone could write down what your best rep is actually doing.

BECOME A CURATOR FOR TLDR FOUNDERS (3 HRS/WEEK, FULLY REMOTE)

We're looking for the founder of a VC-backed startup to help write TLDR Founders for hundreds of thousands of subscribers. Curators have been invited to major tech events, scouted for Tier 1 VCs, and get early access to unreleased TLDR products. Learn more [11].

ZEROHUMAN.

Automate business operations, product development, and growth tasks using AI agents.

INRŌ AI

Automate Instagram DMs to engage users, qualify leads, and manage follow-ups.

GENSPARK FOR EXCEL

Generate formulas, charts, and data analysis in Excel using natural language.

THE MESS IS THE WORK

A designer's job is not the Figma file. A PM's job is not the spec. An engineer's job is not the code. Those are outputs, and AI is great at producing them, which is exactly why the hidden part of work suddenly matters more. Sitting with the problem. Rejecting the cheap answer. Making judgment calls the prompt can't make for you. The next time you're hiring for a role and find yourself impressed by how much someone ships, the better question is whether anyone else could have decided what to ship in the first place.

REVISITING THE OUTCOME DISTORTION COMPLEX

Uber burned cash, courted controversy, and became a massive public company. WeWork did the same things and went bankrupt. The behavior didn't change, only the verdict did. In 2022, investors admitted ZIRP-era excess had pushed companies to build for the wrong environment. The same dynamics are back now under a cleaner label called AI, and "this time we know what we're doing" has historically not aged well.

COMPETITIVE STRATEGY IN THE AGE OF AI

Removing toll booths between users and the core product strengthens the castle by commoditizing the complements around it.

DEGREE OF CUSTOMER FOCUS VS DEGREE OF STANDARDISATION

A "True Product" combines high customer focus with high standardization, resulting in scalable solutions via technology.

THIS TIME IS DIFFERENT (FOR VCS)

A single AI round can now absorb whole funds.

STARTUPS BRAG THEY SPEND MORE MONEY ON AI THAN HUMAN EMPLOYEES

Startups brag about spending more on AI compute, viewing it as a growth marker, while avoiding hiring humans. CEOs claim AI investments replace human roles efficiently, boasting significant expenses on tools like Claude. The rise of the "AI-native company" highlights a push for minimal staff, potentially leading to unsustainable financial practices.

THE DEATH OF SAAS HAS BEEN GREATLY EXAGGERATED

Narratives surrounding the death of SaaS are, at best, too early. They are more of a reflection of where product leaders see the industry going rather than a decision driven by buyer behavior. The vast majority of spend remains seat-based. Consumption-based revenue has barely increased.

THE RISE OF THE PROBABILISTIC FOUNDER

The probabilistic founder is experimental by default and willing to abandon their priors. They'd rather run ten cheap experiments than commit to one expensive plan. They use quick iteration and deliberately light road maps to get results in days, not quarters. The probabilistic founder still has to be a relentless executor, because an environment that rewards running ten experiments instead of one is unforgiving to anyone who can't actually finish things.

DOW CONTRACTING FOR STARTUPS 101

The US Department of War is one of the world's largest and most stable customers. It spends hundreds of billions on modern defense systems and technology every year. Defense contracts offer funding and also long-term sustainment. Winning requires persistence, but it results in predictable margins on predictable revenue streams. This post is a high-level primer that provides a rough framework on how to approach selling to the Department of War today.

WHO GETS AN FDE, AND WHO DOESN'T: THE GREAT B2B + AI DEBATE RIGHT NOW

Forward Deployed Engineers try to understand workflow, find where data is broken, configure for specific use cases, and test, iterate, and catch edge cases before going live. Several vendors are now building toward this with agentic deployment assistants. None of them are at Palantir-grade FDE quality yet, but the vendors who close this gap first will have a very different competitive position than everyone else. The FDE constraint is currently an artificial ceiling on growth - once companies get actual deployment support, they'll switch.

YOUR PRODUCT HAS A NEW USER. IT'S NOT HUMAN

Agents now evaluate, pick, and operate products on behalf of humans who never open the UI, which makes onboarding, microcopy, and brand invisible to the buyer that matters. Stickiness built on switching cost also dies, since agents remove the pain of switching. Stripe's Machine Payments Protocol means agents can also transact. The piece pushes founders to strip UI, brand, and switching friction away from their product and look at what is left.

TOKI 2.0

Automatically plan and schedule tasks from ideas using an AI agent.

FLIPBOOK

A generative visual internet.

CLICKY

An AI buddy that lives on your Mac.

PRICING PRESSURE WILL CRUSH YOU

AI is not trying to replace your SaaS tool. Claude and GPT are the new ROI anchor in every procurement conversation, which makes every incumbent tool feel overpriced. Competitors multiply because shipping software is cheap, and incumbents bundle aggressively enough that the marginal module ends up priced at zero. The post walks through a real renewal where a Claude integration replicated 95% of a vendor's AI feature at 15% of the token cost, and the customer cut the renewal by 45%.

CODING AGENTS IGNORE THEIR OWN BUDGETS

Your coding agent cannot be trusted to watch its own wallet. Token spend across Ramp customers is up 13x since January 2025, and every obvious way to slow it down failed. A live token counter in the system prompt was never referenced across 14,000 agent messages. A request_more_budget tool got zero calls in 5,000 turns. When forced to explicitly approve its own overage, the agent said yes 97% of the time because it was grading its own work. The only setup that actually controlled spend was handing the approval decision to a separate model with its own view of the workspace. Never let the worker audit itself.

A MANAGER'S GUIDE TO REDUCING AI COSTS WITHOUT REDUCING HEADCOUNT

Most managers are budgeting the model API line item and missing the rest of the stack.

THE INTERIOR DESIGN OF SOFTWARE

When AI can generate baseline UI for free, baseline UI is exactly what gets ignored.

HOW TO REALLY STOP YOUR AGENTS FROM MAKING THE SAME MISTAKES

If your agent makes the same mistake twice, you are doing agent reliability wrong.

Try Granola to see what the fuss is about

THE NARROW PATH

Venture capital seed rounds have bifurcated into two distinct markets, fundamentally breaking the traditional "spray and pray" fund model that relied on 1,000x outlier returns. Top-tier founders with legible traction now command massive entry valuations (frequently topping $175 million) from brand-name firms, leaving a vast ocean of low-priced, deeply adverse selection startups that operate as capital black holes.

IT'S NOT JUST YOU. CUSTOMERS ARE ASKING FOR SHORTER AND SHORTER CONTRACTS IN THE AGE OF AI

Enterprise buyers are increasingly demanding shorter contract terms because the rapid evolution of artificial intelligence makes them hesitant to lock into multi-year commitments. Recent data shows that sales cycles have compressed while sub-one-year contracts have risen significantly as customers try to keep their software options open.

YOUR AI FEATURE IS QUIETLY DESTROYING YOUR GROSS MARGIN

AI needs to be treated like traditional SaaS COGS. The classic SaaS model was built on high gross margins and low marginal costs. However, add AI inference costs, model-routing costs, vector database costs, and other AI infrastructure, and that margin profile can change fast. AI can create a better product, but it can also quietly pressure the most important leverage point in the SaaS financial model. Businesses need to learn to isolate that pressure in their SaaS P&L, otherwise they will feel it everywhere.

GREAT COMPANIES ARE BUILT IN HACKATHONS

PostHog has shipped four real products out of hackathons. Logs became one after someone ran the math on Datadog's bill and saw $260K a month. The rules are what make it work. Nothing from the roadmap, no sneaking regular work in, non-engineers participate. It treats hackathons the way most companies treat roadmap planning, which is why they actually produce companies.

THE RUMPELSTILTSKIN EFFECT: WHY WE BUY

Naming a problem gives you power over it. People feel better the moment a vague struggle gets a clean label, even before anything's actually fixed. Febreze coined "noseblind" and suddenly everyone was panic-sniffing their couch cushions. Snickers named the feeling "hangry." A consultant pitching generic marketing help loses, but the same consultant selling a "Content Paralysis Crusher" package closes. The companies that win aren't always the ones with the best product - they're the ones who named the thing their customer was already feeling but couldn't articulate.

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KNOWZILLA

Provide real-time answers and guidance to sales teams during live calls.

CLAYHOG

Track and analyze how AI models represent and rank brands and competitors in their responses.

FOYER

Add a voice-based AI agent to a website to interact with visitors and guide them through the sales process.

NO DEFAULTS

No matter how obvious they appear, it's important to always question all assumptions. In many cases, what is known to be 'true' is only partially true, inaccurate, or simply the residue of a world that no longer exists. It's important to reexamine and reunderwrite your defaults from time to time. Carefully assess even those that seem to be working - these are the most dangerous, as most will not think to question them until it is too late.

STARTING A COMPANY AT THE BEGINNING OF THE EXPONENTIAL

A month-by-month account of a founder watching his moat evaporate in real time. November, two weeks of building replaces two months. December, a week becomes a day. January, a day becomes hours. February, a customer asks on a call why Claude can't just do the whole thing and nobody on the team has an answer. The useful part isn't the doom: it's noticing how quickly "we'll build it" stopped being a defensible answer.

We're hiring the founder of a VC-backed startup to help write TLDR Founders for hundreds of thousands of subscribers. Curators have been invited to major tech events, scouted for Tier 1 VCs, and get early access to unreleased TLDR products. Learn more [17].

THE TOP 10 PRIVATE AI COMPANIES ARE NOW WORTH MORE THAN EVERY PUBLIC SAAS COMPANY COMBINED

The top 10 private enterprise software companies are worth more than the entire Sapphire Pure SaaS Index of 115 public companies.

I AM AN IDIOT

A quiet argument for sitting with the idea that you're an idiot, which most ambitious people have spent their lives training themselves not to do.

AI HAS NO MOAT

SpaceX buying Cursor for $60 billion shows how the tech world is experiencing AI psychosis - Twitter was $44 billion.

THE FUNNEL FLIP: WHY AI FORCES A BOTTOM-UP ACQUISITION STRATEGY

Agents can't act in your favor if they don't understand who you are, what you offer, and whom you serve.