TLDR FOUNDERS 2026-02-25

Replit

THE ENGINEERINGIFICATION OF EVERYTHING

The engineering mindset and tools are infiltrating non-engineering roles, creating a feedback loop that redefines professions, such as "design engineering." This shift is fueled by LLMs, increased capital investment in B2B SaaS for non-engineers, and evolving professional identities. The success of this trend makes roles more autonomous and flexible, urging everyone to adopt a builder's mindset to stay competitive.

IS SAAS DEAD? NO. BUT ONE THING IS CLEAR: IT'S UNSTABLE

A $500M ARR company worth only $1B. That's PagerDuty right now - 2x revenue. The median public SaaS company trades at 3x. Workday's CEO changed the company narrative three quarters in a row. The argument here is that Claude 3.5 Sonnet shipping in June 2024 was the real inflection point for AI eating software - not ChatGPT. Competitive advantages that used to last years now last months. SaaS isn't dead, but revenue durability - the thing every VC priced their multiple on - might not exist anymore.

HOW TO FIND YOUR "ONE METRIC TO RULE THEM ALL"

The founder of HotelTonight tracked 80 metrics at his first two startups. Both failed. At HotelTonight, he picked one - total transactions - and it worked. Slack found that teams sending 2,000+ messages had 93% retention. Airbnb zeroed in on nights booked. WhatsApp only tracked MAU.

SO YOU WANT TO HIRE A FORWARD DEPLOYED ENGINEER: HOW TO KNOW IF YOU NEED ONE AND HOW TO GET THE ROLE RIGHT

Forward Deployed Engineers (FDEs) embed directly with customers to build the 'last mile' of the product to work in production. Unlike traditional solutions consultants or sales engineers, FDEs are still very much engineers who write and debug production code. Founders are turning to the FDE model to roll out highly technical AI products to remove the blockers that stand in the way of adoption. This post looks at what makes this role successful. FDEs can be powerful when deployed intentionally, but they're not the answer for every company or customer, and it takes a ton of careful design to get a return on investment in the role.

WHO OWNS PRICING?

Most SaaS companies have pricing spread across 3-4 different systems. Entitlements are hardcoded. Product catalogs live in multiple places. Launching a new tier takes six months. This piece lays out four pillars to fix it: unified catalog, decoupled entitlements, real-time metering, and a GTM control plane. Whether or not you buy the full framework, the diagnosis is right. If changing a price at your company takes an engineering sprint, something is very wrong.

you can reach.

FALCONER

Self-maintaining docs for engineering teams.

RUNANYWHERE

Run AI models locally on any device.

HOW AI-ENABLED STARTUPS ARE MOVING FASTER — AND REWRITING THE VC PLAYBOOK

AI is reshaping the relationship between founders and venture capital. A new kind of startup is emerging between the big headlines: the Silicon Valley small business. These companies are tiny, extremely leveraged, and shockingly productive. AI is being used as a force multiplier to ship faster, iterate more aggressively, and hit meaningful revenue in months rather than years. The result is a quiet but profound pressure on the traditional VC model. Expectations are being warped by a small group of AI-native outliers that don't need the level of capital the industry was built around.

PATTERNS ARE THE END OF PRODUCT ANALYTICS

AI agents and conversational interfaces are evolving customer interactions beyond traditional product analytics, which focused on linear sequences of clicks. Instead of static metrics, businesses need to analyze patterns of behavior across various channels to accurately capture dynamic consumer journeys. Pattern-based analytics can reveal evolving customer intent and improve the overall experience by highlighting efficient paths and potential friction points.

WHY AI MOATS STILL MATTER (AND HOW THEY'VE CHANGED)

AI is an incredible tool for differentiation. However, the AI-ness of capability is not a source of defensibility. The defensibility of software resides in owning the end-to-end workflow, in the context in which it's applied, becoming the system of record, having a network effect, and being deeply embedded within customers. The market opportunity for software today is largely labor.

AUTOMATING TASTE

AI systems can encode prioritization and quality standards to apply product judgment consistently across software development.

ANDY RACHLEFF ON WHAT MOST FOUNDERS GET WRONG ABOUT PRODUCT/MARKET FIT

Founders often err by focusing on altering the "what" in their value hypothesis, rather than recognizing a technological inflection point for product development.

TWO POSITIONS THAT STILL CREATE DURABLE AI MOATS

CONCENTRATION IN VC

3% of deployed capital delivered all returns across 1,200+ investments and 350+ exits.