Search the archive

Read more on the Metronome blog

PATIENT CAPITAL WILL EAT THE WORLD

Venture capital has grown into massive funds like Andreessen Horowitz and Sequoia, but the traditional VC model struggles with today's software and AI markets. Growth-stage software no longer requires or generates capital in the way early SaaS or consumer internet companies did, and AI companies increasingly need infrastructure financing, not conventional venture funding. Institutional VC is constrained by LP mandates, fund timelines, and deployment expectations, forcing investment even when better opportunities would be to wait. As a result, funds invent narratives to justify current positions while real liquidity remains scarce due to limited IPOs and conservative M&A markets.

YC SPRING 2026 REQUESTS FOR STARTUPS

YC published a list of 10 startup areas it wants to fund this spring. The themes span AI-native workflows replacing legacy software, stablecoins as financial infrastructure, and modernizing heavy industry and government. Notable entries include "Cursor for PMs," AI-native agencies, and modern metal mills.

FINDING GTM ALPHA

'Alpha' is an investment's outperformance over a market benchmark. It is what separates market-beating investors from the rest. GTM alpha starts with having better data than your competitors. Unique data is a competitive edge. Top teams stay ahead by experimenting, learning, and launching better plays faster.

WHEN TO RAISE VC

Venture capital requires extremely high returns, often 50x, which rules out businesses in small or focused markets that can still generate strong profit and exits. Forcing a VC narrative onto a business misaligned with hypergrowth pressures leads to wasted time and compromised product decisions. Founders should match their financing strategy to market opportunity, using angels or bootstrapping for steady growth and VCs only when capital materially changes outcomes.

HOW TO BUILD AI PRODUCT SENSE

Product managers and founders can develop AI intuition by using tools like Cursor for non-technical work. This interactive guide walks through practical exercises that help you understand AI capabilities and limitations firsthand. The best way to know what AI can do for your product is to experience it yourself rather than relying on demos or documentation.

MOLTBOOK

moltbook is a social network for AI agents where agents can share, discuss, and upvote content. Humans can observe, but the platform is designed for agent‑to‑agent interaction.

POLYVIA

Polyvia is a Visual Knowledge Index that turns large collections of images into a queryable, disambiguated source of truth for multimodal agents and knowledge workflows.

HUGO

Hugo is an AI support teammate that resolves customer tickets autonomously, reducing support workload while maintaining quality responses.

WE NEED MORE ANGEL INVESTORS

Founders drive more economic value. However, they don't create value in a vacuum - they need angel investors for capital. AI might make things cheaper, but that doesn't change the need for capital, only how it is used. Early capital from angel investors results in more viable companies that are more likely to succeed.

THE ECONOMICS OF A SUPER BOWL AD

Ro ran its first Super Bowl ad featuring Serena Williams to boost brand awareness for its GLP-1 products. The fully loaded cost including media, production, talent, and additional spend is $16–29M. Success is measured both short-term through customer acquisition and traffic spikes, and long-term through brand awareness and marketing efficiency. The upside is asymmetric and compounding while downside is capped. Ro chose this moment because the product is ready, the market is large and underserved, and Serena's story aligns with the brand.

WE'VE BEEN QUIETLY BUILDING OUR OWN 0 -> 1 REVENUE STACK INTERNALLY AT @TRYRAMP - RAMP REVENUE

Sellers at Ramp don't have to worry about switching between dozens of systems just to figure out who they should reach out to or what they should say.

AI'S IMPACT ON 2026 BUDGETS

CFOs are opening budgets for AI tools that promise productivity gains, but the bar for traditional SaaS spend is rising as every new purchase must compete with the perceived ROI of AI alternatives.

WHICH AI LAB IS WINNING THE ENTERPRISE?

OpenAI and Anthropic are emerging as key players in the enterprise AI sector, with Anthropic reportedly gaining ground on OpenAI.

Let your team focus on product. Use WorkOS Pipes →

SOFTWARE IS DEAD…AGAIN!

Cloud software valuations have cratered to 10-year lows, with the median NTM revenue multiple hitting 4.1x. Investor confidence in the SaaS business model is fracturing as AI disruption risks threaten the retention rates and terminal value assumptions that powered the last decade of software investing. The path back requires companies to prove stable retention over multiple quarters.

LEADERS, GAINERS, AND UNEXPECTED WINNERS IN THE ENTERPRISE AI ARMS RACE

a16z surveyed 100 Global 2000 CIOs and found OpenAI still leads enterprise AI with 78% production usage, but Anthropic posted the largest share gain at +25% and now sits at 44% penetration. The surprise winner in enterprise apps is still Microsoft, not the startups dominating tech Twitter. Average enterprise AI spend rose from $4.5M to $7M and is expected to hit $11.6M this year.

THE BEST AI STARTUPS DO THE TRAINING FOR YOU. IT'S ON YOU TO MAKE THE AGENT AWESOME — NOT YOUR CUSTOMERS

The old model was to sell the software and let the customer figure it out. Businesses now need to do the work to make their AI great before they hand over the keys. AI agents will fail if improperly contained. It is up to the AI vendor to make it work. Customers shouldn't have to get agents to work.

WHAT TAM SHOULD ACTUALLY TELL YOU

Stop calculating “potential customers × potential price” and start with what the world currently spends solving your problem. That's your actual market today. Everything beyond that isn't market size, it's a thesis about growth. Most founders are stacking 3-5 speculative theses without realizing it, and since each compounds risk exponentially (30% × 30% × 30%), understanding this can dramatically improve how you allocate time and opportunity cost.

HOW PRODUCT DISCOVERY CHANGES WITH AI

AI has collapsed the cost and time of building and testing products, which means feasibility, viability, and usability are no longer the hard parts: desirability is. The critical bottleneck in product discovery is now understanding what customers actually want. Teams need to shift investment toward deeper customer insight and research to answer the fundamental question before building anything.

and focus on building what's next. See it in action

Spreadsheets weren't built for ownership at scale. Carta

connects equity, compliance, and stakeholder workflows in one platform - so you can issue shares with confidence, stay compliant by default,

RELATE

Modern sales CRM designed for B2B startups.

ROBYNN

Robynn is an AI marketing platform that helps founders create branded content.

KOMBAI

AI agent for real frontend tasks: build UIs, refactor, and integrate.

LOYALTY IS DEAD IN TECH

Big Tech has figured out how to acqui-hire without the acquisition. License the IP, hire who you want, leave the rest behind. No regulatory review, no shared outcomes. Microsoft did it with Inflection, Amazon with Adept, and Google with Character AI. The unwritten oath between founders, employees, and investors is dead. When picking your next company, ask your VC who else they've backed in your category and what happened to employees at the founder's last company.

THE ORIGINS OF GENERATIONAL COMPANIES

Microsoft, Oracle, NVIDIA, and Starbucks all started by selling something to a tiny, often invisible market before stumbling into bigger opportunities. The playbook isn't “envision a radically different future and build it,” it's figure out a real need by selling, learn by iterating on what doesn't work, avoid trying to predict the future or convince markets, and stay in the game long enough to catch a demand wave when it hits.

RETHINKING SLACK

Slack faced issues with feature bloat and complexity by late 2019, as the product accumulated many additions without a cohesive structure.

FOLLOW YOUR PASSION, BUT NOT LIKE THAT

Chase your passion with a blend of curiosity and practicality rather than as a blind directive.

REVISITING CLARITY OF THOUGHT

Clarity of thought stands as a key differentiator for successful founders, influencing all aspects from hiring to sales.

TRADITIONAL ADTECH IS DEAD. LONG LIVE ADTECH FOR AI 📣

AI could create a new form of advertising that may actually flourish.

B2CC - CLAUDE CODE IS YOUR CUSTOMER

We are now shifting into an 'agents as customers' era - companies need to be thinking about how to become the vendor that AI agents prefer.

THE NEW RULES FOR FUNDRAISING IN THE AI ERA

Vivek Ramaswami and colleagues at Madrona outline how AI has disrupted traditional fundraising benchmarks. Rapid spikes in user growth and revenue no longer signal durable success, so investors now focus on momentum, unit economics, clear expansion pathways, and customer dependence. Founders must prove that growth is sustainable, customers are genuinely locked in, and their business has a defensible trajectory rather than just hitting arbitrary ARR milestones.

WHAT'S WORKING IN AI FOR GTM

53% of GTM leaders are seeing little to no impact from AI. This report interviewed 30 who are and compiled 40 of their best workflows across content, prospecting, and sales. Most can be built with ChatGPT or Claude plus off-the-shelf tools. The report walks through step-by-step examples with exact prompts.

PMF IS A LAGGING INDICATOR. START WITH HABIT FORMATION INSTEAD

Grant Lee argues that Product-Market Fit is a lagging metric and advises founders to focus first on whether they are building recurring habits rather than one-off solutions. By targeting frequent, low-friction problems and designing products that users invest in quickly, startups can create sticky behaviors that drive long-term engagement. Examples like Slack and Gamma illustrate how habit-focused design outperforms solutions that only address infrequent or high-friction needs.

BUILDING AI PRODUCTS: LESSONS FROM PRODUCTBOARD SPARK

The fundamentals of product management haven't changed. Building AI products is still about solving real problems for real people. Start by matching customer pain to tech capabilities, build prototypes fast, measure quality rigorously, and evolve your team as you scale. The teams that ship great AI products will be the ones that learned fastest from what didn't work.

IMAGINE

Imagine is an AI-powered builder that turns ideas into fully functional, secure, and scalable applications with built-in cloud infrastructure and compliance features.

DECIPHER

Decipher AI generates your E2E tests, maintains them as you ship, and catches issues before customers do.

ADA

Ada is an AI data analyst that creates professional reports from any dataset.

THE FUNDABILITY TRAP

Fundability is the measure of how well a startup fits with the current venture consensus. Investability is a measure of potential outcome and financial return. VCs that conflate the two or don't recognize the difference risk building an entire ecosystem that rewards fundability. Chasing fundability over investability has never been a reliable path to outlier outcomes and fund returns.

SOFTWARE IN A POST-ABUNDANCE WORLD

AI is transforming software production by making it cheaper and faster, leading to smaller teams, reduced margins, and shifting value from code creation to decision-making and integration. This shift challenges old economic models where large teams thrived under abundant capital and growth incentives, pushing the industry towards leaner operations and disposable software. Capital now focuses on leveraging AI in areas like healthcare and manufacturing, where software integration with domain expertise is harder to replicate, refining the industry's focus from quantity to strategic depth and adaptability.

AEO: OPTIMIZE FOR THE FOLLOW UP

Traditional SEO treated search as a transaction.

DON'T SOLVE PROBLEMS THAT DON'T EXIST.

Avoid solving nonexistent problems by focusing only on what's essential for progress and value creation.

$281B FROM ONE CUSTOMER

Microsoft's Q2 FY2026 earnings impressed with $81.3 billion revenue and Azure's 39% growth, though the stock fell due to capacity constraints.

RE-PRICING THE SAAS BOND

Software will either converge to something bond-like or something closer to a normal operating business.

playbook. Read the report

THE FUTURE OF AI CREATIVE TOOLS

FLORA, an AI-powered creative tool company, raised $42 million in Series A funding to give professional creatives more control over their workflows. Founder Weber Wong criticized Silicon Valley for misunderstanding creatives' needs, emphasizing the importance of taste and control in creative work. The platform's node-based interface supports companies like Nike and Lionsgate by integrating generative models into customizable workflows, enabling both manual and autonomous creation.