TLDR Founders 2026-05-08

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Doomers keep predicting jobs will disappear in productivity revolutions, and they keep being wrong. Excel cost about 1M bookkeeping jobs and minted 1.5M financial analysts in the same window. The Atlanta Fed reports 90%+ of firms saw zero AI impact on headcount over three years. Earnings calls run 8:1 augmentation over substitution. The data isn't subtle. The narrative is just lagging.

Companies must embrace AI adoption to thrive, with success hinging on team expertise and innovation. Levels of AI implementation range from basic prompt usage to full process automation, impacting headcount and roles. Building a culture of adaptability, hosting hackathons, and investing in AI tools are crucial strategies to drive AI proficiency and maintain competitiveness.

The companies winning the fast AI markets right now are not on the only growth curve available. Treating their trajectory as the benchmark for all AI is going to lead to a lot of misallocated capital. For the most valuable problems, the next phase of AI won't look like Cursor's growth chart. Slow growth is required to build companies that competitors can't easily copy in a quarter when the funding cycle turns.

Avoid pricing software based on build effort, as it disconnects from optimal value-based pricing. Engineers and sales teams often struggle with pricing due to biases related to development effort and historical costs. Instead, focus on the value delivered to customers, with pricing decisions informed by a dedicated pricing team if possible.

The interesting analyses that businesses want to run today depend on events that happened two years ago. If these events weren't logged, no amount of cleverness will work. Businesses need to instrument event data on day one. The cost of not having historical events when needed is high and asymmetric.

AI-native GTM strategies have evolved, emphasizing continuous monitoring and dynamic responses. Key advancements include AI agents autonomously managing multi-step workflows, tailoring outreach using customer-specific data, and shifting from calendar-based to signal-based engagement. Implementing AI-driven systems can enhance pipeline efficiency, boost win rates, and raise team productivity.

O11yCon SF (May 20-21) brings together practitioners and leaders tackling observability, AI systems, and reliability at scale. Expect hands-on workshops, peer-led discussions, and honest conversations with teams operating in today's agent-driven landscape. Use code O1C26IMLH to save. Limited availability. Register now.

Google is rolling out AI-driven bidding and budgeting features across Search, Shopping, and Performance Max. The update is aimed at helping advertisers capture more demand without increasing manual effort. Users will be able to help campaigns respond more dynamically to shifting consumer behavior. They will be able to capture more conversions by using AI to find demand and optimize spend in real-time. The new features will result in more value from the same budget while staying competitive in the fast-changing search landscape.

Flue is an agent harness framework similar to Claude Code or Codex. It is 100% headless and programmable with no TUI or GUI - just TypeScript. Flue's agents act autonomously to solve problems and complete tasks with very little code. It enables anyone to write once, build, and deploy agents anywhere.

Hashgraph Ventures' Dara Campbell argues capital raising sits above sourcing, diligence, and decks as the skill separating elite VCs and founders, citing data that founders pitch 58 investors for one seed yes, 75% of VC-backed companies never return cash, and 13% of GPs in 2024 had no plans to raise another fund. The skill is psychological, built on likability under stress, authenticity that allocators detect physically, patience that can take three years of relationship-building before a Middle East family office wires money, and the boldness to read the room and ask at the right moment for the right size.

Market structure predicts success better than traditional TAM metrics in Vertical AI. Startups should adapt strategies based on whether markets are fragmented or concentrated, avoiding direct competition in entrenched markets. This approach enables Vertical AI companies to innovate and potentially dominate by building comprehensive, unique solutions.

Startups often overlook their existing activities as marketing.

Usage is arguably the most important metric in AI and B2B.

AI is reshaping the workforce, eliminating the need for middle-layer roles and emphasizing the importance of judgment and human connection.