Redpoint

“This has been consistently some of the best content in the entire VC industrial complex.” “A really rational reset that wasn't a total black pill, and wasn't a total white pill. It was just here's some data. There are obviously some conclusions, but you can also make your own." Co-written by Logan Bartlett, Adil Bhatia, and Lydia Day, the report covers some of the biggest questions in the public and private markets right now: - Are we in an AI bubble? - How large is the market opportunity within AI? - Will AI kill enterprise SaaS? - Which categories are most at risk of disruption? - Where is value accruing in the private markets? Full report: https://lnkd.in/eFXgyPiG Source: TBPN

Congratulations to the 9 Redpoint companies named to the 2026 ET30 list! We're proud and honored to back such an incredible group of founders. Mid-Stage: Modal, Serval Late-Stage: n8n, Legora Giga-Stage: Anthropic, ClickHouse, OpenAI, Ramp, and Stripe The ET30 is voted on by 90+ of the top VCs and corporate development leaders in enterprise tech. The list celebrates the best in enterprise tech, highlighting the growing dominance of AI-native apps and agentic systems 🎉.

This framework shows how we think about the different agentic functionality and what the implications are. Up until last year, we were really only seeing the opportunity for Copilots, which was focused on making people more productive and really just competing for software budgets. Now we’re starting to see Task Agents, which are able to run discretely for minutes at a time. This starts to tap into some level of labor spend that’s well beyond what software companies have previously been able to access. We expect that soon, we’ll see Workflow Agents, which will bring operational payroll into scope, targeting the CFO's P&L, not the CIO's budget.

This is not the dotcom bubble playing out again. In 2000, fiber utilization was below 3%, and revenue was essentially zero at the peak. Today, OpenAI and Anthropic are each generating over $20B+ in ARR. More than 90% of new data center capacity is pre-committed before breaking ground. ChatGPT reached 1B monthly active users in ~4 years; the internet took the same period to reach 70M. We feel that physical constraints, including power and land, interconnect to make overbuilding nearly structurally impossible in a way that wasn’t true in the dotcom era.

Every major tech wave looked like overinvestment at the peak (and in a lot of cases it was for that moment), but over time, it was all utilized. AI is following the same pattern, but it’s actually steeper and faster because hyperscalers have real revenue, not speculative balance sheets. This chart is the macro backdrop for everything that follows.

This week, we shared our market overview with our LPs. Co-written by Logan Bartlett, Adil Bhatia, and Lydia Day, the report covers what we're seeing in public and private technology markets right now. Here are 5 takeaways we wanted to share more broadly: 1. We got our technological revolution Every major tech wave looked like overinvestment at the peak. AI is following the same pattern, but steeper and faster, because hyperscalers have real revenue, not speculative balance sheets. Meta, Google, Microsoft, and Amazon are on track to spend a combined $779B in CapEx by 2027, a 36% CAGR from 2024. This is the largest coordinated infrastructure build in the history of technology. 2. This is not the Dotcom bubble In 2000, infrastructure was built far ahead of demand. Fiber utilization was below 3%, revenue lagged, and much of the buildout was funded speculatively. Today looks very different: OpenAI and Anthropic are each generating over $20B in ARR, and more than 90% of new data center capacity is pre-committed before breaking ground. Physical constraints make overbuilding nearly impossible in a way it wasn't in the dotcom era. 3. The Agent Maturity curve is still early Until recently, the opportunity was largely Copilots. Now we're seeing Task Agents capable of running discretely for minutes at a time, beginning to tap into labor spend well beyond what software companies have historically addressed. Workflow Agents are the next step, targeting multi-step business processes.. Ultimately, Autonomous Agents could go after a much larger share of knowledge work, tapping into a $6.1T+ opportunity in the U.S. 4. AI pressure is not evenly distributed The democratization of coding has pushed the public narrative into existential territory. Software has been the worst-performing S&P 500 sector year-to-date. At ~4x NTM revenue, the SaaS median is below where it traded during the 2008 financial crisis, the lowest multiple since 2007. Public software has sold off hard, but not all software is equally exposed. Horizontal SaaS often sits on top of workflows rather than embedded in them, so their functionality is much more likely to be subsumed by AI competitors. Vertical SaaS is protected in part by industry-specific data and regulatory complexity, while Infrastructure benefits from AI driving more consumption. Our view: the thesis that AI threatens software economics is directionally correct, but likely over-rotated at current valuation levels. 5. If history rhymes, this is the optimal deployment window In the last three technological changes, more than 60% of value was created by companies founded in years 4–6 after the seminal moment. Google and Salesforce fell into this time following the Netscape launch, Zoom and Snowflake after AWS’ launch, DoorDash and Robinhood for Mobile after the iPhone App Store launch. If we time to ChatGPT’s launch in November 2022, we’re in that window now. Full report: https://lnkd.in/e8FXxJYR

Congratulations to Abridge, Chainguard, Cyera, and Ramp for being recognized on Fast Company's World's Most Innovative Companies list! These companies are driving innovation across their industries, and we're proud to support such incredible founders. 🎉

Last week, Jacob Effron sat down with Kyle Poe, VP of Legal Innovation at Legora, for a fireside chat to discuss how AI is reshaping the legal industry. A few key takeaways from the conversation: 1. Agentic AI is changing how legal work gets done: Kyle, a former litigator, explains how chatbots don't reflect how lawyers actually work. Lawyers deal with tasks that require integration across multiple systems. For instance, with a judgment motion, you need to research the law, follow lines of authority down various rabbit holes, come back and analyze the evidence, match it against the case law, and then write it all into a memo. AI can now plan and execute this process in a multi-step workflow. 2. Unique IP and data will define law firm winners: Firms whose practice is built on proprietary, private data have a durable edge. Public knowledge is increasingly commoditized by foundational models, but institutional knowledge, built over years of client work, is something models aren't trained on and can't replicate. 3. AI will change law firm economics:  As clients become savvier about what AI can do, outside counsel guidelines are evolving fast. Firms that lean into AI will absorb efficiency gains; those that don't will see margins compress. It was a wonderful evening, and we're grateful for the continued partnership with the Legora team.