Now that we've looked at Q226 results, let's walk through Axon's emerging areas and markets beyond US state & local. This ever-broadening platform is adding more products to land and expand into.

• Axon is now expanding agentic AI capabilities in several new directions.
• Fusus remains the nerve center, and Axon is extending it with proactive AI agents over camera and sensor feeds, while Axon 911 extends the platform into the first emergency call.
• Axon Vision will help automate and expand a command center's real-time view of the world by continuously monitoring connected live streams.
• Axon Guardian will help automate safety oversight by continuously monitoring the personal sensors of frontline officers and workers.
• And from there, their Axon Gravity initiative aims to pull in even more connected operational tools, sensors, and data sources – making Axon the public safety system of record with AI agents working across that connected data.
• Skydio added a new fixed-wing drone capable of faster flight and a longer radius. Prepared is tying more deeply into DFR drone deployment.
• Their push into other customer segments is gaining traction. International and enterprise bookings both tripled. Federal also appears to be gaining momentum, with several large Q3 orders from DHS and other US civilian agencies.

The frontier AI market is entering its next phase. The industry is moving beyond consumer chatbots, with enterprises now starting to adopt long-running coding and work agents more deeply – all of which drive token-intensive workflows. That shift is dramatically increasing revenue and compute consumption, forcing leading AI labs like Anthropic and OpenAI to secure tens of gigawatts of future capacity.

Anthropic has captured the early lead in this agentic transition. Its enterprise-first strategy, usage-based pricing, and earlier push into agentic services have driven its exponential acceleration this year, allowing it to overtake OpenAI in quarterly revenue. OpenAI is now responding with its own enterprise platform, and has shifted its pricing structure deeper into metered APIs. Both now have rapidly expanding roadmaps to drastically increase AI capacity over the next several years, and are relying upon multiple clouds, neoclouds, chip providers, and buildout partners to get there.

This series provides a first look at Anthropic and OpenAI ahead of their coming (albeit delayed) IPOs. This post examines the rise of agentic services, the resulting revenue inflection, and the differing product and pricing strategies behind both companies. Follow-up posts then cover each AI lab's capacity buildouts and financing strategies.

This series will be of interest to hyperscale clouds, chip providers (including NVIDIA, AMD, Cerebras, and Broadcom), neocloud & site partners (including CoreWeave, IREN, Nscale, SB Energy, Hut 8, Core Scientific, TeraWulf, Cipher Mining, and Riot), and upstream suppliers.

• Agentic AI is now a top driver of compute demand. These coding agents, work agents, and managed long-running agents consume far more tokens than chatbot usage.
• Anthropic entered this market earlier, and built its operational model around usage-based enterprise revenue. That helped it reach a reported $65B revenue run rate in July, versus $40B for OpenAI. An estimated 75-85% of ARR is driven by consumption-based pricing, vs 15-25% from subscriptions.
• Anthropic has now spread its Claude models across the agentic AI platforms of all 3 top clouds, plus has embedded its full platform into AWS. These cloud partners now drive an estimated 15-20% of ARR, helping Anthropic capture enterprise customers that want to utilize cloud spend commitments.
• OpenAI has shifted its focus to enterprise over the past year, and has now assembled a set of competing agentic products (despite any potential headwinds from its major org restructuring, unwinding its exclusivity with Microsoft, and ongoing mgmt churn). Yet OpenAI has been roughly 3-5 months behind Anthropic in releasing competing agentic products.
• Critically, OpenAI has also been expanding more deeply into consumption-based pricing. This started in April with a new PAYG Enterprise plan, and its metered API is now backing several new agentic products, including a new managed agent service in AWS Bedrock.
• The gap between these competitors is beginning to close, as coding and agentic workloads have quickly risen in OpenAI's mix this year. Its consumer segment is expected to fall from 65% to 20% of the mix this year, and mgmt noted that its enterprise segment just surpassed consumer in July.
• Metered pricing should drastically improve the economics of both companies in this agentic demand wave. Revenue can expand with every additional workflow and token rather than adding seats. Anthropic is already hitting non-GAAP profitability, and OpenAI's shifts into consumption-based pricing should help reverse its worsening margins.

Compute requirements are rising alongside revenue. SemiAnalysis estimates that OpenAI and Anthropic currently have over 6GW of compute, with combined demand expected to exceed 100GW by the end of 2030. Next up are deep dives into Anthropic's and OpenAI's ongoing buildouts and financing strategies.

AppLovin has been executing on its core ad platform and AI improvement loop for years, providing ad solutions for mobile gaming studios across both supply (putting ads in your game to monetize it) and demand (showing ads for user acquisition). It is now expanding the demand side into non-gaming ads, with an initial focus on product ads for e-commerce and DTC brands.

As I noted in the Q2 preview, the June self-service launch should materially expand AppLovin’s long-term opportunity, although its contribution will likely develop incrementally rather than appear as a one-time inflection. To understand that opportunity, we first need to examine AppLovin’s revenue streams and how consumer advertising feeds its two reinforcing flywheels: continual AI improvement and operational execution.

• AppLovin monetizes both sides of its advertising marketplace: earning a cut of publisher ad revenue on the supply side and performance fees from advertisers on the demand side.
• The core economics depend on the spread between what AppLovin earns from successful conversions and what it pays publishers for the underlying ad impressions.
• Axon's predictive performance is the key lever. Even modest conversion rate improvements can materially increase advertiser returns, AppLovin’s demand-side revenue, and the value of its existing inventory.
• AppLovin’s expansion into consumer advertising and the launch of self-service should bring a much larger and more diverse set of advertisers, products, creatives, and campaigns onto the platform.
• That increased demand density in consumer ads should help monetize impressions that currently generate little value for gaming ads. Gaming ads can be served more selectively when users are most likely to convert.
• Consumer advertising should complement rather than cannibalize gaming: broader data improves ad matching across both verticals, while gaming advertisers retain the highest-converting impressions.
• This creates an AI flywheel in which more advertisers and campaign diversity generate more conversion data, which in turn improves Axon's models and ad performance.
• Improved performance then drives a second, executional flywheel: higher advertiser ROAS leads to larger bids and budgets, higher publisher yields, more ad placements, and additional supply & demand.
• The initial financial benefit may come from higher auction prices and supply-side revenue, but the larger long-term opportunity is demand-side growth as conversion rates improve.
• If demand-side revenue grows faster than publisher payouts, AppLovin could widen its economic spread, accelerate revenue growth, and further expand its already exceptional margins.

Let's look at how AppLovin is doing as it builds up its new non-gaming vertical and self-service platform. In this first post, I review Q1 results and frame what to expect in Q2. Next is a deep dive into the operating mechanics behind their strategic shift into e-commerce, and how it will flow into financials. Part 3 will cover Q2 results and the strategic priorities on the horizon.

• I was pleased with Q1 performance. They continue to show a gradual top-line slowdown as they scale, but I expect this slowdown to flatten out and turn into a reacceleration as self-service strengthens their flywheel.
• Overall revenue grew +59% to over $1.8B, and TTM grew +66% to $6.2B.
• My only concern was the notable deceleration in U.S. revenue growth, which had remained above 60% for the prior year before falling below 50% in Q1.
• Profitability remains jaw-dropping. TTM Adj EBITDA and GAAP net margins hit a record 83.3% and 63.5%. TTM FCF margins rose +4pp to 71.6%, putting them at a Rule of 138 TTM.
• They repurchased $1B in shares (about ~75% of FCF) and have $2.3B remaining under the authorization. Debt is not a concern.
• They continue to see momentum in non-gaming ads, which has now been dubbed their "Consumer vertical" housing e-commerce, DTC, and beyond. They rode holiday momentum into a surprisingly strong Q1, then implemented a significant model improvement in mid-April that lifted ROAS.
• They are also seeing renewed momentum in their core vertical. Gaming studios are now leveraging Generative AI to move faster, plus are starting to experiment with hybrid monetization strategies (IAP+ads) now that non-gaming ads are available.
• The self-service platform opened in late June and will not be a heavy factor in Q2 results beyond the continued beta.
• I worry about the market's understanding of their shift into consumer ads and the new self-service platform, and how (and how soon) the financial impacts will become visible. I believe there are some incorrect assumptions that have been muting its stock performance.
• However, Q2 should see a significant uplift in product ad performance from that model improvement in mid-April. This would provide a clear sign of their ongoing momentum and help counter any misconceptions about the self-service impacts.

Past coverage

If you need to catch up, I previously covered AppLovin in January and February.

• Ad nauseum (Jan-26) covered the mechanics of supply and demand in modern digital advertising, AppLovin's platform and how it dominated the mobile gaming ad market, and its big pivot into self-service consumer (e-commerce and DTC).
• Evolution of Axon ads (Feb-26) covered their evolution over 2022-2025 and strategic directions across Axon model improvements, e-commerce pilot, AI-generated creatives, and CTV.
• Mixed results from pilot (Feb-26) looked at the initial results of their e-commerce pilot.
• Also see my recent piece on Reddit's shifts (Jul-26), which looked at how AI search is changing discovery, resulting in "Google Zero" (zero click-throughs). I believe this is to AppLovin's benefit as a unique ad delivery platform over a niche audience of mobile gamers in a high-attention ad format.

Now that we've covered Reddit's Q1 results and the strategic priorities across its user and advertising sides, let's look at how Reddit is evolving across mgmt changes, AI search, and advertising tooling. We'll also walk through the broader shifts happening in content discovery across AI citations, licensing deals, and legal cases.

Content discovery is a timely subject. We've had a number of updates this week between legal outcomes on AI use of content, and a steady drumbeat of media coverage on the ongoing declines in click-through traffic. Reddit was down 10% at one point today after WSJ pushed rumors as it renegotiates its AI data licensing agreement with Google.

• Reddit has been adding talent from Google and Meta with deep expertise in advertising, personalization, AI search, and video.
• They continue to focus heavily on user engagement. Reddit Search usage and WAUqs are up +30% after new UI changes put it more front and center, and it has become critical to driving engagement by improving content discovery and onboarding.
• Search also gives Reddit a potentially meaningful new monetization surface. Reddit is now adding deeper shopping details to AI search results, leveraging DPA product catalogs into a carousel of relevant product ads.
• The advertiser stack continues to evolve rapidly, with new DPA formats, e-commerce integrations, automated creative tailoring, AI-generated ads, and improved measurement.
• Max Campaigns is becoming the core automation layer of Reddit Ads Manager. They are still pushing existing advertisers into Max Campaigns, and will be opening it up to new signups soon.
• New split-testing capabilities allow advertisers to directly test and compare various campaign & ad strategies. Customers can also easily validate the impacts of automated campaign mgmt, targeting, and budget optimization within Max Campaigns. This should help accelerate the adoption of Max Campaigns, and embeds a new feedback loop to continuously improve ad performance.
• DPA still has a substantial runway. The onboarding of mid-market and SMB advertisers is improving through e-commerce integrations with Shopify & WooCommerce. Besides using DPA ads within AI search results, new DPA formats like Collections and multi-vendor Shopping Listings are now emerging. Mgmt also hints at an eventual expansion of DPA beyond e-commerce, into other ad categories such as travel, services, and autos.
• Video is emerging as another growth vector. The new CTO has extensive video and ML algo experience from Facebook, and Reddit is beginning to expand the use of video as another medium for community interaction.
• Reddit remains one of the most-cited sources across major AI engines, despite a citation pullback by Perplexity.
• AI search citations & legal battles are generating a lot of FUD, but I believe Google might be showing us the start of a better path forward. Google plans to increase emphasis on firsthand opinions and community perspectives in AI Search, which seems likely to further elevate Reddit's visibility and brand in its AI results.
• Reddit's conversational data is becoming an increasingly important asset for brands and AI providers. The rise of AEO/GEO is encouraging companies to build organic Reddit presences to improve their standing in AI results.
• While licensing negotiations and lawsuits with AI engines could create additional monetization upside in data licensing, the core investment thesis still rests on Reddit continually strengthening its ad engine. The financials are showing us that their efforts here to drive user engagement & advertiser demand are clearly working.

Sections:

• Google Zero
• Mgmt changes
• User engagement moves
• Advertiser tooling moves
• A shift in video strategy?
• Competition from Meta's Forum app
• Google Search overhaul
• AI citations
• Legal battles
• A new era in web marketing
• Final thoughts

I continue to like what I am seeing with Reddit's execution today and its opportunities ahead. Let's walk through their Q1 results and what they are most focused on going forward.

In part 1, we'll walk through Reddit's appeal, Q126 results, and the main areas of focus across the user and advertiser sides of their ad platform. In part 2, we'll look at mgmt changes, new monetization directions, and advertiser-focused enhancements. This will also be of interest to other ad tech players like Google, Meta, The Trade Desk, and AppLovin.

• Reddit continues to show strong execution, with TTM revenue growth accelerating to over 70%. Int'l continues to grow faster, and is now nearly 21% of the mix.
• Profitability continues to impress, with every TTM margin rising to a new high. With TTM FCF margin hitting a record 35%, they are now at a Rule of 106 TTM.
• Despite slowing user growth, Reddit continues to dramatically improve its ad revenue per user. ARPU has grown more than 40% for 4Qs straight, and their most mature market, the US, has grown more than 50%.
• Their international expansion efforts continue to show results. Int'l ARPU growth accelerated sharply to over 50%, now matching the pace that the US has sustained over the past year.
• They continue to focus their efforts on improving user onboarding & engagement (driving page views & ad impressions), improving audience targeting (driving ad performance), and automating advertiser tooling (driving ad demand).
• Users are clearly engaged, with Reddit's pool of content growing roughly +21% over the past year. Shopping related conversations grew even faster at +40%.
• Their advertising base continues to broaden into shopping (e-commerce & DTC) and B2B brands, with advertisers growing more than 75% and newer products (such as Dynamic Product Ads and Reddit Max) delivering meaningful improvements in advertiser results.
• Reddit is rapidly automating its ad tech stack to allow advertisers to more easily find relevant audiences and convert purchase intent. They recently added Generative AI-backed features that give it the ability to tailor an ad to a specific persona, and to generate more relevant long-form ads based on community commentary.

Sections:

• Not like the others
• Q126 financial results & KPIs
• User engagement
• Content pool
• Advertiser performance
• Macro impacts?

I looked at Cloudflare's Q4 results back in February, and their positioning in agentic AI in April. As I posited then, their Q1 is typically the seasonally weakest and are likely to provide an entry point. However, the market decided to go all in on Cloudflare in the week leading up, with the stock rising ~25% into Q1 results. The results were good, but a surprise RIF caused the stock to plummet back by around that same percentage.

I hoped to hear more on the RIF during the IR briefing a month later, and it instead provided more context on the reasons why. They have been busy developing an AI & data stack for internal use, noted on the earnings call as "Cloudflare OS" that is now available to every employee across the organization. The CFO provided major margin target updates based on the projected productivity gains from this new tool, which will spread agentic use more deeply across R&D, S&M, and G&A teams. Like with Q1 earnings, the stock rose into the week leading up to IR day only to fade back again after. Thankfully, it is now up +25% YTD.

• Cloudflare’s Q1 results were strong for its seasonally weakest quarter, with revenue growth reaccelerating to +33.5% and mgmt raising its FY26 guide to nearly 30%.
• The headline issue was not the quarter itself, but the surprise RIF that slims their workforce by 20%, which mgmt framed as a one-time organizational reset around internal AI productivity rather than a traditional cost-cutting exercise.
• The core message across IR Day was that Cloudflare is becoming agentic-first, leveraging its own Act 2 and Act 3 stacks to automate work across R&D, S&M, finance, and other operations.
• Their main effort here is a new internal AI operating layer called Cloudflare OS, which gives employees secure and governed access to agentic models, operational context, internal pools of data, and dynamic model routing. Cloudflare is now using this to automate employee workflows, improve productivity, and support higher long-term margin targets.
• Cloudflare OS also provides a key proof point for their agentic AI ambitions in Workers, as it ties together multiple parts of their platform (Workers, Workers AI, AI Gateway, Sandboxes, and Cloudflare One) into a working example of what enterprise agentic AI infrastructure should look like.
• They are not only showcasing this internal tooling stack to top customers to drive Workers and Cloudflare One demand, but are also toying with spinning it into a new managed Agentic Ops product for less technical enterprises without the resources to build it themselves.
• Large-customer momentum remains strong, with faster revenue growth than overall. And that momentum increases further upmarket, with deals over $1M up sharply, and their largest customer segment (>$5M in ARR) growing +50%.
• It also looks like Workers and agentic AI are driving some momentum in smaller customers too, implying strong sequential growth over the past 2Qs.
• Workers remains the biggest emerging growth vector, with active developers reaching 5.5M after adding a massive +1M net new developers this quarter alone. They noted at IR day that Workers drove ARR growth of +137% in FY25, and called out several new initiatives at frontier AI labs and AI providers that are being backed by Workers.
• Its Zero Trust capabilities are becoming more strategically important as Workers and AI agents need secure access into private apps, databases, and API/MCP servers. They noted at IR day that Cloudflare One drove ARR growth of +43% in FY25.
• Despite near-term margin disruption from the RIF and ongoing gross margin pressure from Workers demand rising so quickly, Cloudflare’s AI productivity gains while leveraging its own agentic infrastructure give it strong operational leverage going forward. Mgmt is now raising long-term operating margin targets from 20% to 30%, free cash flow margin targets from 25% to 30-35%+, and are expecting GAAP profitability in 2028.
• Cloudflare is also shifting its long-term financial “north star” beyond Rule of 40, suggesting visibility to Rule of 50 in FY27 and further upside beyond.

Part 2 will cover the agentic layers in Workers being adopted by frontier AI labs, as well as their strategic positioning with Act 4.

Rubrik just reported its latest Q127 in early June, then turned around days later to hold its annual FORWARD conference and first dedicated IR briefing.

Let's look at how Rubrik is progressing in my ongoing thesis, and how its resiliency platform is expanding into Agentic Ops. Beyond the hyperscaler clouds and other next-gen security providers, this will also be of interest to data lakehouses like Snowflake & Databricks and AI providers like Anthropic & OpenAI.

• Rubrik is starting to see the artificial tailwinds of material rights shift into artificial headwinds, which will worsen across FY27.
• I believe the emergence of new Identity and AI Ops (RAC) solutions will drive continued hypergrowth, to greatly counter (and possibly offset) those headwinds. Identity is already hitting $50M in ARR in its first year, and RAC was implied to be growing even faster.
• Profitability continues to trend well. They've been cash flow positive now for 6Qs, and non-GAAP profitable for 3Qs.
• Land and expand continues to trend well, with record net new large customers (outside of their seasonally strongest Q4) and rising deal sizes.
• They embedded a new agentic orchestration layer into their overall platform stack, powered by their Predibase acquisition.
• This new layer enables multiple new product directions, including Rubrik AI, Agentic Ops (Rubrik Agent Cloud), and several new automated remediation services (Cloud Apps, Identity Roll Forward, and SaaS Enterprise Tools recovery) that greatly simplify IT recovery complexity for enterprise customers.
• They expanded their Identity solution with a unique new post-intrusion recovery offering (Roll Forward), and acquired a startup to add Identity Continuity (high availability after an identity service failure).
• This startup also recently added two new services that could greatly enhance the agentic identity security capabilities within RAC.
• Annapurna has been revamped into a new module within Rubrik Agent Cloud. This service now enables an AI agent to securely access an enterprise's pool of unstructured data without needing the overhead of data pipelines and ETL workflows.
• Misunderstanding of these artificial headwinds seems likely to create entry points over the next few earnings reports, at least until RAC & Annapurna revenue starts showing up in earnest or GAAP profitability hits breakeven.

NVIDIA hopes physical AI and edge AI will spread this agentic demand wave farther out, as AI agents help to automate and streamline operations across every industry. NVIDIA wants to spread its entire ecosystem outward, anchoring itself as the end-to-end stack powering the coming waves of demand from autonomous vehicles, robotics, smart devices, industrial automation, and smarter communication networks.

I've been entirely focused on NVIDIA's success in AI data centers in my coverage thus far. Let's finally walk through these further out waves, as its ecosystem spreads across physical and edge AI, NVLink Fusion partnerships, and the roadmap beyond Vera Rubin. It will also be of interest to the hyperscalers and neoclouds that hope to serve this physical AI demand wave.

• Physical AI is starting to fully unleash autonomous vehicles, robotics, drones, and other devices. NVIDIA is seeding each of these areas with ecosystems, software stacks, and open models.
• Physical AI, edge AI, and industrial AI will eventually build towards another inflection point for agentic AI, as compute demand increases further from the ongoing automation of enterprise & industrial workflows.
• NVIDIA is spreading GPU capacity out across multiple levels for these needs – from on-device systems, workstations, edge servers, on-premise clusters, regional or sovereign neoclouds, and hyperscalers. Users will have flexibility to choose between open models running locally, on-demand cloud inference, or dedicated AI capacity.
• They recently announced a new line of superchips designed to reinvent the modern Windows laptop. Let's hope it goes better than their first foray with DGX Spark.
• NVLink Fusion lets partners combine their custom CPU and AI chips into NVIDIA's scale-up fabric, expanding the overall AI ecosystem while preserving NVIDIA's fabric as the anchor point. These partners gain an immediate scale-up network, and it seems likely to also position them for pairing with NVL72 GPUs in disaggregated inference.
• Vera Rubin Ultra and Feynman will see a major expansion of their scale-up networking and introduce optics, resulting in larger supercomputer clusters.

Part 4:

• Expanding compute outward
• Physical AI
• Edge compute systems
• NVLink Fusion
• Future Roadmap