Thrilled to announce KP22, our twenty-second venture fund with $1 billion to back early stage companies, along with $2.5 billion in growth funds to back high-inflection, category-defining businesses — $3.5 billion in total. AI is reshaping every industry from the ground up, faster than anything seen before. This is the moment to build. Grateful to our team, and the founders and LPs who’ve trusted us over the years, and looking forward to partnering with the next generation of history-making companies. kleinerperkins.com/perspecti…

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One of the more underappreciated problems in enterprise AI: getting to 99% accuracy on complex, long-running workflows that can't afford to be wrong. @PoeticHQ cracked it. They built their own English-defined and deterministic programming language that lets companies automate the processes that actually run their business 100x cheaper than traditional AI agents. Excited to deepen our partnership with @markiewagner and the Poetic team.

Incredible

Anthropic is also the first model provider to feature @harvey’s Legal Agent Bench as part of their core go-live benchmarks. Glad to see legal becoming a first-class use case for AI.

in our 2026 @newlimit progress update, we announced our first candidate medicine. it has the one of the most striking effects i’ve ever seen. a single treatment accelerates recovery from alcohol in old animals. it’s so dramatic you can see it with your bare eyes!

every year @newlimit, we host friends at the lab & share our progress for 2026, we announced: - 2X increase in discovery rates with AI systems - new program for endothelial cells - 0 -> 1 medicines headed to the clinic - accelerating recovery from alcohol some highlights --

This is what happens when a great story meets AI. Trailer two: The Soldier. Edward Ross Hunter wrote The Soldier on Inkitt. Readers loved it, so we turned it into a series. AI-generated, from first frame to last. Hollywood is just starting to catch onto what we've known for years, but we're already setting the pace. ironblood.com coming July 15.

Last week we held Harvey Hacks, our internal hackathon. 27 projects total across our 200-person eng team. Wanted to highlight a few hackathon projects:

The first Marketing Engineer job board is now live: marketingengineer.jobs "Marketing Engineer jobs" became a breakout Google Search term after we introduced this new role. @Google already hired their first Marketing Engineer, and companies like @Cloudflare, @tryramp, @getserval, and @DistroKid are hiring for the same or similar role. Interested in posting an opening to our job board? There's a link at the top of the page to submit your role. This Saturday, some of the world's best builders compete at the first Marketing Engineering Hackathon at @tryprofound's HQ in NYC.

We have an uzi of AI output coming from @rippling this year. If you wanna work for me (directly) to tell that story, please DM me. Needs a solid technical foundation, coupled with the X savviness of @HunterBiden.

I'm hiring a Product Manager at @tryprofound to come build out our AI-native CMS. 5 days a week in person, NYC, CMS experience is *required*. Come ready to do the best work of your career. Interested? Chat with @woolfordalden 🖤🖤

Cool!

on day 1 @newlimit, we imagined it would take 10 years to invent real medicines. our recent results have accelerated the timeline to next year. we've raised a Series C led by @foundersfund alongside @ThriveCapital, @Greenoaks, and many others to bring therapies to the clinic. medicines for aging are among the most valuable possible technologies. we are grateful to our partners for the opportunity to pursue this mission.

Congratulations @byersblake @jacobkimmel @brian_armstrong and the entire @newlimit team!

When we started building our cloud agent infrastructure last year, no solutions existed to take the power of coding models and run them securely in the cloud. While the model and cloud providers are starting to do this, our own platform remains critical for three reasons: 1) multi-model flexibility that avoids conflicts 2) zero data retention 3) cost control Our agent use is growing exponentially month over month and this early investment in cloud agent infrastructure is letting us bring the power of agents to customers at scale, securely and cost effectively. Read more here:

Designed, built, and launched in under a year – our dual-use Marauder MUSV is officially entering on-water trials and validating a new model for modern shipbuilding. 1/3

Today we're sharing our first research collaboration with @baseten on open-weight legal agents. Using signal from LAB (our Legal Agent Benchmark of 1,200 tasks across 24 practice areas), we post-trained an open-weight model to match closed-source frontier performance. Training open-weight agents for legal creates three major advantages for Harvey: 1) Cost and latency improvements: The best-performing closed-source frontier models took an average of 22 minutes to complete each LAB task, with $50 per-task average inference cost. Open-weight inference is substantially faster and cheaper. 2) Reasoning visibility: In a high-stakes domain like legal, it's incredibly important to get visibility into agents' internal reasoning states - for audit and governance and also as a lever for Harvey to improve agent performance. Closed-source foundation model providers avoid exposing raw reasoning tokens via API to prevent model distillation. For Harvey, that visibility is a major advantage. 3) Custom training: Owning the model weights lets us customize training and modify architecture. One example: our blog’s final note on training a custom KV cache compactor. More to come on our research collaboration with Baseten.

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Ten years ago I started Stord because nobody had built the infrastructure for what happens after a consumer clicks buy. Today we raised $250M at a $3 billion valuation. Commerce now has the physical intelligence layer that merchants deserve. Full piece: stord.com/blog/the-physical-…