2048 Ventures 🧬 🤖 ⚙️

Pre-Seed should not take months and months to raise! We are thrilled to announce that @2048vc is launching Pre-Seed Fast Track to help you get funding in 10 business days. If you are raising $500K - $1.5M Pre-Seed round in Vertical AI, Deep Tech, Health or Bio we would love to meet you! We offer clear and transparent process and money in the bank within 10 business days of the first meeting. To start the process submit your pitch through our short form - 2048.vc/fasttrack_pitch If there is a potential fit we will reach out within a few days and follow these steps to fund you: Step 1: Intro meeting via Zoom: 30 mins where you meet with 1 member of our team. Step 2: Deep Dive via Zoom: 60 mins where you meet with 3-4 members of our team. Step 3: References + In-Person Meeting: We will chat with your early customers and professional references, and will spend a few hours to get to know each other in person. Startups are long journeys and we know how important the investor-founder fit is, so we will gladly pay for your travel. Step 4: Term sheet: We make you an offer from $250K - $750K Step 5: Wire: We are high conviction and don’t wait for the rest of the round to come together - we wire as soon as we sign the docs. To learn more about Pre-Seed Fast Track visit 2048.vc/fasttrack. We can’t wait to review your pitches and to meet you! @2048vc // #preseed

Excited to share our @2048vc Portfolio Companies CTO AI Usage Survey. We surveyed CTOs of 2048 Ventures backed startups on their usage of AI. We are excited to share with you our learnings. If you are a CTO of an early-stage startup and are using AI in creative ways that are not covered in this summary, we’d love for you to share them in the comments. --- Summary: Across all conversations held with portfolio CTOs, one thing became very clear: AI is now a default part of the engineering workflow. Every team is using AI to write code, and in some cases, engineers are no longer writing code manually at all. The quality of AI-generated code is broadly seen as strong. It is typically cleaner, more structured, and comprehensive as compared to human-written code. However, this comes with limitations: AI still struggles with architecture and long-term system design. This makes it critical for the engineer to define intent, structure the systems, and ensure coherence across the codebase. The main tools used are Claude, Codex, and Cursor, but the most effective teams have been building multi-modal workflows, using different models for planning, implementation, and review, and cross checking outputs between them. CTOs have reported anywhere from 5x - 20x increase in velocity of shipping and building product. In more advanced cases, teams are re-architecting their entire engineering pipelines around AI, introducing spec-driven development, automated testing loops, and even early forms of multi-agent systems that can handle large portions of implementation autonomously. However, this acceleration is not immediate; several teams noted that meaningful gains only came after investing in better testing infrastructure, clearer specifications, and tighter feedback loops. AI has also begun to reshape how CTOs think about talent and team structure. Most CTOs expect to hire fewer engineers than they would have previously, with a growing emphasis on individuals who can operate at a higher level of abstraction with AI, with key skills being designing systems, writing specifications, and managing AI-driven workflows. There is broad agreement that the role of an engineer is shifting from writing code to orchestrating and validating systems built by AI. Questions asked and summary of answers: 1. Are you using AI to build code? How do you find the quality of code written by AI? - All teams are using AI to write code, with some engineers rarely coding manually anymore. Code quality at the implementation level is strong, and is often cleaner and more comprehensive than human-written code. However, AI still struggles with architecture, system design, and business context. Human oversight remains critical for defining intent and structure. 2. Which platforms are you using? What are the use-cases of each? - The core stack is Claude, Codex, and Cursor. Teams are increasingly using multiple models in parallel, with Claude being used for planning and writing, Codex for reasoning and review, and Cursor for IDE integration. Use cases span code generation, testing, refactoring, spec writing, and code review. 3. Is AI usage uniform across the team? - Within engineering, usage is largely uniform and highly adopted. Outside of engineering, adoption is more uneven, with some use in operations and GTM (e.g., note-taking, transcripts), but less integration into core workflows. 4. How much are you spending on AI tools? - Most teams spend between $200–$500 per engineer per month, with lighter users closer to $100 and heavy users exceeding that range. Spend is not seen as a constraint relative to productivity gains. 5. How much faster are you shipping? - CTOs report 5x–20x increases in development velocity. Some tasks that previously took days now take hours. More advanced teams report order-of-magnitude improvements in throughput, though gains depend on infrastructure and workflow maturity. 6. What non-obvious workflows have become possible because of AI? - AI has enabled spec-driven development, where engineers write detailed specifications instead of code. Other workflows include automated test generation and validation loops, rapid design iteration, reusable “skills” or abstractions, and AI-generated pull requests from issues. 7. Are you using AI agents? If so, for what workflows? - Yes, but mostly in simple forms. Most teams run a few parallel tasks or agents rather than large orchestrated systems. More advanced teams are experimenting with multi-agent pipelines (e.g., PM, worker, QA agents) to automate large portions of development. 8. Where is AI meaningfully outperforming humans and where does it consistently fail? - AI excels at implementation, refactoring, test generation, and repetitive tasks. It struggles with architecture, context understanding, and long-term system design. The biggest failure mode is producing correct code for the wrong objective. 9. Has AI changed what you look for in engineering talent, or the quantity of engineers you thought you would hire? - Yes. Most CTOs expect to hire fewer engineers. There is a shift toward hiring engineers who can operate at a higher level, focusing on system design, specifications, and managing AI workflows rather than writing code. 10. What AI tools do you wish you had that aren’t built yet? Tasks that are manual and cumbersome that you want automated? - CTOs want better orchestration layers for managing multiple agents, improved context handling across large codebases, and more reliable autonomous systems that require less human oversight. Quotes: - “We’re building internal teams of agents to handle research, PR review, and implementation in simple loops. We moved away from fragmented repos and now use agents to build the agent team, which then builds the scaffolding and infrastructure. The real work is no longer writing code, but designing the pipeline for how code gets generated and, more importantly, validated. If you can’t measure whether the output is correct, you can’t trust it. At this point, strong testing is critical, because the volume of code being generated is far beyond what humans can realistically review.” - “At this point, the goal isn’t to write better code, it’s to build a system where agents can reliably generate, validate, and improve code on their own.” - “What used to take us three to four days now takes a few hours. Once you have a strong codebase and the right abstractions, AI can handle most of the implementation.” - “We’re probably 20x faster than writing code by hand. The challenge isn’t generating code anymore, it’s making sure what you ship is actually correct.” - “The real unlock has been investing in testing and harnesses. Once you have that, you can let the system run in loops and get much better results.” - “We’ve shifted from writing code to writing skills, like reusable patterns the AI can apply. Then we continuously refine those skills over time.”

Registrations are now open for the @2048vc ⚙️ Deep Tech Pitch Competition Join us on May 28 in Boston as part of @Techweek_. 📍 Hosted at @MassChallenge, in partnership with @BoostVC - An afternoon of early-stage deep tech teams, pitching live in front of investors. - A look at what’s emerging at the earliest stages. - A strong panel of judges to be announced soon. 🎟️ Register: partiful.com/e/WgE2wyAFVShd…

Registrations are now open for the @2048vc🧬 Biotech Pitch Competition We’re kicking off @Techweek_ on May 27 in Boston! 📍 Hosted at @biolabs Join us for an afternoon focused on early-stage biotech, with founders pitching live in front of investors. Expect an exciting mix of scientists, operators, and investors across the ecosystem — and a look at what’s emerging early. A strong panel of judges to be announced soon. 🎟️ Register: partiful.com/e/fWRK866fdFge…

🗞️ 2048 Ventures Portfolio Company News: Century Health: Interview With Founder & CEO Vish Srivastava About The Health Technology Company pulse2.com/century-health… Century Health // @2048vc // #startups // #VC

‼️ Deadline extended: 2 more days to apply to the @2048vc Pitch Competitions Apply to pitch during @Techweek_: Boston: 🧬 Biotech • May 27 | ⚙️ Deep Tech • May 28 New York: 🏥 Healthcare • June 2 | 🤖 Vertical AI • June 2 💰 $50K prize for each Biotech, Healthcare, and Vertical AI winner 💰 $100K prize for the Deep Tech winner (in partnership w/ @BoostVC) Submit your application by SUNDAY April 26, 11:59 PM ET 🔗 Apply: 2048.vc/pitchcompetiti… 🔗 Learn more: 2048.vc/pitchcompetiti…

🗞️ 2048 Ventures Portfolio Company News: Laminar Wins Gold 2026 Edison Award for Physical AI that Powers the Self-Driving Factory prnewswire.com/news-releases/… @RunLaminar // @2048vc // #startups // #VC

‼️ 24 hours left to apply to the @2048vc Pitch Competitions LAST chance to apply to pitch during @Techweek_: Boston: 🧬 Biotech • May 27 | ⚙️ Deep Tech • May 28 New York: 🏥 Healthcare • June 2 | 🤖 Vertical AI • June 2 💰 $50k prize for each Biotech, Healthcare, and Vertical AI winner 💰 $100K prize for the Deep Tech winner (in partnership w/ @BoostVC) Apply by TOMORROW April 24, 11:59 PM ET: 2048.vc/pitchcompetiti… 🔗 Learn more: 2048.vc/pitchcompetiti…

⏰ 48 hours left to apply to the @2048vc Pitch Competitions Final chance to apply to pitch during @Techweek_: Boston: 🧬 Biotech • May 27 | ⚙️ Deep Tech • May 28 New York: 🏥 Healthcare • June 2 | 🤖 Vertical AI • June 2 💰 $50K prize for each Biotech, Healthcare, and Vertical AI winner 💰 $100K prize for the Deep Tech winner (in partnership w/ @BoostVC) Submit your application by April 24, 11:59 PM ET 🔗 2048.vc/pitchcompetiti… 🔗 Learn more: 2048.vc/pitchcompetiti…