Good morning 👋
I don’t think there is a persona that has felt the AI adoption curve more than developers.
It makes sense why. They’re the boots on the ground, and they see problems and opportunity zones before anybody else.
Bessemer put together a roadmap of the future of developer tooling. We spent some time going through it all, and we’ve linked back to the things that you should know.
Today's highlights
Big breakdown
Software 3.0 and the golden era for dev tools
No sector has experienced a larger shift in the AI wave than developer tooling. Whether it’s code generation, code review, code generation, or evals, the dev tool market is completely unrecognizable from what it was five years ago.
The Bessemer team has covered this more than anybody, and they recently put out their roadmap for developer tooling in software 3.0.
Here are some of the biggest takeaways and opportunities directly from that piece:
Software 3.0: an era where natural language becomes the primary programming interface and AI agents don't just assist developers, they evolve into developers themselves.
Natural language becomes the primary programming interface and models execute directly on instructions. In this paradigm shift, the fundamental principles of software development are changing—prompts are now programs, and LLMs function as a new type of computer.
AI is automating the repetitive tasks that drain cognitive energy—debugging, code reviews, environment setup, incident response, and those endless low-level fixes that consume entire afternoons.
Less time debugging = more time towards architectural decisions, creative problem-solving, and high-impact feature development.
Creativity, domain expertise, and product taste matter more than mastering syntax or memorizing frameworks. The best healthcare app might come from a doctor who understands patient workflows, not a developer who's memorized React patterns.
Autonomous AI agents now manage complex workflows, orchestrate deployments, and identify and resolve bugs without constant oversight. These systems don't just assist—they execute.
Software 2.0 was about changing pixels on a screen. Software 3.0 is reimagining how software thinks and reasons.
Context itself will become both composable and portable, enabling information to move seamlessly across different systems and applications.
Organizations will invest in pipelines, tooling, and governance models designed to optimize the quality, provenance, and timeliness of contextual inputs. Small differences in context assembly can yield significant performance gains for models, creating competitive advantages for teams that can most effectively orchestrate context across internal and external sources.
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Around the horn
Uncork Capital on 21 years of venture cycles — and what’s different about this one (TechCrunch)
A Startup That Uses AI to Spot Financial Fraud Raises $60 Million (WSJ)
Private equity fundraising drops 34% from same period in 2024 (Pitchbook)
Vibe coding has turned senior devs into ‘AI babysitters,’ but they say it’s worth it (TechCrunch)
Robinhood unveils a publicly-traded venture fund (NYT)
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Survivorship Bias is Killing Founders’ Judgement: The best insights from successful startups often come from the quiet stories that include failure (LINK)
American Re-industrialization - Empty Promises vs Massive Opportunities: Medium shares a framework for technologists and venture capitalists to assess the venture opportunities in today’s manufacturing landscape (LINK)
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RIP to Financial Planning - Killed by AI: Best practices for long-range planning and how the current environment is changing it (LINK)
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- Clay
(Founder @ Confluence.VC | GP @ Outlaw)
