Driver

New Embedded Executive Podcast: Tools Create All Your Documentation with Adam Tilton of Driver #embeddedsystems #podcast https://lnkd.in/eAvZpyaE

Top Start-Ups of 2024 - Driver Name: Driver Website: www.driver.ai Founded: 1.5 years ago Location: Austin, Texas Industry: Automated documentation creation  Technology: Codebase engineering Driver provides a way of conveniently generating the documentation that tech businesses really need, but don’t want to have to tie up their engineering staff producing. The automated process that this highly regarded start-up has come up with delivers interactive and easily updateable explanations of codebases through use of a large language model (LLM) arrangement. This process also means that clients aren’t exposed to issues if key engineers leave or when iterative changes get made to products further down the line. Based in Austin, Texas, this enterprise was co-founded by serial entrepreneur Adam Tilton (who was previously at Nike) and Daniel Hensley (former Head of Engineering at Infinity AI). Its initial funding of $8.8 million has been sourced from GV (Google Ventures) and Y Combinator, along with a few angel investors. The benefits of the technical documentation that Driver is able to produce can be witnessed across numerous aspects of its clients’ business operations. Companies with longstanding legacy products, where the original engineering team involved have all moved on, so there’s no longer sufficient continuity, can avoid needing to assign their already stretched resources to painstakingly reviewing the original codebase when challenging customer queries arise. Instead, this can be done for them, so they can prioritise development work that will be of greater long-term benefit. Likewise, a company’s field application engineers (FAEs) don’t have to spend valuable time making product collateral (like application notes, etc.), but can concentrate on the customer-facing activities that will bring in revenue. As Tilton told EPDT; “No one's full time job... READ MORE https://lnkd.in/e9nWfhuj Sander Arts Alex Honeysett Satish bagdi Aaron Monieson Shane Ghiotto Jacob Furniss Nicole Conley

Generative AI isn't just making it easier to create technical documentation. It is providing us with orders-of-magnitude changes to how we produce consistent, structured documentation at scale. This allows us to define a new era of how we do technical documentation different from that imposed by the constraints of the past. Consider a 10 million line codebase you want to build documentation for. How long would this take a team of 3 engineers? Months, years, never (you wouldn't even try)? With Driver, you can automatically create structured, consistent, and complete technical documentation for the whole codebase in minutes or hours. And we can automatically keep it up-to-date as the code changes. Users can then adapt and build on top of this structured comprehension of the codebase—the source of truth—to build custom documents targeting specific levels or abstractions or audiences (such as product managers or executives). This is a game-changer for shared understanding, collaboration, and getting products and features to market faster.