Articles on business, SaaS, and the software that powers organizations.
Today we chat with Reshma Khilnani, co-founder and CEO of Medplum, an open-source platform enabling companies to build healthcare applications like EHRs and patient portals. She discusses how to iterate rapidly in an industry where SOC2 compliance is just the beginning (one of the compliance tests is named after Dante’s epic poem depicting the nine circles of hell, if that gives you an idea).
It’s easy to generate code, but not so easy to generate good code.
This week we chat with Kamakshi Narayan, Director of Product Management at SnapLogic, about how APIs can apply fine-grained controls for privacy and governance to the LLM-powered AI apps vacuuming up our data.
We asked when and how often CodeGen tools fall short, what challenges developers face with these tools, and what they are doing with all of the free time these tools purport to offer.
Ben and Ryan talk with Vikram Chatterji, founder and CEO of Galileo, a company focused on building and evaluating generative AI apps. They discuss the challenges of benchmarking and evaluating GenAI models, the importance of data quality in AI systems, and the trade-offs between using pre-trained models and fine-tuning models with custom data.
Marco Palladino, CTO and cofounder of cloud-native API gateway Kong, talks with Ryan about the complexities of multi-cloud Kubernetes architecture, how AI has the potential to improve infrastructure management, and how Kong’s large action model will reshape the future of API platforms.
Ben and Ryan are joined by Nick Heudecker, Senior Director of Market Strategy and Competitive Intelligence at Cribl, to discuss the state of data and analytics. They cover GenAI, the role of incumbents vs. startups, challenges of data storage and security, data quality and ETL pipelines, measures of data quality for GenAI, and Cribl’s role in the data and observability space.
Ben and Ryan are joined by Bill Harding, CEO of GitClear, for a discussion of AI-generated code quality and its impact on productivity. GitClear’s research has highlighted the fact that while AI can suggest valid code, it can’t necessarily reuse and modify existing code—a recipe for long-term challenges in maintainability and test coverage if devs are too dependent on AI code-gen tools.
On this episode: Matt Van Itallie, Founder and CEO at Sema, a company that assesses code to improve outcomes for users, companies, and developers. Plus, friend of the show and erstwhile cohost Cassidy Williams joins the conversation.
On this episode: Eitan Worcel, CEO and cofounder of Mobb, a company that uses AI to automate security vulnerability remediation, talks about how AI can help reduce security backlogs and free up developers’ time, what security risks emerge with GenAI, and why we still need a human in the loop.
Kian Katanforoosh is the CEO and cofounder of Workera and co-created the Stanford Deep Learning class (CS230) with Prof. Andrew Ng. In this episode he talks about how companies can better measure the skill sets of their employees and how AI will change the half-life of useful skills.
Plenty of workers prefer flexibility, regardless of what the research says.
A business wouldn’t take its product development for granted, so why would you neglect the OSS community that’s fundamental to the project’s very existence?
Both new talent and late-career developers are more likely to be looking.
The core challenge posed by generative AI right now is that unlike conventional applications, LLMs have no “delete” button.
For AI tools to be useful to your team, they have to fit into your existing workflows.
If you want the tech debt metaphor to really shine, get some numbers behind it.
Providing the right context to AI can improve accuracy and reduce hallucinations.
Thousands of the company’s engineers, data scientists, designers, and developers have asked and answered questions about how things work inside their organization.
Big changes need more than technical chops to get them implemented.
Fully embracing a remote workplace means letting everyone work when they want to work.
Do you solve new problems the same way because it's already done? Or do you go with a new approach that offers more benefits?
Ad-hoc SRE principles can get you on the right track, but if you want to sustain it long term, you'll need organizational structure.
Today, it’s easier than ever for a team to monitor software in production. But it's also easy to build up a lot of tech debt around monitoring.
