Gitential’s work on an AI Assistant for Software Delivery will help reduce delivery costs and the cost of bug fixes in several ways. Simply stated, an AI Assistant lets users ask questions (Google-like queries) and receive instant answers — data, supporting visuals (graphs/charts), explanation of the data, a summary and Next Best Actions.
Functionally, our AI will provide engineering managers, and developers “Insights On-Demand” – things you can do almost immediately to improve team and individual developer performance. The AI can provide insights to C-levels, BI Specialists, and even HR managers, too, to align on organizational OKRs, optimize budget allocations, and drive hiring strategies.
Preventing bugs in the first place is a function of optimizing teams around project specifications and requirements. Initial team selection and growth scale in complexity to the number of developers in the company (not just project or team) – and scales proportionately. This isn’t so simple, it needs to factor:
- Each developer’s programming language skill and experience (quality)
- Developer cost and performance (productivity)
- Right mix of junior, mid-level, and senior developers (efficiency)
- Relative propensity for teamwork
From a risk management perspective, bottlenecks are almost inevitable without a proper mix of experience on a team – equating to either low quality PR code reviews or delays in picking them up. Much can be said about how code complexity tends to increase dramatically as teams expand – increasing the likelihood of bugs and increasing the time/effort to find them.
Where managers have spent hours digging through analytics to find helpful insights – AI renders actionable insights in seconds – how to help a developer reduce their defect rate or what their team needs to do to improve their MTTR.